CHAPTER 07
Regression Analysis
Regression Analysis
LEARNING PATH
Topics in this chapter
Read by topic; each article preserves the complete explanations, formulas, and tables from the original notes.
- 01→
Simple Linear Regression
Learn least squares, residual diagnostics, sums-of-squares decomposition, coefficient tests, and prediction with one quantitative predictor.
35 content blocks - 02→
Pearson Correlation
Measure linear association between two quantitative variables and connect Pearson’s r with the regression slope, R², t tests, and F tests.
19 content blocks - 03→
Fisher’s z Transformation
Transform correlations for confidence intervals, tests against a specified population correlation, and comparisons between independent groups.
16 content blocks - 04→
Spearman Rank Correlation
Measure monotonic association with ranks and understand ties, inference methods, and differences from Pearson correlation.
21 content blocks - 05→
Coefficient of Determination (R²)
Interpret the proportion of variation explained by a regression model, its relationship to r², t, and F, and its important limitations.
18 content blocks - 06→
Multiple Regression
Interpret conditional coefficients, overall and individual tests, categorical predictors, confounding adjustment, and model diagnostics.
31 content blocks