Cal Teach is a science and math teacher preparation program modeled after UTeach at the Universit... more Cal Teach is a science and math teacher preparation program modeled after UTeach at the University of Texas, Austin. Math for America (MfA), Berkeley, which is part of the national MfA effort, is a 5-year master teacher fellowship program for experienced math and science teachers. Both programs aim to prepare K-12 teachers to excel by strengthening their pedagogical content knowledge and their science content knowledge. We describe the role that statistics education plays in these two synergistic programs and make recommendations how aspects of these efforts might be more broadly adopted.
Summary We derive a model, using trigonometry and the Normal distribution, for the probability th... more Summary We derive a model, using trigonometry and the Normal distribution, for the probability that a golf putt is successful. We describe a class activity in which we lead the students through the steps of examining the data, considering possible models, constructing a probability model and checking the fit. The model is, of necessity, oversimplified, a point which the class discusses at the end of the demonstration.
<p> <italic>Communicating with Data: The Art of Writing for Data Science</italic&g... more <p> <italic>Communicating with Data: The Art of Writing for Data Science</italic> aims to help students and researchers write about their data insights in a way that is both compelling and faithful to the data. This book aims to be both a resource for students who want to learn how to write about scientific findings both formally and for broader audiences and a textbook for instructors who are teaching science communication. In addition, a researcher who is looking for help with writing can use this book to self-train. The book consists of five parts. Part I helps the novice learn to write by reading the work of others. Part II delves into the specifics of how to describe data at a level appropriate for publication, create informative and effective visualizations, and communicate an analysis pipeline through well-written, reproducible code. Part III demonstrates how to reduce a data analysis to a compelling story and organize and write the first draft of a technical paper. Part IV addresses revision; this includes advice on writing about statistical findings in a clear and accurate way, general writing advice, and strategies for proof-reading and revising. Finally, Part V gives advice about communication strategies beyond the witten page, which includes giving talks, building a professional network, and participating in online communities. This part also contains 22 "portfolio prompts" aimed at building upon the guidance and examples in the earlier parts of the book and building a writer's portfolio of data communication.</p>
Putting data into the public domain is not the same thing as making those data accessible for int... more Putting data into the public domain is not the same thing as making those data accessible for intelligent analysis. A distinguished group of editors and experts who were already engaged in one way or another with the issues inherent in making research data public came together with statisticians to initiate a dialogue about policies and practicalities of requiring published research to be accompanied by publication of the research data. This dialogue carried beyond the broad issues of the advisability, the intellectual integrity, the scientific exigencies to the relevance of these issues to statistics as a discipline and the relevance of statistics, from inference to modeling to data exploration, to science and social science policies on these issues.
<p>This chapter provides general advice for strengthening science writing. This advice incl... more <p>This chapter provides general advice for strengthening science writing. This advice includes how to trim phrases, write in a straightforward manner, and use an active voice and concrete nouns. Additionally, the chapter examines how to write from a higher level by, e.g., balancing between specific information and general statements, and smoothly transitioning between paragraphs and sections to improve the reading experience and provide a road map for the reader. Finally, also provided is a list of common grammatical errors to watch out for.</p>
<p>This chapter includes 22 exercises and activities to help the new writer further practic... more <p>This chapter includes 22 exercises and activities to help the new writer further practice their writing skills and build a portfolio of writing samples. The portfolio pieces include prompts for critiquing visualizations, editing Wikipedia entries, writing blog posts and book reports, translating scientific abstracts into everyday language, and describing effective analogies.</p>
This chapter contains many classroom activities and demonstrations to help students understand ba... more This chapter contains many classroom activities and demonstrations to help students understand basic probability calculations, including conditional probability and Bayes rule. Many of the activities alert students to misconceptions about randomness. They create dramatic settings where the instructor discerns real coin flips from fake ones, students modify dice and coins in order to load them, students “accused” of lying based on the outcome of an inaccurate simulated lie detector face their classmates. Additionally, probability models of real outcomes offer good value: first we can do the probability calculations, and then can go back and discuss the potential flaws of the model.
This article presents several student participation activities combining (i) the basics of random... more This article presents several student participation activities combining (i) the basics of random sampling, (ii) practical complications (e.g., how do survey takers deal with biases from selection, nonresponse, and question wording), and (iii) theoretical ideas (e.g., sampling with unequal probabilities). One way students learn about sampling is actually to collect some data. It gives them a feel for the practical struggles and small decisions needed in real data gathering, and it illustrates many key ideas in sampling. Another way is to discuss surveys reported in the popular press. It’s fun to read and critique unusual news stories, and real survey findings bring home the importance of the statistical idea being illustrated. We have developed several demonstrations and examples of survey sampling to use in the classroom, which we use regularly in our introductory statistics courses for college students who have completed high school algebra. We have also had success introducing th...
