Features

See the list below for all the modules and its analyses currently available in JASP. To find out how to perform certain analyses or how to use certain features, visit the How to Use JASP section. If you think that JASP is missing an important analysis, you can issue a feature request. To see how JASP compares to SPSS, have a look at this overview made by Thomas Langkamp.

JASP currently reads the following formats: .csv, .txt, .tsv, .ods, .dta, .sav, .zsav, .por, .sas7bdat, .sas7bcat, .xpt and of course the .jasp format.

Modules
Frequentist

Bayesian

Descriptives

    Descriptives Statistics
    Raincloud Plots
    Time Series Descriptives
    Flexplot

T-Tests

    Classical

      Independent Samples T-Test
      Paired Samples T-Test
      One Sample T-Test

    Bayesian

      Independent Samples T-Test
      Paired Samples T-Test
      One Sample T-Test

ANOVA

    Classical

      ANOVA
      Repeated Measures ANOVA
      ANCOVA
      MANOVA

    Bayesian

      ANOVA
      Repeated Measures ANOVA
      ANCOVA

Mixed Models

    Classical

      Linear Mixed Models
      Generalized Linear Mixed Models

    Bayesian

      Linear Mixed Models
      Generalized Linear Mixed Models

Regression

    Classical

      Correlation
      Linear Regression
      Logistic Regression
      Generalized Linear Model

    Bayesian

      Correlation
      Linear Regression
      Logistic Regression

Frequencies

    Classical

      Binomial Test
      Multinomial Test
      Contingency Tables
      Log-Linear Regression

    Bayesian

      Binomial Test
      A/B Test
      Multinomial Test
      Informed Multinomial Test
      Informed Multi-Binomial Test
      Contingency Tables
      Log-Linear Regression

Factor

    Principal Component Analysis
    Exploratory Factor Analysis
    Confirmatory Factor Analysis

Acceptance Sampling

Audit

    Workflow

      Sampling Workflow
      Bayesian Sampling Workflow

    Other

      True Value Estimation

Bain

    T-Tests

      Welch’s T-Test
      Paired Samples T-Test
      One Sample T-Test

    Regression

      Linear Regression
      Structure Equation Modeling

BSTS

Circular Statistics

Cochrane Meta-Analyses

    Classical

      Continuous Outcomes
      Dichotomous Outcomes

    Bayesian

      Continuous Outcomes
      Dichotomous Outcomes

Distributions

    Continuous

      Normal
      Skew normal
      Generalized normal
      Scaled, shifted Student’s t
      Noncentral t
      Skew t
      Skewed generalized t
      F-Distribution
      Chi-squared
      Uniform
      Beta
      Stretched beta
      Beta prime
      Gamma
      Inverse gamma
      Exponential
      Laplace
      Log-normal
      Logistic
      Log-logistic
      Pareto
      Amoroso
      Fréchet
      Gumbel
      Gompertz
      Triangular
      Wald (inverse Gaussian)
      Weibull
      Mixture of normal and normal
      Mixture of normal and uniform

    Discrete

      Bernouilli
      Binomial
      Beta-binomial
      Poisson
      Negative binomial
      Zero-inflated Poisson
      Zero-inflated negative binomial
      Geometric
      Hypergeometric

Equivalence T-Tests

    Classical

      Independent Samples T-Test
      Paired Samples T-Test
      One Sample T-Test

    Bayesian

      Independent Samples T-Test
      Paired Samples T-Test
      One Sample T-Test

JAGS

Learn Bayes

    Counts

      Binomial Estimation
      Binomial Testing

Learn Stats

    Normal Distribution
    Binomial Distribution
    Central Limit Theorem
    Standard Error
    Descriptive Statistics
    Sample Variability
    P Values
    Confidence Intervals
    Effect Sizes
    Statistical Test Decision Tree

Machine Learning

    Regression

      Boosting
      Decision Tree
      K-Nearest Neighbors
      Neural Network
      Random Forest
      Regularized Linear
      Support Vector Machine

    Classification

      Boosting
      Decision Tree
      K-Nearest Neighbors
      Linear Discriminant
      Naive Bayes
      Neural Network
      Random Forest
      Regularized Linear
      Support Vector Machine

    Clustering

      Density-Based
      Fuzzy C-Means
      Hierarchical
      Neigborhood-Based
      Random Forest

Meta-Analysis

    Classical

      Meta-Analysis
      Prediction Model Performance
      WAAP-WLS
      PET-PEESE
      Selection Models

    Bayesian

      Meta-Analysis
      Penalized Meta-Analysis
      Prediction Model Performance
      Robust Bayesian Meta-Analysis

Network

    Frequentist Network
    Bayesian Network

Power

Predictive Analytics

    Predictive Analytics
    Multivariate Binomial Control

Process

Prophet

Quality Control

    Measurement Systems Analysis

      Type 1 Instrument Capability
      Linearity Study
      Type 2 and 3 Gauge r&R (manual/automatic equipment)
      Gauge r&R (non-replicable measurements)
      Attributes Agreement Analysis
      Test-retest (Range method)

    Control Charts

      Variables Charts for Subgroups
      Variables Charts for Individuals
      Control Charts for Attributes
      Time Weighted Charts

    DOE

      Factorial Design
      Response Surface Design
      Define Custom Design

Reliability

    Classical

      Unidimensional Reliability
      Intraclass Correlation
      Rater Agreement
      Bland-Altman Plots

Robust T-Tests

    Bayesian Model-Averaged T-Test

Structural Equation Modeling (SEM)

    Structural Equation Modeling
    Mediation Analysis
    MMIC Model
    Latent Growth
    Partial Least Squares

Survival

    Non-parametric

Time Series

    Descriptives
    Stationarity
    ARIMA
    Spectral Analysis

Summary Statistics

    T-Tests

      Bayesian Independent Samples T-Test
      Bayesian Paired Samples T-Test
      Bayesian One Sample T-Test

    Regression

      Bayesian Correlation
      Bayesian Linear Regression

Visual Modeling

    Flexplot
    Linear Modeling
    Mixed Modeling
    Generalized Linear Modeling