Art of Stat: Regression 4+

Fit Linear Regression Model

Bernhard Klingenberg

Designed for iPad

    • Free
    • Offers In-App Purchases

Screenshots

Description

Simple & Multiple Linear Regression. Logistic Regression. Scatter- and Residual Plots. Parameter Estimates, Inference & Prediction.

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

The app computes 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.

New: 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.

New: Fit a multiple linear regression model with both quantitative and categorical predictors. The app

- creates a Scatterplot Matrix to study pairwise relationships

- clearly displays the fitted regression equation, including dummy variables

- presents a table with all regression coefficients

- obtains summary statistics such has R^2-adjusted

- gives fitted values and (standardized) residuals (which you can download)

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

- constructs a residual plot to check assumptions and for outliers

What’s New

Version 1.5.0

- Multiple Linear Regression
- Quantitative and Categorical Predictors
- Data Editor
- Scatterplot Matrix

App Privacy

The developer, Bernhard Klingenberg, indicated that the app’s privacy practices may include handling of data as described below. For more information, see the developer’s privacy policy.

Data Not Collected

The developer does not collect any data from this app.

Privacy practices may vary based on, for example, the features you use or your age. Learn More

More By This Developer

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