JASP is an open-source statistics program that conveniently analyze data, present and publish valid results in an intuitive manner with the help of this highly efficient utility that allows both classical and Bayesian analyses.
About JASP
Created by a team of dedicated academics from the University of Amsterdam, JASP Probably the first thing you should know about this application is the fact that it's capable of performing most types of both Frequentist and Bayesian analysis, with support for ANOVA, ANCOVA, Binomial Test, Contingency Tables, Correlation: Person, Spearman, Kendal, Linear Regression, Log-Linear Regression, and T-Test, as well as many others.JASP Main Features
How to use JASP to perform an Analysis of Variance. JASP can be freely downloaded at www.jasp-stats.org. JASP is available for Windows, Mac, and Linux. The website also contains a demo of JASP in action. Where can I fi nd JASP? JASP off ers many advantages over popular competing packages. Compared to commercial packages such as SPSS, JASP is free, open-source, actively developed,.
- JASP is an open-source project supported by the University of Amsterdam.- JASP has an intuitive interface that was designed with the user in mind.
- JASP offers standard analysis procedures in both their classical and Bayesian form.
- Frequentist and Bayesian analyses
- Dynamic update of all results
- Spreadsheet layout and an intuitive drag-and-drop interface
- Progressive disclosure for increased understanding
- Annotated output for communicating your results
- Integrated with The Open Science Framework (OSF)
- Support for APA format (copy graphs and tables directly into Word)
Getting Started
Before you do anything else, we strongly recommend that you visit the JASP YouTube channel and the ‘How to Use JASP’ page, where you can find introductory blog posts and videos. Below is some general information about JASP that may be helpful as you analyze your first data set. We invite you to post any remaining questions on the JASP forum or on the JASP GitHub page.Data Sets
JASP comes with a series of example data sets that can be accessed from the ‘File → Open’ tab. Selecting an example data set will open it in JASP for inspection, editing, and analysis. In addition to its own .jasp format, JASP can open data sets in formats such as .csv (comma-separated values), .txt (plain text), .sav (IBM’s SPSS), and .ods (OpenDocument Spreadsheet). Note that all files need to have a header row that contains names for each of the columns or variables. Missing values can either just be missing (i.e., an empty cell) or be denoted by “Nan”, “.” (period), or ” ” (space). When opening a file, JASP makes a best guess to assign variable types, as explained below.
Variable Types
JASP distinguishes four variable types:
Nominal Text
Nominal
Ordinal
Continuous
Nominal Text variables are categorical variables without numeric value (i.e., strings). An example might be a variable called “Favorite Dutch Soccer Club”, with three possible entries: “Ajax”, “PSV”, and “Feyenoord”.
Nominal variables are categorical variables that are represented by numeric values. For example, a variable “Group” may have levels “1” and “2”. Even though these are numbers, they do not imply an order, and the distance between them is not meaningful.
Ordinal variables are categorical variables with an inherent order. An example might be a Likert preference rating scale with levels 1 (“hate it”), 2 (“yuk”), 3 (“meh”), 4 (“cool“), and 5 (“in love”). Note that the distance between the numbers is not meaningful. JASP assumes that all ordinal variables have been assigned numeric values.
Continuous variables are variables with values that allow a meaningful comparison of distance. Examples include income, IQ, or weight. Variable types in JASP are often enforced; for instance, you are not allowed to conduct a t-test when your dependent measure is nominal.
Variable Type Assignment
When loading a file, JASP automatically assigns variable types according to the following rules: If the variable contains only integer values and missing values, and contains fewer than 25 unique values, then it is assigned a variable type of Nominal. If the variable contains only integer values, floating point numbers, missing values, and +/- infinities, then it is assigned a type of Continuous. Otherwise the variable is assigned a type of Nominal Text.
Changing Variable Types
If need be, the automatic variable type assignment can be corrected manually. When you click the icon representing the variable type at the top of the column, a menu is produced that allows you to choose a different variable type. Values incompatible with the new variable type are automatically converted to missing values. But be careful! JASP presently does not feature an “undo” facility, so if you change a Nominal Text column full of text values to a type such as Continuous, the entire column will be converted to missing values. At present, there is no way to undo this action and it will be necessary to reload the data set. Analyses
Having loaded a data set, it is now possible to run analyses. After selecting an analysis from the ribbon along the top you will see input options for that analysis in the left panel, and the associated output in the right panel. As the input options are specified, the analysis results automatically update, providing immediate feedback.
