Topic hub
Regression & Correlation
How variables relate to each other: correlation coefficients, lines of best fit, and linear regression for measuring an association's strength.
Coefficient of Determination (R-Squared) Explained
The coefficient of determination (R²) measures how well a regression model fits your data. Learn the formula, a worked example, and when adjusted R² is better.
Correlation Coefficient Formula: Interpreting r
See how to calculate a correlation coefficient and, more importantly, what an r value does and doesn't license you to conclude about your data.
Correlation Definition: Positive, Negative & Types Explained
Learn the correlation definition: a numerical measure of how strongly two variables are related, plus positive, negative, and zero correlation explained.
Correlation vs Causation: The Key Differences
Learn correlation vs causation: why correlation doesn't imply causation, what spurious correlation means, and how scientists establish true cause-and-effect.
Linear Regression Assumptions: What They Are & How to Check
Learn the five linear regression assumptions — linearity, independence, homoscedasticity, normality, no multicollinearity — plus how to test each one.
Linear Regression: Equation, Formula & How It Works
Understand linear regression: the regression equation, slope and intercept formula, and how to fit a least-squares line with a fully worked numeric example.
Multicollinearity & Variance Inflation Factor (VIF) Explained
Learn what multicollinearity is, why it distorts regression results, and how the Variance Inflation Factor (VIF) detects and measures it, with a worked example.
Pearson Correlation Coefficient: Formula, Covariance & Spearman
Learn the Pearson correlation coefficient formula, how it relates to covariance, how to interpret r values, and when to use Spearman rank correlation instead.
Regression to the Mean: Definition & Real-World Examples
Learn what regression to the mean is, how Galton discovered it, the key formula, and real-world examples from sports, medicine, and education.
Simpson's Paradox: Definition, Examples, and Why It Happens
Simpson's paradox occurs when a trend in data subgroups reverses when the groups are combined. Learn what causes it, how to spot it, and real-world examples.