Art of Stat: Regression
1.9.0 by Bernhard Klingenberg, Art of Stat (0 Reviews) September 12, 2024
Latest Version
Version
1.9.0
1.9.0
Update
September 12, 2024
September 12, 2024
Developer
Bernhard Klingenberg, Art of Stat
Bernhard Klingenberg, Art of Stat
Categories
Education
Education
Platforms
Android
Android
Downloads
0
0
License
Free
Free
Package Name
com.artofstat.regression
com.artofstat.regression
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More About Art of Stat: Regression
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
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
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