This chapter addresses how to create statistical graphs that are effective in communicating findi... more This chapter addresses how to create statistical graphs that are effective in communicating findings. This includes how to select an appropriate type of plot to reveal underlying structure in the data, facilitate important comparisons, and create a context for interpreting the distributions and relationships observed. The chapter also covers how to read common univariate and bivariate plots, pay attention to the details in making and interpreting plots, and create plots that help make a convincing argument.
The potential for multimedia to enhance the statistics curriculum is clear, but how to develop in... more The potential for multimedia to enhance the statistics curriculum is clear, but how to develop instructional materials that take advantage of the riches that multimedia has to o er is not as transparent. It requires more than a simple translation of textbooks into HTML and statistical software into Java in order to obtain a product that is functional, e ective, and artful. Accepted de nitions of good design and good educational paradigms do not necessarily hold in the new digital media. In this article we would like to consider ways in which multimedia can augment the statistics curriculum. We will provide examples drawn from our e orts to design instructional labs for use in teaching introductory statistics to university students who are non-science majors. We also describe a general collection of tools we have developed to build these types of labs. For further information on our project, Tools for an Interactive Learning Environment (TILE), see www.stat.berkeley.edu/users/nolan/T...
An essential component of statistics education is to provide first-hand experience with applicati... more An essential component of statistics education is to provide first-hand experience with applications of statistics where students learn how to analyze data in the context of addressing a scientific question. The approach we present brings the work of statistics researchers and data analysts to the community of educators so that they can utilize their expertise, data, problems, and solutions in teaching statistics. We hope to accomplish this sharing of ideas and materials through a new type of “document”, an electronic lab notebook that captures the research process and acts as a database of the statistician’s activities and analysis. These documents can be explored in rich new ways: they can have interactive controls that allow students to modify computations, they can be projected into different views for different audiences, and they can contain different branches of analysis for exploration.
Cal Teach is a science and math teacher preparation program modeled after UTeach at the Universit... more Cal Teach is a science and math teacher preparation program modeled after UTeach at the University of Texas, Austin. Math for America (MfA), Berkeley, which is part of the national MfA effort, is a 5-year master teacher fellowship program for experienced math and science teachers. Both programs aim to prepare K-12 teachers to excel by strengthening their pedagogical content knowledge and their science content knowledge. We describe the role that statistics education plays in these two synergistic programs and make recommendations how aspects of these efforts might be more broadly adopted.
Summary We derive a model, using trigonometry and the Normal distribution, for the probability th... more Summary We derive a model, using trigonometry and the Normal distribution, for the probability that a golf putt is successful. We describe a class activity in which we lead the students through the steps of examining the data, considering possible models, constructing a probability model and checking the fit. The model is, of necessity, oversimplified, a point which the class discusses at the end of the demonstration.
<p> <italic>Communicating with Data: The Art of Writing for Data Science</italic&g... more <p> <italic>Communicating with Data: The Art of Writing for Data Science</italic> aims to help students and researchers write about their data insights in a way that is both compelling and faithful to the data. This book aims to be both a resource for students who want to learn how to write about scientific findings both formally and for broader audiences and a textbook for instructors who are teaching science communication. In addition, a researcher who is looking for help with writing can use this book to self-train. The book consists of five parts. Part I helps the novice learn to write by reading the work of others. Part II delves into the specifics of how to describe data at a level appropriate for publication, create informative and effective visualizations, and communicate an analysis pipeline through well-written, reproducible code. Part III demonstrates how to reduce a data analysis to a compelling story and organize and write the first draft of a technical paper. Part IV addresses revision; this includes advice on writing about statistical findings in a clear and accurate way, general writing advice, and strategies for proof-reading and revising. Finally, Part V gives advice about communication strategies beyond the witten page, which includes giving talks, building a professional network, and participating in online communities. This part also contains 22 "portfolio prompts" aimed at building upon the guidance and examples in the earlier parts of the book and building a writer's portfolio of data communication.</p>
Putting data into the public domain is not the same thing as making those data accessible for int... more Putting data into the public domain is not the same thing as making those data accessible for intelligent analysis. A distinguished group of editors and experts who were already engaged in one way or another with the issues inherent in making research data public came together with statisticians to initiate a dialogue about policies and practicalities of requiring published research to be accompanied by publication of the research data. This dialogue carried beyond the broad issues of the advisability, the intellectual integrity, the scientific exigencies to the relevance of these issues to statistics as a discipline and the relevance of statistics, from inference to modeling to data exploration, to science and social science policies on these issues.
