I declare that this is my own work and should this declaration be found to be untrue I acknowledge that I may be guilty of committing an academic offence. SPE001-3 Dissertation The Effect Birth Date Has On Choosing To Study A Sports Related Course At An Educational Institution 26th April 2013 Carl Page (1008889) Carl.Page@study.beds.ac.uk Mr. D Pears SPE001-3 Dissertation Contents Abstract ...................................................................................................................... 2 Introduction ................................................................................................................ 3 Review of Literature ................................................................................................... 5 Methods ................................................................................................................... 14 Results ..................................................................................................................... 20 Discussion ................................................................................................................ 26 Conclusion ............................................................................................................... 37 References ............................................................................................................... 39 Appendices .............................................................................................................. 51 Carl Page (1008889) Page 1 BSc (Hons) Sports Science and Coaching SPE001-3 Dissertation Abstract Page, C.G. and Pears, D. (2013) The Effect Birth Date Has On Choosing To Study A Sports Related Course At An Educational Institution. Purpose: The Relative Age Effect (RAE) in the academic study of sport. The aim of this study was to investigate the relationship of those students being born on a certain date will indeed influence the decision to study a sports related course at an educational institution. Methods: Contacted various levels of educational institutions and requested student information from sport related academic courses such as their date of birth, gender and course title. The gatekeeper and the data managers securely passed the relevant information requested. Organised and arranged data collection into three birth date month groups; September-December, January-April and May-August within appropriate statistical software and spreadsheet software. Results: Statistical analysis was determined where appropriate using Chi-Square tests and formulas. The main findings show there to be significant results in the birth dates of an individual and studying a sports academic course as with the distribution of births across all levels of education were not equally distributed throughout the year. The observed frequencies showed the birth date is highest for the months of September-December and lowest for the spring and summer months. It also showed an over populace representation of male students compared to females who are studying a sport related academic course at an educational institution. Conclusions: Therefore it can be derived from the results presented that the birth date did have a large influence on choosing to study a sports related course at an educational institution. Key Words: Relative Age Effect, birth date grouping, gender bias, sports academia. Carl Page (1008889) Page 2 BSc (Hons) Sports Science and Coaching SPE001-3 Dissertation Introduction A number of things are under our control, while others are not under our control, for instance our own birth date is something we cannot control by ourselves. The issue of when we are first required to start compulsory schooling at an educational institution in England has received considerable critical attention. It is possible that two friends with birthdays merely days apart can be placed into different year groups. Subsequently this may have an effect on your own life when placed and labelled as being the youngest in the year group. Although our friend shall be identified as the oldest in their year group, in which they have been situated in. In recent years, there has been an increasing interest in the start dates for an educational institution within England. Normally this occurs during the September month apart from Universities which start in early October. An individual can decide to participate in studying a sport related course at an educational institution at various ages i.e. from thirteen onwards. However, a major problem with this kind of application is the maturity of the individuals can possibly differ since their ages may influence choosing to study a sports related academic course. Throughout this paper the term RAE will refer to/will be used to refer to Relative Age Effect. Currently a considerable amount of literature has been published on the socalled ‘birth date effects’ or Relative Age Effect. These studies explain the bias that is evident within individual youth team sport and within an educational setting. The participation is typically higher between people who are born in the early appropriate selection phase and have not attained an adequate understanding of the normal distribution of live births. There is an increasing concern that there is a smaller Carl Page (1008889) Page 3 BSc (Hons) Sports Science and Coaching SPE001-3 Dissertation number amongst those who are born in the later selection phase being disadvantaged. This concept has recently been challenged by other researchers’ studies demonstrating it does not apply to all sports at different levels of performance and genders. Hence Reilly, (2010) demonstrated the Relative Age Effect occurrence has been observed in scientific visionary, and achievements academically within the primary schools and entry into universities. However it is still unclear if this advantage is simply from more experience which is linked with the earlier birth date. Van den Honert, (2012) argues that his study does not support Reilly’s, (2010) view since it was discovered there is a smaller amount of competition for places. Though it is worth mentioning it was the opposite for senior elite level athletes having a significant effect. Also it might have been the case for males yet findings indicate there is an actual statistical significant Relative Age Effect linking of junior male players with falling of the effect as they increase with age. Some researchers (e.g. Ford and Williams, 2011) have attempted to draw fine distinctions between there being no Relative Age Effect in the birth dates of awardwinning athletes in male professional team sports. Although they had expected normal frequencies of birth dates to be equal across four equal groups and have no over-representation of younger or fairly older performers. Nevertheless their investigations also showed that performers are more likely to be born late in the selection year when compared to those earlier in the year. As opposed to most investigations into the Relative Age Effect in competitive sports and educational success has been explored for instance by Larouch et al. (2010) who proposed it is Carl Page (1008889) Page 4 BSc (Hons) Sports Science and Coaching SPE001-3 Dissertation still unclear whether the RAE occurs in the recreational sports and leisure activities too. Therefore it has been shown the Relative Age Effect not being as dominant within the leisure physical activities through adulthood when compared to competitive sport. Review of Literature The statute (Great Britain. Education Act 1996) established that: A person begins to be of compulsory school age— a. when he attains the age of five, if he attains that age on a prescribed day, and b. otherwise at the beginning of the prescribed day next following his attaining that age. Bedford Borough Council (2013) advises the school year in which the children will become five they are generally permitted to begin in or during the Reception year. In particular this means children will start attending their first formally compulsory educational institution either in September or the term in which they reach the age of five. Nevertheless it is dependent upon the current course of action in place within the child’s Local Education Authority. This is supported by Central Bedfordshire Council (2012) which recommends children to be normally given entry to an educational institution in the month of September following their fifth birthday. This is known as the start of the reception year within an educational institution. Consequently children who have not reached the legal school age will not have to commence being in an educational institution, until they are five years of age. Furthermore in northern European countries it is known for children to start their education aged six or seven. Nonetheless in England it is different since they begin Carl Page (1008889) Page 5 BSc (Hons) Sports Science and Coaching SPE001-3 Dissertation at a younger age. According to, Cocozza, (2011) claims the positives of being born in August students have the advantage of being able to leave school, college and university before everyone else as they have not had to be at school for as many months as the older students. Specifically this result means that summer birth students get up to two fewer terms at an educational institution as opposed to their fellow students who were born in the autumn and who started at the educational institution in September. Elsewhere, Paton (2012) has argued that compulsory education ought to be postponed until a child reaches the age of six. He believes there is a current increased importance on the three-Rs; reading, ’riting (writing), and ’rithmetic (arithmetic). As a consequence during the early years of a child who is intelligent this can result in significant long lasting harm. Therefore an alternative option is to have the initial start date delayed by at least twelve months since this will then let infants progress more naturally. As Alger, (2004) reminds us investigators use numerous terms that focus on the same subject when examining the distribution of birth dates. Specifically, this author found that the term ‘Relative Age Effect’ does not appear in some studies since they decide to use other terminologies which mean the same thing. For instance; relative age bias, birth date effects, birth date bias and season-of-birth effects. To determine the influences of the Relative Age Effect Wolstencroft, (2005) compared selections of young performers in teams. This major study concluded a Carl Page (1008889) Page 6 BSc (Hons) Sports Science and Coaching SPE001-3 Dissertation bias towards young performers who are physically mature and consequently are chosen for various sports, e.g. football, rugby and tennis but the opposite applies for gymnastics. It has been recognised that the selection bias can be advantageous to those performers being successful in sport. Other authors (see Simmons and Geoffrey, 2001) point out that this selection bias for age-category in team sports is prevalent due to the importance of winning at any cost. Figure 1 illustrates how ultimately the other young performers get closer to their early developed educational group; this ensures understanding that they were not extra talented when in fact only had matured at a faster rate and are classified as being unexpected “Non-Achievers”. As