This course covers topics such as log transformation for response and predictor variables, equal variance test, variance inflation factors, comparison of confidence intervals and prediction intervals, subset F-test in multiple linear regression, individual F-test, overall F-test, adjusted sum of squares and sequential sum of squares, multiple linear regression examples, information criteria and PRESS, best subsets regression, stepwise regression, ANOVA basics, slope test, interaction models, additive models, P-value demonstration, slope demonstrations, mean squared error, coefficient of determination, and linear regression assumptions. The course aims to teach statistical analysis techniques and methods using practical examples and demonstrations. It is designed for individuals interested in expanding their knowledge of statistics and data analysis.
Overview
Syllabus
STAT 501 Log Transform for response and predictor variables.
STAT 501 Equal Variance Test.
STAT 501 Variance Inflation Factors.
STAT 501: Comparison of CI and PI.
STAT501: Subset F-test in Multiple Linear Regression.
STAT 501 Individual F-test.
STAT501: Overall F test.
STAT501: Adjusted SS and Sequential SS.
STAT501, 5-3 Multiple linear regression example.
STAT501: Information Criteria & PRESS.
STAT 501: 10-3 Best Subsets Regression.
STAT501 Stepwise Regression.
STAT501Sec2 6 SLR anova2.
STAT501: ANOVA: The Basics.
STAT501 Slope Test.
501Interaction model.
501 Additive Model.
501 8-8 chalk talk video.
501 P-Value Demonstration.
501 Negative Slope Demonstration.
501 Positive Slope Demo.
501 SLR MSE.
STAT 501 Coefficient of Determination.
STAT 501 SLR Assumptions.
Taught by
Penn State Statistics
