Art of Stat: Regression

Name: Art of Stat: Regression
Rating: 4.7 (20 reviews)
Author: Bernhard Klingenberg

Fit Linear Regression Model

Free · In‑App Purchases · Designed for iPad

20 Ratings
Ages

4+
Years
Category

Education
Developer

Bernhard Klingenberg
Language

EN
English
Size

34.5
MB

Legacy Version: Please consider upgrading to the new "Art of Stat" app. Go to the App Store and search for "Art of Stat"! It contains this and many other modules. News: The Regression app is now part of the all new "Art of Stat" app, which contains the Regression and seven other modules. Please consider getting the Art of Stat app for the latest updates and features from the App Store. Simply search for "Art of Stat" on the App Store. This app will continue to work, but future development is concentrated on the new Art of Stat app. Original Description: The Art of Stat: Regression app creates scatterplots, fits linear, logistic, Poisson or exponential regression models, and displays inference for model parameters (standard errors, confidence intervals, P-values). The app now also fits multiple linear and logistic 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

Ratings & Reviews

4.7

out of 5

20 Ratings

Easy to use interface
03/03/2023

Will8R
This is a very comprehensive app with important output well organized in tables and great plots. Easy to make a screenshot and share with others. This is so much better than having to use R.
Easy to use interface
03/03/2023

Will8R

This is a very comprehensive app with important output well organized in tables and great plots. Easy to make a screenshot and share with others. This is so much better than having to use R.
Excellent app, and simple to use!
05/28/2023

987654321+
Only request is that the developer adds feature that lets iPad version display in portrait mode (like most of the other Art of Stat apps do)

Developer Response
Thank you for the feedback. The latest version better supports tablets in portrait or landscape view.
Excellent app, and simple to use!
05/28/2023

987654321+

Only request is that the developer adds feature that lets iPad version display in portrait mode (like most of the other Art of Stat apps do)
Developer Response 09/06/2024
Thank you for the feedback. The latest version better supports tablets in portrait or landscape view.
Nice and easy
03/24/2023

Phi 88
Easy to fit regression model and focus on interpreting the output. Lots of plots and features. Take a screenshot and share.
Nice and easy
03/24/2023

Phi 88

Easy to fit regression model and focus on interpreting the output. Lots of plots and features. Take a screenshot and share.
Intuitive!
02/13/2025

JohnnyJMR
I like doing a Regression via mobile.
Intuitive!
02/13/2025

JohnnyJMR

I like doing a Regression via mobile.

- Legacy Version: Continuous to work, but I recommend upgrading to the new "Art of Stat" app, which contains Regression and 7 other modules. - Search for "Art of Stat" in the App Store. - Multiple Logistic Regression