a result it would seem the requirement of being selected for a sports team is related to the performer’s own birth date. Figure 1. Performance and selection (cf. Hohmann & Carl. 2002, p. 10) In Chun, J. (2007) Identifying Highly Talented Athletes: Conception and Design of an Expert System: Specific to Track and Field. Norderstedt: GRIN Verlag Evans, (2012) draws our attention to the fact that more students are choosing practical courses e.g. food safety and music academic qualification over GCSEs. This decline could be because of the size of the year groups and/or schools Carl Page (1008889) Page 7 BSc (Hons) Sports Science and Coaching SPE001-3 Dissertation increasing the opportunities to take a vocational qualification. This is supported by Groby Community College (2012) which mentions that there is an option for students to gain a vocational qualification such as the BTEC Level 2 First Award in Sport or Dance while studying core Physical Education. Male domination which is the topic for numerous sociological literatures formed the central focus of a study by Laker, (2002) in which the author found there is a gender bias in participation in sport and Physical Education. Plus it has been argued that the educational system is simply part of mixing children into society and equally Physical Education and sport plays a part in this. Hence the equality of opportunity is stated in the National Curriculum, there are recognisable components which are evidently unbalanced. In another major study, the Royal Statistical Society Centre for Statistical Education (2004) found that GCSE Dance is a low chosen subject where it is mainly girl students who choose this subject. On the other hand it was revealed that in years 10-11 there was nearly twice as many boys when compared to girls who decided to study PE and Games as a GCSE. However BBC Learning Parents (2012) uses examples that particular subjects are compulsory at GCSE level whereas others are known as ‘entitlement areas’ when informing parents. Furthermore they recommend it is better for students to study a range of subjects offered for increased career options and choices to study later on in their life. Consequently, it would seem it’s dependent on the school and their provision of subjects by either allowing students to study GCSE’s and/or vocational qualifications. Carl Page (1008889) Page 8 BSc (Hons) Sports Science and Coaching SPE001-3 Dissertation The relationship differences in genders and grades have been widely investigated (Roberts & Fairclough 2012, cited in Burgess, McConnell, Propper & Wilson, (2004). In their piece of research it analysed the gender difference within England and concluded that girls usually do better than boys in educational achievements. Equally recognised by BBC News (2008) announces that while 60.7% of September-born girls and 50.3% of September-born boys achieved five good GCSEs grades A* to C. As opposed to, 55.2% of August-born girls and 44.2% of August-born boys did. Therefore this suggests those students who are the youngest in the year shall be placed behind their older peers even up to the age of 16. Collectively this would suggest more support and encouragement needs to be given at an earlier stage to those students born in the summer months to counter balance the disadvantage of being born later in the year compared to their class peers. Curtis’s comparative study (2009) found that summer-born babies are less expected to obtain the grades at GCSEs and A-levels which consequently hinder them from progressing onto university. A further investigation from Sedghi, (2011) believes specifically those children who were born in the month of August are more likely to underperform in an educational institution when compared to those children who are born in September. A recent study by Shepherd, (2011) publicised shows August babies are less likely to go onto top universities as the study showed they are more likely to study vocational courses. This would imply there is an under-achievement across those students who are born in the summer month of August and influences them succeeding at an educational institution. Carl Page (1008889) Page 9 BSc (Hons) Sports Science and Coaching SPE001-3 Dissertation Although Bell et al. (2009) reported the effects of the birth date effect in assessments of sporting performance. This is continually being questioned by results of public examinations, Physical Education teachers and the development of sporting talent. Furthermore Deming and Dynarski (2008) described the ethical concerns for investigators and methodological issues related to the age-at-test effects on test results being robust and explicit. In particular they found that the cognitive development of infants can produce large variations. Furthermore Morris and Nevill (2006) exposes there is evidence to suggest the Relative Age Effect exists in some sports which significantly sways the opportunities for those wanting to reach the high-level of the sporting pyramid. Collectively this would suggest from the observation that there is an over-representation from being born early in the selection year in both junior and senior elite teams with what might be expected since it is centred on the national birth rates. This view is supported by Nakata and Sakamoto (2012) who points out that only in the female sport of volleyball there was a significant Relative Age Effect. Whilst the effect for males was evidenced in more sports such as baseball, soccer and track and field, hence aiding to the factors of RAEs in sports could change between males and females. Although some investigators reports showed that in women’s elite performers of football produced mixed findings and it has since been revealed there is no significant Relative Age Effect to be found involving youth players. Carl Page (1008889) Page 10 BSc (Hons) Sports Science and Coaching SPE001-3 Dissertation Despite this Chun, (2007) gave evidence for the possible difference involving young performers real age and their biological age. The Matthew Effect as seen in Figure 2 below even occurs whenever class peers compare each other generally being much faster, taller and more muscular. Grade IV player 10 on 1st day of year turning 11 in that year. Jan – April birth e.g. 10 years 11 months at school start. Oct – Dec birth e.g. 10 years 1 month at school start. Up to 12 month difference in maturity. Stronger, faster, improved co-ordination and decision-making ability. At ages younger than 12, ability is a poor guide to talent & capacity. Difference in ability at school level. Higher fall-out rate in first three years – self-removal from talent pool. Selection into squads Better coaching More playing time Better competition & team mates Figure 2. The Matthew Effect. (Adapted from Tucker & Dugas, 2009) As Oakley, (2012 p.1) puts it: Children born immediately after the cut-off point in their specific sport or country are usually bigger and therefore are more likely to be picked in their early years leading to a cumulative advantage. Carl Page (1008889) Page 11 BSc (Hons) Sports Science and Coaching SPE001-3 Dissertation Oakley clearly sees that the children who are born in September will have the advantage over August born children since they will have approximately a whole additional year which allows them to further grow and develop. Specifically, it is intensified with the child’s early stages of puberty, as they are capable of spurting up in one year. Although Simmons, (2001a) establishes the season-of-birth bias is evident when observed within both the educational and sport sectors in England. This is supported by Simmons, (2001b) who reports that there is considerable data on the findings of age-bias in educational year groups showing the season-of-birth bias is not limited to sport but in school education too. Therefore it would seem the advantages of school attainment are presented from the season of birth bias in an educational institution for particularly the older students within each year. Nonetheless the possible explanations as to why this occurs is mentioned by Roberts and Fairclough, (2012) who observed the supporting staff being inexperienced in the Relative Age Effect. Equally Verachtert et al. (2010) suggested that autumn-born students should remain in a teacher’s classroom with the younger students. This is because they possibly will under-rate the stages of development in the younger students. Moreover the difference in gender achievements at GCSE has revealed certain perspectives from students about teachers who perceive they are more easy-going and understanding with girls rather than with students who are boys (Younger and Warrington, 1996). Based on this they then suggest the consequences are significant when involving the interaction of teachers and the Carl Page (1008889) Page 12 BSc (Hons) Sports Science and Coaching SPE001-3 Dissertation students and is dependent on the student’s gender and their birth date period and end-of-year attainment levels in sport and education across all levels. Whilst the reasoning for this is from an investigation which discovered students who are born between the months of June-August are more likely to be identified with behaviour challenges and/or moderate learning difficulties (Roberts & Fairclough 2012, cited in Wilson, (2000). However the phrase “red-shirting” was initially utilised to explain the practice of retaining college athletes out of play while waiting for them to grow bigger and stronger. Other studies show that in sport this has a long-lasting competitive advantage for those athletes (Deming and Dynarski, 2008). Collectively this proposes more investigations are needed to be carried out at all levels of the educational ladder in which teachers/coaches should become experienced in identifying the Relative Age Effect within their group of performers/students. Consequently through directing Physical Education teachers through the Relative Age Effect this will go away as soon as everybody is mature. In addition typically those in youth sport who are named as the least mature ones are the youngest. On the other hand it attributes the older athletes being known as the better ones and more mature (Thomas et al. 2008). As a result the Relative Age Effect (RAE) is used to describe a bias, evident in youth sport and academia. This is where involvement is greater between those born early in the appropriate selection phase and correspondingly lowers between those born late in the selection phase. This would then be expected from the normalised distribution of live births. Carl Page (1008889) Page 13 BSc (Hons) Sports Science and Coaching SPE001-3 Dissertation Although extensive research has been carried out on birth dates, no single study exists which has examined if there is a double relationship between the students’ birth date with the Relative Age Effect in the academic study of sport. The key research question of this study was thus whether or not those students being born on a certain date will indeed influence the decision to study a sports related academic course at an educational institution. Another question is establishing whether there are any other factors such as the effect of a student’s gender, culture, and social class as to why they had selected a specialist sports educational institution too. Methods This study was granted ethical approval