NoCode Python Statistics
It turns the boilerplate code for using Python statistical libraries into a GUI, allowing users to focus on analyzing data.
Highly reliable output
The output results are the result of running major Python libraries, ensuring reliability for academic use.
AIPowered
LLMAI aids interpretation of results and prevents misuse of statistical methods
Get started with PyStat for free!
Many common statistical analysis methods are available for free, forever.
The Python environment is encapsulated in an exe file.
You can run Python code on your computer without the hassle of setting up a Python environment. There is no need to worry about security as all processing is done within your computer. Using the core libraries used by many Python users, the quality of the output is guaranteed. The analysis is completed entirely through a GUI, but abusolutely it's the same as if you were using Python. You can report it as a result of using Python libraries.
Generative AI supports you.
The OpenAI's latest LLM will explain how to interpret the results, so you can avoid misusing statistical methods.
Transparent licensing policy
Many commercial statistical analysis software products offer pricing for businesses, faculty, and students. However, the distinction between these statuses is unclear and does not reflect the reality of joint research between companies and universities, or collaboration between faculty and students. PyStat offers academic pricing levels for all users.

PyStatBase
PyStatBase covers the most commonly used statistical analysis techniques: tabulation, basic statistics, hypothesis testing, multivariate analysis, graphing, etc. You will be able to master Python statistics in no time.

PyStatPro
In addition to the functions of Free and Base, PyStatPro has enhanced functions such as nonparametric tests, multiple comparison tests, predictive models, and machine learning to meet more advanced needs.