<p>This chapter provides general advice for strengthening science writing. This advice incl... more <p>This chapter provides general advice for strengthening science writing. This advice includes how to trim phrases, write in a straightforward manner, and use an active voice and concrete nouns. Additionally, the chapter examines how to write from a higher level by, e.g., balancing between specific information and general statements, and smoothly transitioning between paragraphs and sections to improve the reading experience and provide a road map for the reader. Finally, also provided is a list of common grammatical errors to watch out for.</p>
<p>This chapter includes 22 exercises and activities to help the new writer further practic... more <p>This chapter includes 22 exercises and activities to help the new writer further practice their writing skills and build a portfolio of writing samples. The portfolio pieces include prompts for critiquing visualizations, editing Wikipedia entries, writing blog posts and book reports, translating scientific abstracts into everyday language, and describing effective analogies.</p>
This chapter contains many classroom activities and demonstrations to help students understand ba... more This chapter contains many classroom activities and demonstrations to help students understand basic probability calculations, including conditional probability and Bayes rule. Many of the activities alert students to misconceptions about randomness. They create dramatic settings where the instructor discerns real coin flips from fake ones, students modify dice and coins in order to load them, students “accused” of lying based on the outcome of an inaccurate simulated lie detector face their classmates. Additionally, probability models of real outcomes offer good value: first we can do the probability calculations, and then can go back and discuss the potential flaws of the model.
This article presents several student participation activities combining (i) the basics of random... more This article presents several student participation activities combining (i) the basics of random sampling, (ii) practical complications (e.g., how do survey takers deal with biases from selection, nonresponse, and question wording), and (iii) theoretical ideas (e.g., sampling with unequal probabilities). One way students learn about sampling is actually to collect some data. It gives them a feel for the practical struggles and small decisions needed in real data gathering, and it illustrates many key ideas in sampling. Another way is to discuss surveys reported in the popular press. It’s fun to read and critique unusual news stories, and real survey findings bring home the importance of the statistical idea being illustrated. We have developed several demonstrations and examples of survey sampling to use in the classroom, which we use regularly in our introductory statistics courses for college students who have completed high school algebra. We have also had success introducing th...
This chapter addresses how to create statistical graphs that are effective in communicating findi... more This chapter addresses how to create statistical graphs that are effective in communicating findings. This includes how to select an appropriate type of plot to reveal underlying structure in the data, facilitate important comparisons, and create a context for interpreting the distributions and relationships observed. The chapter also covers how to read common univariate and bivariate plots, pay attention to the details in making and interpreting plots, and create plots that help make a convincing argument.
The potential for multimedia to enhance the statistics curriculum is clear, but how to develop in... more The potential for multimedia to enhance the statistics curriculum is clear, but how to develop instructional materials that take advantage of the riches that multimedia has to o er is not as transparent. It requires more than a simple translation of textbooks into HTML and statistical software into Java in order to obtain a product that is functional, e ective, and artful. Accepted de nitions of good design and good educational paradigms do not necessarily hold in the new digital media. In this article we would like to consider ways in which multimedia can augment the statistics curriculum. We will provide examples drawn from our e orts to design instructional labs for use in teaching introductory statistics to university students who are non-science majors. We also describe a general collection of tools we have developed to build these types of labs. For further information on our project, Tools for an Interactive Learning Environment (TILE), see www.stat.berkeley.edu/users/nolan/T...
An essential component of statistics education is to provide first-hand experience with applicati... more An essential component of statistics education is to provide first-hand experience with applications of statistics where students learn how to analyze data in the context of addressing a scientific question. The approach we present brings the work of statistics researchers and data analysts to the community of educators so that they can utilize their expertise, data, problems, and solutions in teaching statistics. We hope to accomplish this sharing of ideas and materials through a new type of “document”, an electronic lab notebook that captures the research process and acts as a database of the statistician’s activities and analysis. These documents can be explored in rich new ways: they can have interactive controls that allow students to modify computations, they can be projected into different views for different audiences, and they can contain different branches of analysis for exploration.
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