in agreement with the guidelines of the Research Ethics Committee of University of Bedfordshire. The participants were given an information sheet for guidance about the study taking place as shown in appendix 1. Plus for the duration of the tests the data was made to follow the Declaration of Helsinki which is a set of ethical principles for the medical community regarding human experimentation. Also this is largely considered to be the foundation document of human research ethics. Likewise the study was processed in accordance with The Nuremberg Code, in paper or electronic form, and must ensure that these are kept confidential and appropriately destroyed or deleted after use. Carl Page (1008889) Page 14 BSc (Hons) Sports Science and Coaching SPE001-3 Dissertation The sample group chosen for this research is comprised of students who study a sports related course from various levels of educational institutions and are split into three categories with both genders. The method of data collection for this involved contacting a range of neighbouring educational institutions that run sport courses this can be seen in appendix 2. The researcher was aware of the need for anonymity for the students and organisation (educational institutions), confidentiality of data, and the need for a professional approach during the investigation to minimise any potential risk to participants Therefore the gatekeepers and the data managers of the educational institutions accessed and securely passed the relevant information about the individuals such as their date of birth, gender and the course title the students are studying. Thus all parties involved were notified that this process was to be kept strictly confidential (subject to legal limitations) and follow the Data Protection Act’s 8 key principles. Hence the data generated by the study will be retained in accordance with the University's policy on Academic Integrity. The data generated in the course of the research is kept securely in paper or electronic form for a period of ten years after the completion of a research project. Furthermore the next phase involved collective organised data collection into statistical software and spreadsheet software. The use of IBM SPSS Statistics 19 (SPSS, Inc., Chicago IL, USA) determined statistical analysis where appropriate. Plus exploring the relationships between variables within this study followed the Inferential Statistical Decision Tree (Corston and Colman 2000) as shown in Carl Page (1008889) Page 15 BSc (Hons) Sports Science and Coaching SPE001-3 Dissertation appendix 3. This involved the tallying of data into frequencies which form a number of variables such as the expected and observed, subsequently either used ChiSquare tests for comparing to theoretical distribution or been tested for association. Plus with the use of spreadsheet software Microsoft Excel 2010 (Office Home and Student 2010 for Windows Vista, Microsoft Corporation, Redmond WA, USA) was used to calculate significant differences within the data collected through a range of formulas, filtering, frequency and pivot tables. The spreadsheet processing computer program allows numerical data to be inputted and displayed in cells of a worksheet. These rows and columns then have hidden formulas which are able to carry out arithmetic on the visible data. Thus altering the contents of a particular cell will result in a program updated result in other specified cells. Nonetheless the controlled variables within this structured independent study of those who are studying a particular sports related course are being kept the same throughout the experiments. Therefore the Independent Variable (IV) is the students being born on a certain date, for instance in January-April, May-August and September-December. In addition the Dependent Variable (DV) is specifically the frequency of students choosing to study sports related courses at an educational institution. The significant difference was set at p ≥ 0.05. The data is presented with a 95% confidence interval. The expected and observed birth months for those studying sports related academic course at an educational institution was examined using Carl Page (1008889) Page 16 BSc (Hons) Sports Science and Coaching SPE001-3 Dissertation Chi-Square tests. The test worked by observing comparisons of frequencies in addition to the frequencies that would be expected if the statistical independence and the null hypothesis of no association were true. Moreover the researcher was capable of calculating the likely frequency for each cell in the contingency table/crosstabulation through presuming each of the variables was independent. The first group started in September and finished in December, the second was from January-April and the last was from May-August. Following similar investigations from Nakata & Sakamoto (2012) the Chi-Squared tests were appropriate to the birth dates in line with the four quarters which assist measuring the statistical significance of deviations for the expected number of births in all the quarters. This is supported by Easton & Mc Coll (2012) who specifies that to determine whether there is any relationships between the data sample involved comparing two attributes with the process of Chi-Squared Test of Association. The formulae and functions which are arithmetic operations +, -, ^, * and % to be used in the spreadsheet. VLookup; searches for a value in the first column of a table and returns a value in the same row from another column in the table array. CountIf; it counts the number of cells within a range that meet the given criteria. Minimum; this will be used to calculate the lowest recorded amount. Maximum; this was employed to calculate the largest amount number. Average; this will be used to calculate the average of a group of numbers by adding each member of the group and dividing the total by the number of members. Total, the sum of several amounts added or considered together. Range, is the highest Carl Page (1008889) Page 17 BSc (Hons) Sports Science and Coaching SPE001-3 Dissertation minus the lowest value. Interquartile Range is a measure of the spread of a group of values equal to the difference between the upper limit for the lower quarter and the lower limit for the upper quarter. While Excel Frequency Tables are applied to work out the ratio of that number to the total results obtained. Furthermore the Pivot Table report automatically extracted and summarised the data. This consequently allowed for reported analysis of the data to make comparisons of trends. Equally with the Pivot Chart report when this was simply carried out to discover any relationships or patterns within the data set. Therefore in comparing the Pivot Table report and Pivot Chart report this allowed the researcher to compare any significant information in the study. The Pivot Table report is used since it is an interactive method to swiftly sum up large quantities of information in a very user-friendly manner. Likewise when altering the rows to columns or columns to rows of the data will allow the researcher to concentrate on the information that they want or need. Additionally by means of filtering, categorisation, alignment and conditional format tools to the cells this allows for specific pieces of information to be presented. Consequently the spreadsheet Pivot Table showed how many students are at a particular level of studying a sports related course at an educational institution. Plus the researcher can easily indicate which month the student’s birth dates are the most common out of the data sets. Additionally it is shown there to be poor relationship between the observed and expected frequencies. Plus rejected the null hypothesis of independence/no association occurs during the Chi-Squared Test of Association is too big of a value Carl Page (1008889) Page 18 BSc (Hons) Sports Science and Coaching SPE001-3 Dissertation for the test statistic (Easton & Mc Coll, 2012). Auto filtering; this is used so that it displays only a part of a list the researcher requires. As by providing the specific criteria in the spreadsheet then Excel will display only the data that match the criteria. Filtering is especially useful when having a large amount of data and the need to work with only a small part of the data in the list. Microsoft includes safety features to help protect the documents from numerous possible unsafe actions, for instance current versions of the spreadsheet software include security measures intended to maintain the computer safety. Therefore password protected spreadsheet offers safety measure points and macro virus avoidance. These are the essential safeguards accessible in Excel. This stops unauthorised staff and other individuals being able to access the researcher’s data. However it is through electronic communication the data becomes legalised, yet the researcher will be accountable for the security of the data. Also identified were sufficient protection actions for each stage of information being used like password protection or encryption of the document. Therefore with password protection the researcher’s Excel worksheets prevented others from tampering with the data. The easiest methods are to password protect the entire sheet or word document. Also the encryption document increased the security since through restricted permissions being only granted people could access data while restricting their ability to edit, copy and print the data. Carl Page (1008889) Page 19 BSc (Hons) Sports Science and Coaching SPE001-3 Dissertation In addition the Excel Advanced Filter was applied to take out a record of distinctive items in the database. For instance, the document files of students from the specific spreadsheet and those from the same birth date range. Furthermore utilising the AutoFilter feature to filter data; this is a quick and easy way to find and work with a subset of data in a range of cells or table. To filter data in a range of cells or table, you can either reapply a filter to get up-to-date results, or clear a filter to redisplay all of the data. Plus the search technique was applied for displaying individual records which was dependent on the criteria being entered. Along with it presents the matched criteria of students across the entire spreadsheet for analysing particular results. Results Chi-Square tests were used to analyse the relationship between the observed and expected frequencies of students birth months studying a sport related academic course at an educational institution. Data was collected from a range of educational institutions with a total of nine thousand three hundred and twenty students from sport related academic courses (N = 9320). Also used a significance level of p = 0.05 level for all statistical tests. The breakdown of those students decision to study a sports related course at GCSE BTEC Level 1 and 2 (N = 123), A-Level courses includes BTEC’s at Level 3 (N = 344) and Undergraduate courses such as Foundation Degrees, Bachelor of Arts with Honours and Bachelor of Science Honours (N = 8533). Carl Page (1008889) Page 20 BSc (Hons) Sports Science and Coaching SPE001-3 Dissertation The total sample group distribution of males (N = 6522) and females (N = 2798). This can be seen in Figure 3 below and compares the experimental data on genders studying a sport related academic course at an educational