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From Yuk Tung Liu
Ch 53: Kruskal-Wallis Test Ch 54: Spearman Rank-Order Correlation Coefficient (notebook pages 219-221) -
From Yuk Tung Liu
Ch 49: Interpreting the Slope of a Binary Predictor Variable Ch 50: Multiple Logistic Regression Ch 51: Inference for Logistic Regression (notebook pages 206-212) -
From Yuk Tung Liu
Ch 45: Logistic Regression (Intro) Ch 46: Odds and log(odds) Ch 47: Making predictions using the log(odds) equation Ch 48: Interpreting the Slopes in the log(odds)… -
From Yuk Tung Liu
Ch 41: Prediction for Log Transformations, Ch 42: Examining Residual Plots, Ch 43: Interpreting Coefficient in Log Models, Ch 44: Correcting Heteroscedasticity… -
From Yuk Tung Liu
Ch 39: Randomization test, Ch 40: Transformations of Variables (notebook pages 181-190) -
From Yuk Tung Liu
Ch 38: Z and t-tests for the Slopes in Multiple Regression (notebook pages 178-180), Review for Exam 2 -
From Yuk Tung Liu
Ch 37: R-square and Chi-square test for overall regression effect, Ch 38: Z and t-tests for the Slopes in Multiple Regression (notebook pages 171-177) -
From Yuk Tung Liu
Ch 34: Interpreting the Slopes, Ch 35: Interpreting the Slopes Graphically, Ch 36: Assumptions, Ch 37: R-square and Chi-square test for overall regression effect… -
From Yuk Tung Liu
Ch 29: ANOVA for Regression Model, Ch 30: Controlling for a Confounder (notebook pages 143-151) -
Spring 2019 Stat 200 Lecture 18
41:46 duration 41 minutes 46 seconds
Spring 2019 Stat 200 Lecture 18
From Yuk Tung Liu
Ch 31: Interactions bewteen a Binary and Quantitative Variable, Ch 32: Regression with 2 Binary Predictors, Ch 33: 3D Scatter Plot (notebook pages 151-160) -
From Yuk Tung Liu
Ch 27: Confidence Intervals for the Slope, Ch 28: Significance Tests for the Slope, Ch 29: ANOVA for Regression Model (notebook pages 133-142)