PyStatPremium
PyStatPremium provides all the features of Pystat in addition to the features of Free, Base, and Pro, and can meet all your statistical needs. Especially, time series analysis, survival analysis, and metaanalysis are enhanced.
Comparison Table
Find the right product with the features you need.
Description  Free  Base  Pro  Premium  
AI Asistance  
Automatic Consderation  PyStat will use ChatGPT to analyze the results calculated by each analysis function.  ✓  ✓  ✓  
Basic Statistcs  
Descriptive Statistics  Basic statistics such as the mean, variance, and median can be calculated all at once. Statistics can also be calculated for each group.  ✓  ✓  ✓  ✓ 
Correlation Coefficient  It is possible to perform Pearson productmoment correlation coefficients, rank correlation coefficients, and tests for noncorrelation.  ✓  ✓  ✓  
Intraclass Correlation Coefficient  Intraclass correlation coefficients and 95% confidence intervals can be calculated.  ✓  ✓  
Hypothesis Tests  
Parametric Tests  
Unpaired ttest  Calculate statistics, pvalues, and effect sizes for unpaired ttests.  ✓  ✓  ✓  ✓ 
Welch's ttest  Calculate Welch's ttest statistics, pvalues, and effect sizes.  ✓  ✓  ✓  ✓ 
Paired ttest  Calculate statistics, pvalues, and effect sizes for paired ttests.  ✓  ✓  ✓  ✓ 
Oneway ANOVA  Perform a oneway ANOVA and create an ANOVA table.  ✓  ✓  ✓  ✓ 
Repeated Measures ANOVA  Conduct oneway ANOVA with replicates.  ✓  ✓  
Factorial ANOVA  Perform multiway ANOVA, such as twoway or threeway ANOVA, and create ANOVA tables.  ✓  ✓  ✓  ✓ 
Nonparametric Tests  
Mann–Whitney U test  Calculate the MannWhitney U test statistic, pvalue, and effect size.  ✓  ✓  
BrunnerMunzel test  Calculate the BrunnerMunchel test statistic and pvalue.  ✓  ✓  
Wilcoxon rank sum test  Calculate Wilcoxon signedrank test statistics, pvalues, and effect sizes.  ✓  ✓  
KruskalWallis test  Calculate the KruskalWallis test statistic and pvalue.  ✓  ✓  
Friedman's test  Calculate Friedman test statistics, pvalues, and effect sizes.  ✓  ✓  
Multiple Comparison  
TukeyKramer's test  Calculate the pvalue for the TukeyKramer method.  ✓  ✓  
SteelDwass test  Calculate the pvalue for the SteeleDwas test.  ✓  ✓  
Dunnett's test  Calculate the pvalue for the Dunnett test. *Not available on the macOS version. 
✓  ✓  
Bonferroni correction  Bonferronitype corrections are performed on significance levels and pvalues. Sidak and Holm methods can also be performed.  ✓  ✓  
Checking Normality  Three methods are possible:  Creating a normal QQ plot  ShapiroWilk test  KS test 
✓  ✓  ✓  ✓ 
Test of Homogeneity of Variance  Three test methods are available:  F test  Bartlett test  Levene test 
✓  ✓  
Multivariate Analysis  
Regression  
Multiple Regression  Perform multiple regression analysis to calculate the coefficient of determination, partial regression coefficient, and VIF. It is also possible to evaluate the model and calculate predicted values.  ✓  ✓  ✓  
Logistic Regression Analysis  Performs logistic regression analysis to calculate loglikelihoods, partial regression coefficients, and adjusted odds ratios.  ✓  ✓  ✓  ✓ 
Multinomial Logistic Regression Analysis  Runs a multinomial logistic regression and calculate the loglikelihood and explanatory variable statistics.  ✓  ✓  
Probit Analysis  Performs probit analysis to calculate log likelihood, partial regression coefficients, and marginal effects. Also can evaluate the model and calculate predicted values.  ✓  
Generalized Linear Mixed Model  Analysis can be performed using generalized linear mixed models.  ✓  ✓  
Quantification Theory  
Type Ⅱ  Executes quantification type II to calculate correlation ratios, ranges, and partial correlation coefficients.  ✓  ✓  
Multipul Correspondence Analysis  Multipul Correspondence Analysis is performed to calculate cumulative scores, category scores, and sample scores, and graphs are created.  ✓  ✓  
Discriminant Analysis  Perform discriminant analysis to calculate contribution ratios, perform classification, and create graphs.  ✓  ✓  ✓  
Principal Component Analysis  Perform principal component analysis to obtain contribution ratios, principal component loadings, and create graphs.  ✓  ✓  ✓  
Factor Analysis  Perform factor analysis to generate eigenvalues, factor loadings, and biplots.  ✓  ✓  ✓  
Structured Equation Modeling  Define the model formula and perform structural equation modeling. The results are displayed as a path diagram.  ✓  ✓  
Machine Learning  
Decision Tree  It is possible to perform classification and regression problems using decision trees.  ✓  ✓  ✓  ✓ 
Random Forest  Classification and regression problems can be solved using random forests.  ✓  ✓  
Gradient Boosting Decision Tree  It can perform classification and regression problems using gradient boosting decision tree  ✓  ✓  
Time Series Analysis  
Basic Analysis  
Moving Average  It can perform classification and regression problems using gradient boosting decision trees.  ✓  ✓  ✓  ✓ 
Autocorrelation Coefficient  Calculate the autocorrelation coefficient and partial autocorrelation coefficient and create a correlogram.  ✓  ✓  ✓  ✓ 
Augmented DickeyFuller test  It is possible to perform the ADF test, which is a test for unit root processes.  ✓  ✓  ✓  ✓ 
Models  
ARIMA  Create models and make predictions using the ARIMA model. Parameters can also be calculated automatically.  ✓  ✓  ✓  ✓ 
GARCH  Using the GARCH model, it is possible to create models and calculate volatility and VaR.  ✓  
VAR  Use VAR models to create models, make forecasts, and analyze causality using impulse response functions and Granger causality tests.  ✓  
Prophet  Prophet can be used to make predictions on time series data.  ✓  
Graphs  
Line Chart  Create a line graph.  ✓  ✓  ✓  ✓ 
Scatter Plot  Create scatter and bubble charts.  ✓  ✓  ✓  ✓ 
Scatterplot Matrix  Create a scatter plot matrix for multivariate data.  ✓  ✓  ✓  ✓ 
Histogram  Create a histogram. It is possible to create a histogram by overlaying two data.  ✓  ✓  ✓  
Distribution Plot  Creates four graphs:  Box plot  Violin plot  Swarm plot  Split plot 
✓  ✓  ✓  
Error bar  Create error bars.  ✓  ✓  ✓  ✓ 
Other methods  
Crosstab  Create crosstabulation tables and perform chisquare tests, exact tests, odds ratios, risk ratios, and correspondence analysis.  ✓  ✓  ✓  
Survival Time Analysis  
Survival Curve  It is possible to create survival curves using the KaplanMeier method, and perform logrank tests and generalized Wilcoxon tests.  ✓  
Cox Proportional Hazards Regression  Hazard ratios can be calculated and tested for survival time data.  ✓  
Association Analysis  Association analysis is performed based on various rules. Network diagrams can also be created.  ✓  ✓  
Propensity Score Matching  Based on the propensity scores, greedy matching or optimal matching is performed. It is also possible to check the balance of the matching results.  ✓  
MetaAnalysis  
MetaAnalysis of Proportions  Perform metaanalysis on categorical data. Forest and funnel plots can also be created.  ✓  
MetaAnalysis of means  Perform metaanalysis on continuous data. Forest and funnel plots can also be created.  ✓  
Generalized inverse variance method  Metaanalysis is performed using the generalized inverse variance method. Forest plots and funnel plots can also be created.  ✓ 