Leverage the power of correlation and regression to understand relationships and make predictions with data.
Practice Correlation Extremes
Simple Linear Regression
Simple Linear Regression Practice 1
Simple Linear Regression Practice 2
Practice Least Squares
Regression and Prediction
This course introduces correlation and regression, which are used to quantify the strength of the relationship between variables and to compute the slope and intercept of the regression line. It explores two applications of these methods, using correlated measurements to make informed guesses for measurements that are not available, and making predictions for future events. Datasets used in these lessons include weights and other measurements from penguins and a time series of annual average temperatures. Later lesson explore nonlinear relationships and Simpson's paradox.
- Mean squared error
- Mean absolute error
Prerequisites and next steps
Exploring Data Visually Introduction to Probability