Why this chapter matters
Prediction and comparison tasks often require relationship models, and ANOVA extends mean comparison to more than two groups.
What you will learn
- Interpret correlation direction and strength without overstating causation.
- Fit and interpret a simple linear regression model including slope and residuals.
- Explain ANOVA as variance-based comparison of multiple group means.
Lessons in this chapter
- Correlation and causation boundariesSeparate association evidence from causal claims. Read the full guide →
- Simple linear regression basicsInterpret slope, intercept, prediction, and residual error. Read the full guide →
- Diagnostics and model cautionCheck linearity, outliers, and extrapolation risk.
- ANOVA first lookDescribe null and alternative ideas for comparing three or more means.
Study task
Given spending and sales data for several stores, fit a simple linear model, interpret slope in units, and state one reason the relationship may still be non-causal.
Chapter checkpoint
What does the slope of a simple linear regression line represent?
It is the expected change in the response variable for a one-unit increase in the predictor, on average, within the modeled range.