Jasp Logiciel Mac



Jasp Logiciel Mac

JASP is a free and open-source program for statistical analysis supported by the University of Amsterdam. It is designed to be easy to use, and familiar to users of SPSS.It offers standard analysis procedures in both their classical and Bayesian form. JASP generally produces APA style results tables and plots to ease publication. It promotes open science by integration with the Open Science. JASP aims to be a complete statistical package for both Bayesian and Frequentist statistical methods, that is easy to use and familiar to users of SPSS. JASP User Guide. Guide to Building JASP. The JASP Guide for Implementing Analyses in R. Guide to Adding Analyses. Guide to creating a. JASP stands for Jeffreys’ Amazing Statistics Program, a nod to the Bayesian statistician, Sir Harold Jeffreys. It is available for Windows, Mac, Linux, and there is even a cloud version. One of JASP’s key features is its emphasis on Bayesian analysis. Mac MCR 2019b (9.7) posted by Alfonso Nieto-Castanon on Feb 11, 2020 conn: files for standalone installation on Mac/macOS (without Matlab) release conn19bmaci64.zip posted by Alfonso Nieto-Castanon on Feb 11, 2020.

Welcome to the JASP Tutorial section. Below you can find all the analyses and functions available in JASP, accompanied by explanatory media like blog posts, videos and animated GIF-files.

Click on the JASP-logo to go to a blog post, on the play-button to go to the video on Youtube, or the GIF-button to go to the animated GIF-file. We’re working hard to complete this list of tutorials. To request a tutorial for a specific analysis procedure, please send an email to info@jasp-stats.org and we will prioritize accordingly.

NB. For feature requests, for help installing JASP, or for bug reports: please post your issue on our GitHub page so the JASP team can assist you efficiently (for details see this blog post).


Frequentist Analyses

Blog PostVideoGIF
ANCOVA–
ANOVA–
Binomial Test–––
Confirmatory Factor Analysis––
Contingency Tables––
Correlation–
Descriptive Statistics–
Exploratory Factor Analysis––
Generalized Linear Mixed Models–––
Hierarchical Regression
Independent Samples T-Test
Linear Mixed Models––
Linear Regression–
Logistic Regression–
Log-Linear Regression–––
MANOVA––
Mediation Analysis––
Multinomial Test and Chi-Square Test
Nonparametric tests––
One Sample T-Test
Paired Samples T-Test––
Principal Component Analysis–––
Repeated Measures ANOVA–
Selection Models––
Structural Equation Modeling––


Bayesian Analyses

Blog PostVideoGIF
A/B Test–––
ANCOVA–––
ANOVA––
Binomial Test––
Contingency Tables–––
Correlation–
Generalized Linear Mixed Models–––
Independent Samples T-Test–––
Linear Mixed Models–––
Linear Regression––
Log-Linear Regression–––
Multinomial Test––
One Sample T-Test–––
Paired Samples T-Test––
Repeated Measures ANOVA–––
Robust Bayesian Meta-Analysis––


Modules

Blog PostVideoGIF
Audit–
Bain–––
Distributions–
Equivalence T-Tests (Beta)–––
JAGS–
Learn Bayes––
Machine Learning–
Meta-Analysis
Network
R (Beta)––
Reliability–
Structural Equation Modeling (SEM)–––
Summary Stats–
Visual Modeling (Beta)–


Functions

Blog PostVideoGIF
Compute Columns–
Data & Label Editing
Exact P-Values–
Filtering–
OSF support–
Test Interval-Null Hypotheses––
VS-MPR–


Tips & Tricks

Below you can find a list of small features as well as tips and tricks in JASP, explained with a simple animated GIF or video. Click on the icon to get to the file.

Jasp Logiciel Mac Gratuit

How to…
Add a new module
Add confidence intervals for effect sizes
Arrange analyses in desired order
Change a variable type
Change the default language
Cite and reference in APA Style
Copy tables directly into your word processor
Copy tables in LaTeX format
Export results to HTML
Load a data set from the JASP Data Library
Make your plots have a transparent / white background
Resize the data view
Save plots as images
Save plots as PowerPoint file (.pptx)
Search for variables by typing the variable name
Select dark theme
Tell JASP which values in your dataset are NA values
View a help file
Write annotations in the output