Jasp Software Mac

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.

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Jasp Software Mac Os

Jasp Software MacJasp tutorials

The 0.6.6 version of JASP for Mac is available as a free download on our software library. The actual developer of this free software for Mac is JASP. The size of the latest downloadable setup file is 107.9 MB. This Mac download was checked by our built-in antivirus and was rated as virus free. JASP should run on Apple Silicon #1098 opened Dec 16, 2020 by JorisGoosen JASP crashes on open after MacOSX install waiting for requester.

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).


  1. JASP is installed by downloading and double clicking the.dmg file, and dragging the JASP icon to the Applications folder. This places JASP in your applications folder. It might warn you that it “is a file downloaded from the internet” and it is right, but you can just click through that and everything should work fine.
  2. 0.13 JASP 0.13 (Windows) JASP 0.13 (Windows 32 Bit) JASP 0.13 (Windows 64 Bit Pre-Installed) JASP 0.13 (Windows 32 Bit Pre-Installed) JASP 0.13 (MacOS Catalina and above) JASP 0.13 (MacOS High Sierra and Mojave) 0.12.2 JASP 0.12.2 (Windows) JASP 0.12.2 Continue reading →.

Jasp Software Analysis

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

Jasp Software Mac Download

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)–

Jasp Install


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 Software Download

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

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