institution with an over populace representation of male students compared to females. Male Female 30% 70% Figure 3. The total distribution of genders studying a sport related academic course at an educational institution. Also, Chi-Square tests revealed in the crosstabulation for analyses the whole sample frequencies of all students’ birth months in each third period based on the assumption of an unequal distribution across the trifold. As in Table 3 this can be seen in appendix 4 and shows there is a significant difference, X2 (3, N = 9320) = 17185.29, p < 0.05 indicated between the three groups. The relationship between these variables was significant so agrees with the hypothesis as it occurs with the distribution of births across all levels of education is not equally distributed throughout the year. The results obtained from the preliminary analysis of the whole samples of the observed frequencies it would appear that the birth date is highest for the months of Carl Page (1008889) Page 21 BSc (Hons) Sports Science and Coaching SPE001-3 Dissertation September-December and lowest for the spring and summer months as shown in Figure 4. Frequency of students Expected 3300 3250 3200 3150 3100 3050 3000 2950 2900 2850 Observed Linear (Expected ) 3269 3044 3107 September-December 3107 3007 3107 January-April May-August Birth Date Month Groups Figure 4. The total distribution of student’s birth dates studying a sport related academic course at educational institutions. Further Chi-Square tests revealed in appendix 5 for the frequencies of undergraduate students’ birth months in each third period based on the assumption of an unequal distribution across the trifold. The statistical results, X2 (3, N = 8853) = 16402.47, p < 0.05, is significant with the participation of students on undergraduate courses and the distribution of their birth dates are not being distributed as expected throughout the year. Figure 5 presents the intercorrelations among the observed frequency is higher amongst those born early in September and is also the starting date for the educational institution and correspondingly in comparison lower between those students who were born later in the year. The pie chart in Figure 6 shows the breakdown of undergraduates, females (N = 2714) in contrast to a higher percentage of male undergraduate students (N = 6139). Carl Page (1008889) Page 22 BSc (Hons) Sports Science and Coaching SPE001-3 Dissertation Frequency of students Expected 3150 3100 3050 3000 2950 2900 2850 2800 2750 2700 Observed Linear (Expected ) 3110 2951 2951 September-December 2951 2860 2883 January-April May-August Birth Date Month Groups Figure 5. The distribution of student’s birth dates who are studying a sport related academic course at undergraduate level. Male Female 31% 69% Figure 6. A higher percentage of undergraduate’s who are male compared to female students in the academic study of sport. There was a similarity of results when using Chi-Square tests. This was used in examining the A-Level courses which include BTEC’s at Level 3 expected and observed frequencies being significant in appendix 6. The statistical results, X2 (3, N = 344) = 620.92, p < 0.05, specifies data from observed frequencies of A-level students in Figure 7 can be compared with the data in undergraduate students Figure 5 which is consistent with the hypothesis that the September-December Carl Page (1008889) Page 23 BSc (Hons) Sports Science and Coaching SPE001-3 Dissertation group reported significantly more students than the other two birth date month groups. Expected Observed Linear (Expected ) Frequency of students 130 125 120 115 110 105 125 115 115 115 113 106 100 95 September-December January-April May-August Birth Date Month Groups Figure 7. The distribution of student’s live births who are studying an A-level course. From the graph below in Figure 8 we can see that the breakdown of genders there is a higher distribution of males (N = 276) when compared to females (N = 68). Male Female 20% 80% Figure 8. The distribution of more male students studying an A-level sports related course when compared to female students. The single most striking observation to emerge from the data comparison was that the observed frequencies is highest for the months of May-August and lower for the educational institutions start date and in the winter months from students studying a GCSE at BTEC Level 1 and 2 at an educational institution (Figure 9). Carl Page (1008889) Page 24 BSc (Hons) Sports Science and Coaching SPE001-3 Dissertation Expected Observed Linear (Expected ) Frequency of students 60 50 40 30 20 41 41 34 41 41 48 10 0 September-December January-April May-August Birth Date Month Groups Figure 9. Observed and Expected frequencies in September-December, JanuaryApril and May-August groups at GCSE BTEC Level 1 and 2 courses. This is inconsistent with the hypothesis as presented in the contingency table of appendix 7. The statistical results, X2 (3, N = 123) = 175.29, p > 0.05, revealed to accept the null hypothesis since there is significant difference between the distribution of births not being equally distributed throughout the year. It is apparent from the Figure 10 that very few females study a sports related academic course even at GCSE level, males (N = 107) and females (N = 16). Male Female 13% 87% Figure 10. Higher male distribution of students studying a sports related course at BTEC Level 1 and 2 (GCSE). Carl Page (1008889) Page 25 BSc (Hons) Sports Science and Coaching SPE001-3 Dissertation Discussion The present study was designed to determine the effect of those students being born on a certain date will indeed influence the decision to study a sports related course at an educational institution. As in reviewing the literature, no data was found on the association between the Relative Age Effect (RAE) in the academic study of sport. The main findings show there to be significant results in the birth dates of an individual and studying a sports academic course as with the distribution of births across all levels of education were not equally distributed throughout the year. The results of this study did show that higher percentages of students were born in the months of September-December and lower percentages in the spring and summer months which it is consistent with the set hypothesis. The results of this study show/indicate that an over populace representation of male students compared to females who are studying a sport related academic course at an educational institution. Contrary to expectations, this study did not find a significant difference between the observed frequencies and expected frequencies from GCSE BTEC Level 1 and 2. The crosstabulation is identified as a helpful tool in assessing the statistical significance in the relationship involving the categories of two or more variables. Hence Virginia Polytechnic Institute and State University (1999) informs that if there is a large quantity of statistical instances, the Chi-Square returned a value which is of great importance even when there is not that much of a correlation. Consequently they were able to effectively calculate through the Chi-Square the observed and expected frequencies for each birth date month group. Carl Page (1008889) Page 26 BSc (Hons) Sports Science and Coaching SPE001-3 Dissertation Whilst Northern Illinois University Department of Biological Sciences (2004) test results will match the expectations more closely. Although even when the researcher carries out statistical analysis properly which is based on the suitable hypothesis the distribution of data can become very one-sided. As a result there are two ways in which the researcher is able to obtain a large high Chi-Square value or an unfamiliar result from the right theory or secondly it may be a consequence of using the wrong theory. Hence both are interchangeable since the data is always able to be separated between being the truth and false with a 100% confidence. This study confirms that birth dates in the earlier months is associated with a biased selection (Wilson, 1998). As a result of the Chi-Square tests representing the observed distribution of birth dates, by month is contrasted considerably from the expected frequencies. In the same way Jiménez and Pain (2008) highlighted specifically in Spain, even though their selection period for education usually starts in January the Relative Age Effect exists since this then influences the development amongst the students of the oldest and the youngest in a group being different physically, emotionally and academically. However there are discrepancies between the data sets of students studying sport related academic courses at educational institutions. This is because there is a much larger sample size of students from undergraduate courses. Consequently Radford University (2002) show larger differences occur between the expected and actual data which generate an increased Chi-Square value. Along with the increased Chi- Carl Page (1008889) Page 27 BSc (Hons) Sports Science and Coaching SPE001-3 Dissertation Square value there is a greater likelihood of there really being a significant difference. Specifically, with the smaller sample size for those students studying GCSE’s which can be either at BTEC Level 1 or Level 2 courses; caution must be applied, as the findings might not be transferable to the Relative Age Effect. The reason for this is not clear but Berk and Carey (2010) discussed the validity of the Chi-Square test with small frequencies. Specifically the authors found that researchers could face problems when applying the Pearson Chi-Square test on a table which has a large amount of empty cells and it might not be valid to do so. Cells with few inputted amounts can be problematic as this means a researcher is required to have a bigger sample size for the Pearson Chi-Square test to function properly. One of the issues that emerge from these findings is that various conditions for the application of the Chi-Square test need to be carried out before it can be fully functional (Kothari, 2004). For instance the input of observed frequencies should be generated from a random basis. Hence most statisticians believe the group of items must contain no less than 10 items as some regard this to be better than 5. Whilst it is recognised that a typical sample size study should be at least 50, since this total quantity of items is needed for increasing the size of analysis into the effects. In contrast Howell, (2010) reports that in numerous previous investigations there appears to be no issues around the definition of large being known as "at least 5". Following the analysis of contingency tables, his report found that a researcher could make use of the normal Pearson Chi-Square test even when the expected cell Carl Page (1008889) Page 28 BSc (Hons) Sports Science and Coaching SPE001-3 Dissertation frequencies are moderate. Consequently the constraints have to be linear as each of the items within the sample is independent. Furthermore a smaller sample size was generated of students from educational institutions who study a sport related academic course at A-Level and includes BTEC’s at Level 3. Ford and Williams (2011) investigation had a low sample size when contrasted against the previous literature into the Relative Age Effect. This is supported by Baker et al. (2009) whose