When the analysis has been specified to your satisfaction, you can return to the data view by clicking the “OK” button. You can return to an earlier analysis simply by clicking on the output of interest. This brings up the options that were used to generate that analysis, and allows you to make adjustments or additions. There is much more to say about JASP: its ability to annotate output, to interact with the Open Science Framework, to conduct sophisticated analyses using modules, to save APA tables and publication-ready figures, and much more. These options are discussed in our YouTube videos. We are also in the process of writing a JASP manual.
JASP FAQ
Which file formats does JASP support?JASP can open the following file types:
- .csv (any text files with comma/semicolon/colon/tab separated columns)
- .sav (SPSS files)
- .ods (Open Document Spreadsheet format, that is used by software such as OpenOffice, LibreOffice and Excel)
What does JASP stand for? - In recognition of Bayesian pioneer Sir Harold Jeffreys, JASP stands for Jeffreys’s Amazing Statistics Program.
What programming language is JASP written in?
The JASP application is written in C++, using the Qt toolkit. The analyses themselves are written in either R or C++. The display layer (where the tables are rendered) is written in javascript, and is built on top of jQuery UI and webkit.
If JASP uses R for doing analyses, is it possible to export the R code which was used for that analysis?
Not without considerable effort. When JASP was first developed, our focus was on producing a GUI that would retain the desirable properties of syntax (such as reproducibility) without requiring or producing syntax itself. We believe we did a decent job on the GUI, but we recognize that some users still like easy access to the R code. We hope to add this functionality in a future version.
JASP for MAC
Download JASP 0.10.0.0 for MAC here!JASP for Linux
JASP is now available for virtually all Linux distributions through the widely available flatpak. This is most likely already installed on your distribution and otherwise can be easily acquired through your package manager. After you have installed flatpak enter the following command into a terminal:
It might not be automatically added to the application menu in some cases (ubuntu for instance) and there you can start JASP by running:
After you have installed JASP from flatpak any new releases/updates can be installed by running:
Should the flatpak install fail to work for some reason you can always contact us for support or you can try to build JASP from source.
Conclusion
To conclude JASP works on Windows operating system and can be easily downloaded using the below download link according to Freeware license. JASP download file is only 252 MB in size.JASP was filed under the Science and Engineering category and was reviewed in softlookup.com and receive 5/5 Score.
JASP has been tested by our team against viruses, spyware, adware, trojan, backdoors and was found to be 100% clean. We will recheck JASP when updated to assure that it remains clean.
JASP user Review
Please review JASP application and submit your comments below. We will collect all comments in an effort to determine whether the JASP software is reliable, perform as expected and deliver the promised features and functionalities.Popularity 10/10 - Downloads - 63 - Score - 5/5
| Category: | Science and Engineering |
| Publisher: | The JASP Team |
| Last Updated: | 06/11/2019 |
| Requirements: | Windows 10 64 bit / Windows 10 / Windows 8 64 bit / Windows 8 / Windows 7 64 bit / Windows 7 / Windows Vista 64 bit / Windows Vista |
| License: | Freeware |
| Operating system: | Windows |
| Hits: | 890 |
| File size: | 252 MB |
| Price: | Not specified |
| Leave A comment | |
| Name: * | E-Mail: * |
| Comment: * | |
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 Post | Video | GIF | |
| 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 | – | – |
Jasp Fur Machine
Bayesian Analyses
| Blog Post | Video | GIF | |
| 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 Post | Video | GIF | |
| 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
Jasp Mac Review
| Blog Post | Video | GIF |
| Compute Columns | – | |
| Data & Label Editing | ||
| Exact P-Values | – | |
| Filtering | – | |
| OSF support | – | |
| Test Interval-Null Hypotheses | – | – |
| VS-MPR | – |
Jasp Machine Learning
Tips & Tricks
Jasp For Mac
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 For Mac
| 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 |