Art of Stat: Regression

News Feb. 2026:

The new Art of Stat app includes this Art of Stat: Regression module and many others useful for statistics and data science. Please install the new Art of Stat app now.

However, this legacy version will continue to work

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Original Description:

The Art of Stat: Linear Regression app creates scatterplots, fits simple (and multiple) linear, logistic or exponential regression models, and displays inference for model parameters (standard errors, confidence intervals, P-values).

New: The app now also fits multiple linear regression models and allows including categorical predictors and two-way interactions!

The app computes and displays confidence intervals for the mean response and prediction intervals for a future response. The fitted model and the intervals are visualized on the scatterplot, and you can obtain and plot raw and standardized residuals.

You can color points on the scatterplot according to a third quantitative or categorical variable to reveal additional patterns.

For data entry, you can enter your own data via the new Data Editor app, import a CSV file, or choose from several pre-loaded example datasets.

Features:

- Scatterplot Matrix to study pairwise relationships

- Display the fitted regression equation on the scatterplot, even when including (and additional) categorical predictor

- Table with all regression coefficients and their inferences (P-values, confidence intervals)

- Summary statistics such has R^2, R^2-adjusted and maximized Log-Likelihood

- Fitted values and (standardized) residuals (which you can download)

- Predictions for your own values of the explanatory variables

- Residual plot to check assumptions and for outliers

- lets you make predictions for your own values of the explanatory variables

- constructs a residual plot to check assumptions and for outliers