study encountered sampling issues when evaluating the effects of other linear studies. Therefore it would seem that sample size is connected to the analyses of how much of an influence can be discovered from analysing an individual’s date of birth. Additionally it is shown there to be a poor relationship between the observed and expected frequencies of GCSE BTEC Level 1 and 2 sports related academic courses. Therefore with the observed frequencies in the birth date month groups they did not match the expected frequencies; whereby adapting Sharp, (2004) suggests this could be due to the influences of the sample size being too small or the incorrect birth date was received from the contacted educational institutions. There are, however, other possible explanations specifically Easton & Mc Coll, (2012) indicates this occurs when the researcher rejects the null hypothesis of independence / no association. This is because the Chi-Squared Test of Association is too big of a value for the test statistic. Similarly Glynn, (2000) testifies the ChiSquare test will become unreliable once the researcher’s table includes cells with the expected frequencies of below 5. Therefore different statistical procedures may be Carl Page (1008889) Page 29 BSc (Hons) Sports Science and Coaching SPE001-3 Dissertation used to better determine if statistical significance occurs from deviations for the expected frequency number of births within the particular sample size groups. This inconsistency/discrepancy may be due to the fact that the researcher is only able to make the interpretation of the Chi-Square test as it does not identify the relationship within the data (Heavey, 2011). Equally DiMaria, (2007) warns that the Chi-Square statistic will not present clear results so the researchers are required to consider if a relationship exists. As a consequence Franke et al. (2012) recognised researchers will be more likely to either wrongly read or over interpret the results of Chi-Square tests. This practice influences their reports which could include inadequate or no backing from the statistical analyses which has been carried out as part of the research. Verachtert et al. (2011) addressed the issue of limited longitudinal investigations on the continuation of the season of birth effect over time. They mainly used crosssectional data instead from various cohorts. Specifically their study was able to signify the difference amongst children who are born in the first and the fourth quarter lessened significantly. On the other hand Baker et al. (2009) discovered the role of date of birth can either promote or limit an individual’s prospects for improved achievement and developing skills. Consequently with the current investigations season of birth and school success in the early years of primary education in which other factors such as using the growth curve modelling to analyses the longitudinal data into the Relative Age Effect. Carl Page (1008889) Page 30 BSc (Hons) Sports Science and Coaching SPE001-3 Dissertation Edgar and O’Donoghue (2005) identified limitations to the study which needed to take into account that the researchers must be familiar with age subgroups, gender, area and gender for homogeneity to larger groups of people. Hence this distribution of larger groups of people will help overcome problems of alterations in the population season of birth distributions concerning the different calendar years the students were born in. Likewise the researcher needs to take into consideration the different amount of days there are in every month of the year. Sykes et al. (2009) expresses concern that the Relative Age Effect lowers through time but continues to be significant at GCSE, A-level and into university. Rosenbaum (2013) discovered the likelihood of becoming a university student for either Oxford or Cambridge is clearly affected by date of birth. Collectively this suggests the Relative Age Effect is already present for students who are academically strong and are currently applying to Oxbridge. The combination of findings provides some support for the conceptual evidence that the Relative Age Effect is present in sports academia. Consequently in future investigations it might be possible to have a different start date in an educational institution and whether universities should begin to consider offering applicants places dependent on their dates of birth. Additionally Crawford, et al. (2007) evidenced recently qualified teachers are inexperienced in the impact relative age has on test results. Collectively this suggests the issue has to be more recognised so that with students of different ages the lessons can be adapted to suit their needs. Therefore the results mean that teachers could be mislabelling the students born in the summer months as having special education needs. This may just be that the older class peers are basically Carl Page (1008889) Page 31 BSc (Hons) Sports Science and Coaching SPE001-3 Dissertation further developed emotionally and cognitively to those students born later in the year (Sykes et al. 2009). These results are consistent with those of other studies and suggest that the Relative Age Effect is advantageous for the students born during the beginning of the academic year when matched with the other students who are born in the later months (Cobley et al. 2008). Furthermore Georgakis et al. (2011) learnt the Relative Age Effect influences a student’s physical education accomplishments as well as their representation in school sport competitions. The data must be interpreted with caution because the researcher is unable to identify from the obtained results which students have possibly either skipped or been held back a year. Subsequently this creates issues to the observed age and the expected age of starting at an educational institution to study a sports related course (Crawford, et al. 2007). Some of the issues emerging from the findings relate specifically to students who are the youngest within their year group at an educational institution and will be more likely on average to do considerably poorer in terms of educational achievement. Deaner et al. (2013) revealed the negative impact the Relative Age Effect has on relatively younger individuals which is evidenced in various educational and sporting backgrounds. Smith, (2007) discovers through the National Curriculum Physical Education (NCPE) in years 10 and 11 for 15—16 year olds the involvement in diverse sports and physical activities changed significantly and differently according to the gender, the school, specialist Sports College and if the student was studying Carl Page (1008889) Page 32 BSc (Hons) Sports Science and Coaching SPE001-3 Dissertation GCSE PE. Sykes and colleagues in 2009 believe when trying to solve the issue of the birth date effect this will not happen by using a common start date for an educational institution. Nonetheless Crawford, et al. (2007) proposed the starting age at an educational institution needs to be studied and be flexible. Consequently nurseries would be available as a substitute option to full-time education. On the other hand Bono and Galindo-Rueda (2004) presents Local Education Authorities are responsible for the implementation of the start dates for compulsory primary educational institutions. Furthermore Local Education Authorities would also be responsible if they decided to defer the entry date. This would be more of an exception than a possibility. Cobley, et al. (2008) encountered multiple circumstances of the Relative Age Effect in school Physical Education and sport environments with the present selection, assessment and age-grouping approaches. Similarly trying to compare the evidence of Relative Age Effect in other educational institutions from around the world can be difficult. For instance variables like the differences in start date of the school year, legalised compulsory education and whether there is ability grouping in early years (Sykes et al. 2009). For instance Laker, (2002) noticed that there is a gender bias in America; therefore a law was made in 1972 to allow equal opportunities for women in sport. Plus this effected women’s sport in education establishments trying to reflect the male varsity sports arrangement. However in some social circles it is considered inappropriate for women to participate in sport, for instance it is believed a woman’s role was to look Carl Page (1008889) Page 33 BSc (Hons) Sports Science and Coaching SPE001-3 Dissertation after the children and were physiologically not suited to sport performance and physical activity because of the perceptual differences in abilities. Grenet, (2010) exposes a number of problems which exist in institutional education systems which possibly can be responsible for the birth effects carrying on into adulthood through influential differentiated educational trajectories. Specifically they found men have a lower probability of possessing an academic A-level or above if born late in the year. However Sykes et al. (2009) believed it is very important to recognise that only a number of summer-born students really get to the highest level of education. This effect has been insufficiently investigated within all levels of education. Therefore researchers would have to examine if this is one of the reasons why the summer birth students are currently not continuing with education especially right up to university level. Bono and Galindo-Rueda (2004) reveals the present qualification system in England challenges students with the key intermediate level assessments which normally are taken at the end of the summer educational term. However the differences in school leaving dates from birth date of students in the same classroom this generates a significant incoherence in the educational achievement. This is because it indicates a minor variance of two to three months of education. Although it is interesting to note that those students who attended a specialist school it was often found to their grades increased at GCSE level (Levačić and Jenkins, 2006). Whilst Crawford, et al. (2007) suggested former investigations possibly limited the importance of their findings which contained small sample sizes. Also there needs to Carl Page (1008889) Page 34 BSc (Hons) Sports Science and Coaching SPE001-3 Dissertation be further investigations into the expected accomplishments of August born students when contrasted against the cohort. This is because a student may just necessarily be developing at a slower rate when compared against fellow students. Therefore it assures parents that their child is not special needs. However Cobley (2009) exposes more students from the later birth months of January to August were recognised as having special educational needs from the referrals for learning support. It is encouraging to compare this with that found by Zubero et al. (2008) who found that there is a relationship between the birth date and entering the university. The study examined the effect is possibly from the difference of maturity between the teenage students who were born in the months of January and December. Besides, when at being at a mature student and it is possible to achieve better grades. Since this difference has not been found elsewhere it is probably not due to the socialisation influences but differences of being through the multifaceted relations