Park University's online Advanced Statistics course, EC315, is required of all Park Economics stu... more Park University's online Advanced Statistics course, EC315, is required of all Park Economics students, and is the second statistics course in the undergraduate program, and is also required of MBA students. EC315 also goes by the name, Quantitative Research Methods, and focuses on hypothesis testing and multiple linear and non-linear regression—with multiple regression constituting about half of the course – plus the course project. Students are required to find a suitable project and data sets for multiple regression (usually on the internet), perform the analyses and interpretations, and submit a final paper with their results. Students are given a choice of using either Excel's Data Analysis ToolPak or Minitab, which comes with the textbook as Minitab 14 Student edition. Minitab provides a full set of analysis outputs within the regression tool to allow the researcher to evaluate regression equations and determine which independent variables provide the best predictors of the dependent variable. A crucial part of the online course is the full set of tutorials showing students how to perform all the different types of statistical analyses in both Excel and Minitab. In addition, instructors can use the eCollege Live Chat Pro feature to give live demonstrations of how to use the statistical software by sharing their desktop and lecturing via microphone. Although students may be located literally around the world, they still can participate in live computer lab demonstrations and see directly how to use statistical software to solve problems and perform statistical analyses. Linear regression All multiple linear regression equations have the general form shown in Eqn. 1. (Eqn. 1) y = b + m 1 x 1 + m 2 x 2 + … + m n x n In Eqn. 1, y is the dependent variable and the various x i 's are the independent variables. The constant, b, is the y intercept for all x i = 0, and the various m i 's are the slopes/coefficients of the corresponding independent variables, x i. Unlike the two-dimensional case, y = mx + b, in which the independent variable x is the sole contributor to predictable changes in the dependent variable, in multiple regression, different independent variables contribute unevenly to changes in the dependent variable. Hence, in any multiple regression, it's important to evaluate the contributions of each independent variable – in fact, it may be necessary to drop some independent variables and/or add new ones to the regression. Minitab allows the user to make such evaluations and determinations. As an example, one Park student conducted a recent study of public high school graduation rates as a function of school funding, average family income, average
Park University's online Advanced Statistics course, EC315, is required of all Park Economics stu... more Park University's online Advanced Statistics course, EC315, is required of all Park Economics students, and is the second statistics course in the undergraduate program, and is also required of MBA students. EC315 also goes by the name, Quantitative Research Methods, and focuses on hypothesis testing and multiple linear and non-linear regression—with multiple regression constituting about half of the course – plus the course project. Students are required to find a suitable project and data sets for multiple regression (usually on the internet), perform the analyses and interpretations, and submit a final paper with their results. Students are given a choice of using either Excel's Data Analysis ToolPak or Minitab, which comes with the textbook as Minitab 14 Student edition. Minitab provides a full set of analysis outputs within the regression tool to allow the researcher to evaluate regression equations and determine which independent variables provide the best predictors of the dependent variable. A crucial part of the online course is the full set of tutorials showing students how to perform all the different types of statistical analyses in both Excel and Minitab. In addition, instructors can use the eCollege Live Chat Pro feature to give live demonstrations of how to use the statistical software by sharing their desktop and lecturing via microphone. Although students may be located literally around the world, they still can participate in live computer lab demonstrations and see directly how to use statistical software to solve problems and perform statistical analyses. Linear regression All multiple linear regression equations have the general form shown in Eqn. 1. (Eqn. 1) y = b + m 1 x 1 + m 2 x 2 + … + m n x n In Eqn. 1, y is the dependent variable and the various x i 's are the independent variables. The constant, b, is the y intercept for all x i = 0, and the various m i 's are the slopes/coefficients of the corresponding independent variables, x i. Unlike the two-dimensional case, y = mx + b, in which the independent variable x is the sole contributor to predictable changes in the dependent variable, in multiple regression, different independent variables contribute unevenly to changes in the dependent variable. Hence, in any multiple regression, it's important to evaluate the contributions of each independent variable – in fact, it may be necessary to drop some independent variables and/or add new ones to the regression. Minitab allows the user to make such evaluations and determinations. As an example, one Park student conducted a recent study of public high school graduation rates as a function of school funding, average family income, average
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