Art of Stat: Regression
by Bernhard Klingenberg, Art of Stat
Simple & Multiple Linear Regression, Logistic Regression, Inference & Prediction
| App Name | Art of Stat: Regression |
|---|---|
| Developer | Bernhard Klingenberg, Art of Stat |
| Category | Education |
| Download Size | 29 MB |
| Latest Version | 1.8.0 |
| Average Rating | 0.00 |
| Rating Count | 0 |
| Google Play | Download |
| AppBrain | Download Art of Stat: Regression Android app |
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 (dummy variables) and two-way interactions.
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.
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.
The app
- creates a Scatterplot Matrix to study pairwise relationships
- displays the fitted regression equation, including dummy variables
- presents a table with all regression coefficients and their inferences (P-values, confidence intervals)
- 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
Recent changes:
Version 1.8.0 (18)
New: The app now also fits multiple linear regression models and allows including categorical predictors (dummy variables) and two-way interactions.
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.
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.
The app
- creates a Scatterplot Matrix to study pairwise relationships
- displays the fitted regression equation, including dummy variables
- presents a table with all regression coefficients and their inferences (P-values, confidence intervals)
- 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
Recent changes:
Version 1.8.0 (18)