involving the individual’s biological and maturational existing between both genders (Vincent and Glamser, 2006). For that reason there are possible shortcomings related to being born later in the year and should be of particular focus. The results may be explained by the fact that evidenced from Bell and Daniels (1990) birth date effect exists in the performance even for students aged 11, 13 and 15. Whereby it is seen less so in the older age when compared to the younger age group. This also accords with Zubero et al. (2008) observations, which showed that students who are roughly older by a single year are more skilled at playing sports. Carl Page (1008889) Page 35 BSc (Hons) Sports Science and Coaching SPE001-3 Dissertation Subsequently this may possibly increase inspiration to take an interest in sport along with developing self-esteem. Van Wersch et al. (1992) identified at the age of 14 a girls' interested in Physical Education was significantly lower than that of boys but was found to be the opposite in the younger age groups. This finding corroborates the ideas of Evans et al. (1997), who suggested that more needs to be done to aid promotion of getting female students attracted into Physical Education and sport. This applies equally to primary and secondary educational institutions with reference to the National Curriculum PE (NCPE) which will prepare them for their future careers in leisure and/or paid employment. The possible difference of gender cannot be ruled out since Dexter (1999) evidenced the effect of gender varied across schools. Yet also found there to be stability across schools of students’ educational ability on sports knowledge as well as their sport performance. Additionally Simmons, (2001a) found a significant contribution of those born September-December lead to a higher percentage of being chosen for selection against those born between the months of May and August. It may be that these students benefitted from being older and being recognised as “talented” this is because of their physiological/psychological advantages which the students have over their “younger” cohort (Helsen et al. 2005). Likewise Simmons, (2001b) reasoned that it is mainly from the September-December born individuals enjoying dominance in the earlier years amongst their cohort. Carl Page (1008889) Page 36 BSc (Hons) Sports Science and Coaching SPE001-3 Dissertation Conclusion This dissertation has investigated the double relationship between the students’ birth dates with the Relative Age Effect in the academic study of sport. Therefore returning to the hypothesis/question posed at the beginning of this study, it is now possible to state that birth date has a large influence on the decision to study a sports related course at an educational institution. The results of this study also indicate that elements of Relative Age Effect (RAE) in the academic study of sport may vary amongst male and female students. These findings suggest that in general the birth dates of an individual and studying sport academic course at all levels of education were not equally distributed. One of the more significant findings to emerge from this study is that the observed frequencies show the birth date is highest for the months of September-December and lowest for January-April and May-August months from all data sets apart from those at GCSE BTEC Level 1 and 2. The study has gone some way towards enhancing our understanding of the Relative Age Effect (RAE) in the academic study of sport. In general, therefore, it seems that it confirms previous findings of the birth date effect and contributes additional evidence that suggests there is an over populace representation of male students compared to females who are studying a sport related academic course at an educational institution. However the study was limited in several ways. First, the dissertation used a convenience sample that grouped subjects together from the same educational level to increase the data size. Carl Page (1008889) Page 37 BSc (Hons) Sports Science and Coaching SPE001-3 Dissertation Although the reader should bear in mind that the study was based on a small sample for GCSE students at BTEC Level 1 and 2 due to data protection and would be deemed unethical practice in terms of students giving consent for use of data. Secondly the researcher was unable to establish whether there are any other factors such as the effect of whether practical vs. theory examinations took place to gain entry, cultural background and social economic class as to why they had selected a specialist sports educational institution. It is suggested that the association of these factors is investigated in future studies. Consequently the implication of these findings is that both birth date and gender are taken into account when deciding to study a sports related course at an educational institution. Therefore future investigations need to include a focus group which allows for an indepth analysis with a small group of cross representative people who are questioned about their opinions as part of the research. The focus group meetings will be recorded with a Dictaphone; this is so that it can be transcribed for the researcher. Furthermore this allows for new insights to be discovered as to whether the students realised that this is happening through their educational life and give examples of how it has affected them positively and/or negatively. Further research in this field regarding the role of birth date would be of great help to those studying or teaching in an educational institution. Carl Page (1008889) Page 38 BSc (Hons) Sports Science and Coaching SPE001-3 Dissertation Finally unless the government adopt strategies on the Relative Age Effect (RAE) and gender bias of those studying sports related courses at educational institution, summer born students will not have good career prospects. This information can then be used worldwide to develop targeted interventions aimed at supporting those born later in the year and stop discrimination to allow for equal opportunities to study sports academia. References BBC Learning Parents (2012) Choosing subjects for GCSE. Available at: http://www.bbc.co.uk/schools/parents/gcse_choosing/ (Accessed on: 26/10/2012). BBC News (2008) Summer-born to start school later. Available at: http://news.bbc.co.uk/1/hi/education/7178969.stm (Accessed on: 15/01/2013). Bedford Borough Council (2013) School Admissions. Available at: http://www.bedford.gov.uk/education_and_learning/schools_and_colleges/school_ad missions.aspx (Accessed on: 15/01/2013). Bell, J., Massey, A. & Dexter, T. (2009) ‘Birthdate and Ratings of Sporting Achievement: Analysis of Physical Education GCSE Results’ European Journal of Physical Education, 2(2), pp.1-8. Bell, J.F. and Daniels, S. (1990) ‘Are Summer‐born Children Disadvantaged? The Birthdate Effect in Education’ Oxford Review of Education, 16(1), pp.67-80 Taylor & Francis Online [Online]. Available at: http://www.tandfonline.com/doi/abs/10.1080/0305498900160106 (Accessed on: 5/03/2013). Carl Page (1008889) Page 39 BSc (Hons) Sports Science and Coaching SPE001-3 Dissertation Berk, K.N. and Carey, P. (2010) Data Analysis With Microsoft Excel: Updated for Office 2007. Google Books [Online]. Available at: http://books.google.co.uk/books?id=TUpDeKGyN5MC&pg=PA299&dq=Pearson's+C hiSquare+Test+issues&hl=en&sa=X&ei=Ua5yUfaRGeGc0QWeioD4DQ&ved=0CFQQ 6AEwBg#v=onepage&q=Pearson's%20Chi-Square%20Test%20issues&f=false (Accessed on: 4/02/2013) Bono, E.D. and Galindo-Rueda, F. (2004) Do a Few Months of Compulsory Schooling Matter? The Education and Labour Market Impact of School Leaving Rules. Germany: The Institute for the Study of Labor (IZA) [Online]. Available at: http://papers.ssrn.com/sol3/papers.cfm?abstract_id=574065 (Accessed on: 5/03/2013). Burgess, S., McConnell, B., Propper, C., & Wilson, D. (2004) ‘Girls rock, boys roll: An analysis of the age 14-16 gender gap in English schools’ Scottish Journal of Political Economy, 51(2), pp.209–229. Central Bedfordshire Council (2012) Your child’s admission for September 2013. Schools and academies in Central Bedfordshire. Bedfordshire: Central Bedfordshire Council [Online]. Available at: http://www.centralbedfordshire.gov.uk/Images/Booklet%202013%20Proper_tcm634345.pdf (Accessed on: 15/01/2013). Chun, J. (2007) Identifying Highly Talented Athletes: Conception and Design of an Expert System: Specific to Track and Field. Google Books [Online]. Available at: http://books.google.co.uk/books?id=qHcHdCiekuwC&pg=PA58&lpg=PA58&dq=pelto la+talent+identification&source=bl&ots=9Zqb3CZkYj&sig=lTUfQxZI_rNTRDheI_TeH Carl Page (1008889) Page 40 BSc (Hons) Sports Science and Coaching SPE001-3 Dissertation Dn7WZg&hl=en&sa=X&ei=2ozdUKmJE4Kd0QWbtoHIBw&ved=0CDQQ6AEwAA#v= onepage&q=peltola%20talent%20identification&f=false (Accessed on: 28/12/2012) Cobley, S., Abraham, C. and Baker, J. (2008) ‘Relative age effects on physical education attainment and school sport representation’ Physical Education and Sport Pedagogy, 13(3) pp.267-276 Taylor & Francis Online [Online]. Available at: http://www.tandfonline.com/doi/abs/10.1080/17408980701711983 (Accessed on: 5/03/2013). Cobley, S., McKenna, J., Baker, J., Wattie, N. (2009) ‘How pervasive are relative age effects in secondary school education?’ Journal of Educational Psychology, 101(2), pp.520-528 American Psychological Association [Online]. Available at: http://psycnet.apa.org/journals/edu/101/2/520/ (Accessed on: 5/03/2013). Crawford, C., Dearden, L. and Meghir, C. (2007) When You Are Born Matters: The impact of Date of birth on child cognitive outcomes in England. London: The Centre for the Economics of Education [Online]. Available at: http://cee.lse.ac.uk/ceedps//ceedp93.pdf (Accessed on: 13/04/2013) Curtis, P. (2009) ‘School starting age moved to help summer-born children’, The Guardian, 30 April. [Online]. Available at: http://www.guardian.co.uk/education/2009/apr/30/school-starting-age-primary-review (Accessed on: 15/01/2013). Deaner R.O., Lowen A, Cobley, S. (2013) ‘Born at the Wrong Time: Selection Bias in the NHL Draft’ PLOS ONE, 8(2), pp.1-7 PLOS ONE [Online]. Available at: http://www.plosone.org/article/info%3Adoi%2F10.1371%2Fjournal.pone.0057753. (Accessed on: 28/01/2013). Carl Page (1008889) Page 41 BSc (Hons) Sports Science and Coaching SPE001-3 Dissertation Deming, D. & Dynarski, S. (2008) ‘The Lengthening of Childhood’ Journal of Economic Perspectives, 22(3), pp.71–92. Dexter, T. (1999) ‘Relationships between sport knowledge, sport performance and academic ability: Empirical evidence from GCSE Physical Education’ Journal of Sports Sciences, 17(4), pp. 283-295 Taylor & Francis Online [Online]. Available at: http://www.tandfonline.com/doi/abs/10.1080/026404199366000 (Accessed on: 5/03/2013). DiMaria, R.A. (2007) Understanding and Interpreting the Chi-square Statistic (X2). Available at: http://www.hsc.wvu.edu/Charleston/son/StudentResources/PDF/Class%202%20chisquare%20DiMaria.pdf (Accessed on: 29/03/2013). Easton, VJ. & Mc Coll, JH. (2012)Statistics Glossary. Available at: http://www.stats.gla.ac.uk/steps/glossary/categorical_data.html#chigof (Accessed on: 28/11/2012). Evans, G. (2012) ‘More pupils choosing practical courses over GCSEs’, Wales Online, 10 May [Online]. Available at: http://www.walesonline.co.uk/news/localnews/more-pupils-choosing-practical-courses-2030523 (Accessed