Regression, PSM & Neural Networks
Free set of regression calculators, statistical matching techniques, and neural network calculators — with assumption checks, charts and step-by-step results.
6 free calculators Checks assumptions APA-style reports
Regression calculators 6 calculators
| Calculator | Description | Statistic | |
|---|---|---|---|
| Simple Linear Regression | Calculates the best fitting equation and the ANOVA table. Draws the regression line and the residual plot, and tests the linear model assumptions: residual normality, power, outliers. Step by step calculation, reports in APA style. | ||
| Multiple Linear Regression | Multiple variables and transformations. Best fitting equation, ANOVA table, coefficients and standardized coefficients. Line fit, residual, Q-Q and histogram plots. Tests residual normality, power, homoscedasticity, multicollinearity and outliers. | ||
| Binary Logistic Regression | Logistic regression calculator with multiple variables. The dependent variable (y) is binary — for example: yes / no, or 1 / 0. | χ² = 2(LL1−LL0) | |
| Multinomial Logistic Regression | Multinomial logistic regression calculator with multiple variables. The dependent variable (y) is a categorical variable — for example: red, green, blue. | χ² = 2(LL1−LL0) | |
| Propensity Score Matching | Propensity score estimation is performed using logistic regression, and matching is done using the nearest neighbor method, with an optional caliper. | ||
| Neural Network Calculator | Learns the relationship between the inputs and the outputs, predicts new data, and generates the network plot. Supports feed-forward and recurrent networks (RNN, LSTM, GRU). | feed-forward · RNN · LSTM · GRU |