on: 26/10/2012). Evans, J., Davies B. and Penney, D. (1997) ‘Making Progress? Sport Policy, Women and Innovation in Physical Education’ European Journal of Physical Education, 2(1), pp. 39-50 Taylor & Francis Online [Online]. Available at: http://www.tandfonline.com/doi/abs/10.1080/1740898970020104 (Accessed on: 5/03/2013). Carl Page (1008889) Page 42 BSc (Hons) Sports Science and Coaching SPE001-3 Dissertation Ford, PR., & Williams, AM. (2011) ‘No Relative Age Effect in the Birth Dates of Award-Winning Athletes in Male Professional Team Sports’ Research Quarterly for Exercise and Sport, 82(3), pp. 570–573 Franke, T.M., Ho, T. and Christie, C.A. (2012) ‘The Chi-Square Test: Often Used and More Often Misinterpreted’ American Journal of Evaluation, 33(3), pp.448-458 SAGE Publications [Online]. Available at: http://aje.sagepub.com/content/33/3/448.full.pdf. (Accessed on: 4/02/2013). Georgakis, S., Russell, K. and Russell, K.M. (2011) Youth Sport in Australia Glynn, P. (2000) SPSS PC Version 10: Crosstabs with Chi-Square Test1. Seattle: University of Washington [Online]. Available at: http://staff.washington.edu/glynn/chisspss.pdf (Accessed on: 04/01/2013). Google Books [Online]. Available at: http://books.google.co.uk/books?id=g5L_upSbd3AC&printsec=frontcover&dq=isbn:1 920899642&hl=en&sa=X&ei=66V3Ua6wI6SS0QXP74DoCw&ved=0CDYQ6AEwAA# v=onepage&q=Relative%20Age%20Effect&f=false (Accessed on: 23/03/2013) Great Britain. Education Act: Compulsory school age. Chapter 56. (1996) London: The Stationery Office. Grenet, J. (2010) Academic performance, Educational Trajectories and the Persistence of Date of Birth Effects. Evidence from France. London: Centre for Economic Performance [Online]. Available at: http://www.parisschoolofeconomics.com/grenet-julien/Articles/Grenet2010a.pdf (Accessed on: 5/03/2013) Carl Page (1008889) Page 43 BSc (Hons) Sports Science and Coaching SPE001-3 Dissertation Groby Community College (2012) PE Core & GCSE. Available at: http://www.grobycoll.leics.sch.uk/index.php/faculties/pa/pe-gcse (Accessed on: 26/10/2012). Heavey, E. (2011) Statistics for Nursing: A Practical Approach. Google Books [Online]. Available at: http://books.google.co.uk/books?id=SsTjh3Pdqm0C&pg=PA108&dq=Pearson's+ChiSquare+Test+problems&hl=en&sa=X&ei=9axyUZLeJOSW0QXrhYHoAQ&ved=0CD gQ6AEwAQ#v=onepage&q=Pearson's%20ChiSquare%20Test%20problems&f=false (Accessed on: 4/02/2013) Helsen, W.F., Winckel, .JV. and Williams, A.M. (2005) ‘The relative age effect in youth soccer across Europe’ Journal of Sports Sciences, 23(6), pp. 629-636 Taylor & Francis Online [Online]. Available at: http://www.tandfonline.com/doi/abs/10.1080/02640410400021310 (Accessed on: 5/03/2013). Howell, D.C. (2010) Chi-Square Test - Analysis of Contingency. Burlington: University of Vermont [Online]. Available at: http://www.uvm.edu/~dhowell/methods7/Supplements/ChiSquareTests.pdf (Accessed on: 4/02/2013). Jiménez, I.P and Pain M.T.G (2008) ‘Relative age effect in Spanish association football: Its extent and implications for wasted potential’ Journal Of Sports Sciences, 26(10), pp. 995-1003 Taylor & Francis Online [Online]. Available at: http://www.tandfonline.com/doi/abs/10.1080/02640410801910285 (Accessed on: 5/03/2013). Kothari, C. R. (2004) Research Methodology: Methods and Techniques. Google Books [Online]. Available at: http://books.google.co.uk/books?id=8c6gkbKiCarl Page (1008889) Page 44 BSc (Hons) Sports Science and Coaching SPE001-3 Dissertation F4C&pg=PA233&dq=ChiSquare+Test+problems&hl=en&sa=X&ei=d6tyUaCANeeG0AWP6ICAAQ&ved=0CD kQ6AEwAA#v=onepage&q=Chi-Square%20Test%20problems&f=false (Accessed on: 4/02/2013) Laker, A. (2002) Beyond the Boundaries of Physical Education: Educating Young People for Citizenship and Social Responsibility. Google Books [Online]. Available at: http://books.google.co.uk/books?id=nFt1AgduGSEC&pg=PA35&dq=Month+of+birth +bias+education+and+sport&hl=en&sa=X&ei=Jnk4UceoIcjUPKzqgOgC&ved=0CDo Q6AEwAg#v=onepage&q=Month%20of%20birth%20bias%20education%20and%20 sport&f=false (Accessed on: 23/03/2013) Larouch, R., Laurencelle, L., Grondin, S., & Trudeau, F. (2010) ‘Influence of birth quarter on the rate of physical activities and sports participation’ Journal of Sports Sciences, 28(6), pp.627–631. Levačić, R. and Jenkins, A. (2006) ‘Evaluating the effectiveness of specialist schools in England’ School Effectiveness and School Improvement: An International Journal of Research, Policy and Practice, 17(3), pp.229-254 Taylor & Francis Online [Online]. Available at: http://www.tandfonline.com/doi/abs/10.1080/09243450600697267 (Accessed on: 5/03/2013). Morris, J. G. and Nevill, M. E. (2006) A Sporting Chance - Enhancing Opportunities For High-Level Sporting Performance: Influence Of Relative Age. London: Loughborough University and Sportnation [Online]. Available at: http://www.lboro.ac.uk/microsites/ssehs/youth-sport/downloads/research-archivedownloads/sporting-chance-relative-age-2.pdf (Accessed on: 29/12/2012). Carl Page (1008889) Page 45 BSc (Hons) Sports Science and Coaching SPE001-3 Dissertation Nakata, H. & Sakamoto, K. (2012) ‘Sex Differences In Relative Age Effects Among Japanese Athletes’ Perceptual & Motor Skills: Physical Development & Measurement, 115(1), pp.179-186. Northern Illinois University Department of Biological Sciences (2004) Chi-Square Test. Available at: www.bios.niu.edu/johns/genetics/chi_square.ppt (Accessed on: 29/03/2013). Oakley, B. (2012) ‘How to build a champion: Be born at the right time’, BBC Sport, 23 July [Online]. Available at: http://www.bbc.co.uk/sport/0/olympics/18891749 (Accessed on: 26/10/2012). Paton, G. (2012) ‘Bright children should start school at six, says academic’, The Telegraph, 16 May. [Online]. Available at: http://www.telegraph.co.uk/education/educationnews/9266592/Bright-childrenshould-start-school-at-six-says-academic.html (Accessed on: 15/01/2013). Radford University (2002) Chi-Square Test Explanation. Available at: www.radford.edu/~biol-web/.../chi-sq_explanation.doc (Accessed on: 3/04/2013). Reilly, T. (2010) Ergonomics in Sport and Physical Activity: Enhancing Performance and Improving Safety. Google Books [Online]. Available at: http://books.google.co.uk/books?id=6MakhS_g2FQC&printsec=frontcover&dq=isbn: 0736069321&hl=en&sa=X&ei=zl5xUdSuL4fnObPwgagJ&ved=0CDYQ6AEwAA#v=o nepage&q=Relative%20Age%20Effect%20&f=false (Accessed on: 23/03/2013) Roberts, S. & Fairclough, S. (2012) ‘The Influence of Relative Age Effect in the Assessment of High School Students in Physical Education in the United Kingdom’ Journal of Teaching in Physical Education, 31(1), pp.56-70. Carl Page (1008889) Page 46 BSc (Hons) Sports Science and Coaching SPE001-3 Dissertation Rosenbaum, M. (2013) ‘Month of Birth affects chance of attending Oxbridge’, BBC News. 27 February [Online]. Available at: http://www.bbc.co.uk/news/uk-politics21579484 (Accessed on: 28/03/2013). Royal Statistical Society Centre for Statistical Education (2004) Young People and Sport in England, 2002: A Survey of Young People and PE Teachers. Devon: Royal Statistical Society Centre for Statistical Education [Online]. Available at: http://www.rsscse.org.uk/stats4schools/cymraeg/images/SP_AdditionalReports(4)_tc m88-13170.pdf (Accessed on: 29/11/2012). Sedghi, A. (2011) ‘How does birth month affect your child's future?’ The Guardian, 1 November. [Online]. Available at: http://www.guardian.co.uk/news/datablog/2011/nov/01/birth-month-affects-resultswell-being. (Accessed on: 26/10/2012). Sharp, V. (2004) Chi-Square Test. Available at: http://www.enviroliteracy.org/pdf/materials/1210.pdf (Accessed on: 29/03/2013). Shepherd, J. (2011) ‘August babies are less likely to go on to top universities, says study’ The Guardian, 1 November. [Online]. Available at: http://www.guardian.co.uk/education/2011/nov/01/august-babies-top-universitiesstudy?intcmp=239 . (Accessed on: 24/10/2012). Simmons, C. & Geoffrey, P.C. (2001) ‘Season-Of-Birth Bias in association football’ Journal of Sports Sciences, 19(9), pp.677-686 Informa Ltd [Online]. Available at: https://breo.beds.ac.uk/bbcswebdav/pid-1861242-dt-content-rid3373551_1/courses/12-13TYABSPO0023/Simmons%20and%20Geoffrey_2001_Season-ofbirth%20bias%20in%20association%20football.pdf (Accessed on: 22/10/2012). Carl Page (1008889) Page 47 BSc (Hons) Sports Science and Coaching SPE001-3 Dissertation Simmons, C. (2001a) Can family planning increase your selection chances? Seasonof-birth bias in Association Football. London: The Football Association [Online]. Available at: http://www.thefa.com/GetIntoFootball/FALearning/FALearningPages/~/media/Files/P DF/Get%20into%20Football/FA_Learning_YouthModule2/Can%20family%20plannin g%20increase%20your%20selection%20chances.ashx/Can%20family%20planning %20increase%20your%20selection%20chances.pdf. (Accessed on: 5/03/2013). Simmons, C. (2001b) External Influences in Football Recruitment. London: The Football Association [Online]. Available at: http://www.thefa.com/GetIntoFootball/FALearning/FALearningPages/~/media/Files/P DF/Get%20into%20Football/FA_Learning_YouthModule2/External%20Influences%2 0in%20Football%20Recruitment.ashx/External%20Influences%20in%20Football%20 Recruitment.pdf (Accessed on: 5/03/2013). Smith, A. (2007) ‘Young people's participation in National Curriculum Physical Education: A study of 15—16 year olds in North-West England and North-East Wales’ European Physical Education Review. 13(2), pp.165-194. SAGE Publications [Online]. Available at: http://epe.sagepub.com/content/13/2/165.abstract (Accessed on: 5/03/2013). Sykes, E.D.A., Bell, J.F., Rodeiro, C.V. (2009) Birthdate Effects: A Review of the Literature from 1990-on. Cambridge: University of Cambridge [Online]. Available at: http://www.cambridgeassessment.org.uk/ca/digitalAssets/169664_Cambridge_Lit_R eview_Birthdate_d3.pdf (Accessed on: 5/03/2013). Tucker, R. & Dugas, J. (2009) The Matthew Effect. Available at: http://www.sportsscientists.com/2009/01/matthew-effect.html?m=1 (Accessed on: 29/12/2012). Carl Page (1008889) Page 48 BSc (Hons) Sports Science and Coaching SPE001-3 Dissertation UK Legislation (1996) Education Act 1996. Available at: http://www.legislation.gov.uk/ukpga/1996/56/section/8#section-8-2 (Accessed on: 15/01/2013). Van den Honert, R. (2012) ‘Evidence of the relative age effect in football in Australia’ Journal of Sports Science, 30(13), pp.1365-74. Van Wersch, A., Trew, K. and Turner, I. (1992) Post-Primary School Pupils' Interest In Physical Education: Age And Gender Differences. British Journal of Educational Psychology, 62(1), pp.56–72 Wiley Online Library [Online]. Available at: http://onlinelibrary.wiley.com/doi/10.1111/j.2044-8279.1992.tb00999.x/abstract (Accessed on: 5/03/2013). Verachtert, P., De Fraine, B., Onghena, P. and Ghesquière, P. (2010) ‘Season of birth and school success in the early years of primary education’ Oxford Review of Education, 36(3), pp.285–306. Vincent, J. and Glamser, F.D. (2006) ‘Gender Differences In The Relative Age Effect Among US Olympic Development Program Youth Soccer Players’ Journal of Sports Sciences, 24(4), pp. 405-413 Taylor & Francis Online [Online]. Available at: http://www.tandfonline.com/doi/abs/10.1080/02640410500244655 (Accessed on: 5/03/2013). Virginia Polytechnic Institute and State University (1999) Crosstabulations Statistical Significance of the Relationship between Two or More Variables. Available at: http://simon.cs.vt.edu/SoSci/converted/XTabs/ (Accessed on: 8/02/2013). Wilson, G. (1998) ‘The birthdate effect in school sports teams’ European Journal of Physical Education, 4(2), pp.139-145Taylor & Francis Online [Online]. Available at: Carl Page (1008889) Page 49 BSc (Hons) Sports Science and Coaching SPE001-3 Dissertation http://www.tandfonline.com/doi/abs/10.1080/1740898990040203 (Accessed on: 5/03/2013). Wolstencroft, E. (2005) Talent Identification and Development Programme Academic Review: Summary. Edinburgh: sportscotland [Online]. Available at: http://researchrepository.napier.ac.uk/2493/1/Academic_Review.pdf (Accessed on: 11/11/2012). Younger, M. and Warrington, M. (1996) ‘Differential Achievement of Girls and Boys at GCSE: some observations from the perspective of one school’ British Journal of Sociology of Education, 17(3), pp. 299-313 Journal Storage [Online]. Available at: http://www.jstor.org/discover/10.2307/1393405?uid=3738032&uid=2129&uid=2&uid= 70&uid=4&sid=21101497463317. (Accessed on: 5/03/2013). Zubero, J., Gil, S.M., Irazusta, A., Hoyos, I. and Gil, J. (2008) ‘Is There a Relationship Between the Birth-Date and Entering the University?’ The Open Education Journal, 1, pp.23-28 Open Access [Online]. Available at: http://www.benthamscience.com/open/toeduj/articles/V001/23TOEDUJ.pdf (Accessed on: 5/03/2013). Carl Page (1008889) Page 50 BSc (Hons) Sports Science and Coaching SPE001-3 Dissertation Appendices Appendix 1. Information sheet for participants. Appendix 2. Letter to requesting for student information. Appendix 3. Corston and Colman (2000) Inferential Statistical Decision Tree. Appendix 4. Table 1. The crosstabulation of student’s birth dates studying a sport related academic course at educational institutions. Appendix 5. Table 2. The contingency table of student’s birth months studying a sport related undergraduate degree at an educational institution. Appendix 6. Table 3. The expected and observed frequencies of student’s birth months studying A-Level (BTEC Level 3) sport related course at an educational institution. Appendix 7. Table 4. The contingency table of student’s birth months studying a GCSE (BTEC Level 1 & 2) sport related course at an educational institution. Carl Page (1008889) Page 51 BSc (Hons) Sports Science and Coaching DEPARTMENT OF SPORT & EXERCISE SCIENCES Bedford Campus Polhill Avenue Bedford MK41 9EA Web: www.beds.ac.uk/departments/sport INFORMATION SHEET The effect birth date has on choosing to study a sports related course at an educational institution. Dear Participant, Thank you for showing an interest in participating in the study. Please read this information sheet carefully before deciding whether to participate. If you decide to volunteer we thank you for your participation. If you decide not to take part there will be no disadvantage to you of any kind and we thank you for considering our request. What is the aim of the project? The purpose of the study is to test if there is a relationship between student’s birth date and decisions to study a sports related course at an educational institution. Furthermore examines the students gender, any cultural factors, social class and if they had selected a specialist sports educational institution. This study is being undertaken as part of the requirements of a BSc (Hons) Sports Science and Coaching degree. What type of participant is needed? The participant studies a sports related course from various educational institutions as two/three per category with range of ages and be of mixed genders. What will participants be asked to do? Answer a set of questions used to gather information in a survey since take part in a focus group. What are the possible risks of taking part in the study? All of information collected about the individual will be kept strictly confidential (subject to legal limitations) and follow the Data Protection Act’s 8 key principals. As data generated by the study will be retained in accordance with the University's policy on Academic Integrity. The data generated in the course of the research will be kept securely in paper or electronic form for a period of ten years after the completion of a research project. What if you decide you want to withdraw from the project? If, at any stage you wish to leave the project, then you can. There is no problem should you wish to stop taking part and it is entirely up to you. There will be no disadvantage to yourself should you wish to withdraw. What will happen to the data and information collected? Everyone that takes part in the study will receive their own results for the tests that they complete. All information and results collected will be held securely at the University of Bedfordshire and will only be accessible to related University staff. Results of this project DEPARTMENT OF SPORT & EXERCISE SCIENCES Bedford Campus Polhill Avenue Bedford MK41 9EA Web: www.beds.ac.uk/departments/sport may be published, but any data included will in no way be linked to any specific participant. Your anonymity will be preserved. What if I have any questions? Questions are always welcome and you should feel free to ask myself Carl Page or David Pears (Supervisor) any questions at any time. See details below for specific contact details. Should you want to participate in this study then please complete the attached consent form, which needs to be returned before commencing the study. This project has been reviewed and approved by the Ethics Committee of the Department of Sport and Exercise Sciences. Many Thanks, Carl Page Department of Sport and Exercise Sciences, University of Bedfordshire Bedford Campus, Polhill Avenue, Bedford Tel: 07749587386 Email: carl.page@study.beds.ac.uk David Pears Email: David.Pears@beds.ac.uk Carl Page University of Bedfordshire Polhill Avenue Bedford Bedfordshire MK419EA 14/11/2012 Principal of Corby Business Academy Corby Business Academy Academy Way Gretton Road Corby, Northamptonshire, NN17 5EB To Whom It May Concern: I am currently studying for a BSc (Hons) Sports Science and Coaching degree at the University of Bedfordshire and am writing my dissertation on the area of Relative Age Effect (RAE) in the academic study of sport. The term RAE is used to describe a bias, evident in youth sport and academia, where participation is higher amongst those born early in the relevant selection period (and correspondingly lower amongst those born late in the selection period) than would be expected from the normalised distribution of live births. Therefore, I wish to seek access to some aspects of data that you may hold on students/applicants to sport related academic courses. I would only need access to the following data held on those students;    Date of birth Gender Course title I have ethical approval for this study and can send a copy if required. Please contact me by phone on 07749587386 or by email at carl.page@study.beds.ac.uk if you have any questions or to discuss how you might provide this data. My supervisor is David Pears (david.pears@beds.ac.uk 01234 793357) and he can be contacted if you have any concerns or further questions. Thank you for your assistance. I look forward to hearing from you. Yours sincerely, Carl Page Purpose of statistical analysis Summarizing univariate data Descriptive statistics (mean, standard deviation, variance, etc) Exploring relationships between variables Testing significance of differences Form of data Number of groups Frequencies Measurements One: mean compared to a specified value Number of variables Number of variables One-sample t-test One: compared to theoretical distribution Two: tested for association Two: degree of relationship Chi-square goodness-of-fit test Chi-square test for association Level of measurement Ordinal Spearman's rho Two Independent samples Related samples Form of data Form of data Multiple: effect of 2+ predictors on a dependant variable Multiple regression Multiple Ordinal Interval Mann-Whitney U test Independentsamples t-test Ordinal Independent samples One independent variable Multiple independent variables One-way ANOVA Multifactorial ANOVA Related samples Repeatedmeasures ANOVA Interval Interval Pearson's correlation cooeficient Wilcoxon matchedpairs test Figure 9. Choosing an appropriate statistical procedure Pairedsamples t-test Source: Corston and Colman (2000) SPE001-3 Dissertation Appendix 4. Table 1. The crosstabulation of student’s birth dates studying a sport related academic course at educational institutions. Observed * Expected Crosstabulation Expected SeptemberDecember Observed September-December January-April Count Total 169 0 3269 Expected Count 1089.8 1089.4 1089.8 3269.0 % within Observed 94.8% 5.2% .0% 100.0% 7 2930 70 3007 1002.4 1002.1 1002.4 3007.0 .2% 97.4% 2.3% 100.0% 0 7 3037 3044 1014.8 1014.4 1014.8 3044.0 .0% .2% 99.8% 100.0% 3107 3106 3107 9320 Expected Count 3107.0 3106.0 3107.0 9320.0 % within Observed 33.3% 33.3% 33.3% 100.0% Count % within Observed Count Expected Count % within Observed Total May-August 3100 Expected Count May-August January-April Count Carl Page (1008889) BSc (Hons) Sports Science and Coaching SPE001-3 Dissertation Appendix 5. Table 2. The contingency table of student’s birth months studying a sport related undergraduate degree at an educational institution. Observed * Expected Crosstabulation Expected SeptemberDecember Observed September-December January-April Count Total 159 0 3110 Expected Count 1036.7 1036.7 1036.7 3110.0 % within Observed 94.9% 5.1% .0% 100.0% 0 2792 68 2860 953.3 953.3 953.3 2860.0 .0% 97.6% 2.4% 100.0% 0 0 2883 2883 961.0 961.0 961.0 2883.0 .0% .0% 100.0% 100.0% 2951 2951 2951 8853 Expected Count 2951.0 2951.0 2951.0 8853.0 % within Observed 33.3% 33.3% 33.3% 100.0% Count % within Observed Count Expected Count % within Observed Total May-August 2951 Expected Count May-August January-April Count Carl Page (1008889) BSc (Hons) Sports Science and Coaching SPE001-3 Dissertation Appendix 6. Table 3. The expected and observed frequencies of student’s birth months studying A-Level (BTEC Level 3) sport related course at an educational institution. Observed * Expected Crosstabulation Expected SeptemberDecember Observed September-December May-August Total May-August Total Count 115 10 0 125 Expected Count 41.8 41.4 41.8 125.0 92.0% 8.0% .0% 100.0% 0 104 2 106 Expected Count 35.4 35.1 35.4 106.0 % within Observed .0% 98.1% 1.9% 100.0% 0 0 113 113 Expected Count 37.8 37.4 37.8 113.0 % within Observed .0% .0% 100.0% 100.0% Count 115 114 115 344 115.0 114.0 115.0 344.0 33.4% 33.1% 33.4% 100.0% % within Observed January-April January-April Count Count Expected Count % within Observed Carl Page (1008889) BSc (Hons) Sports Science and Coaching SPE001-3 Dissertation Appendix 7. Table 4. The contingency table of student’s birth months studying a GCSE (BTEC Level 1 & 2) sport related course at an educational institution. Observed * Expected Crosstabulation Expected SeptemberDecember Observed September-December Count 0 34 11.3 11.3 11.3 34.0 100.0% .0% .0% 100.0% 7 34 0 41 13.7 13.7 13.7 41.0 17.1% 82.9% .0% 100.0% 0 7 41 48 Expected Count 16.0 16.0 16.0 48.0 % within Observed .0% 14.6% 85.4% 100.0% 41 41 41 123 41.0 41.0 41.0 123.0 33.3% 33.3% 33.3% 100.0% Count Expected Count % within Observed Total Total 0 % within Observed May-August May-August 34 Expected Count January-April January-April Count Count Expected Count % within Observed Carl Page (1008889) BSc (Hons) Sports Science and Coaching