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Buchanan Missouri State University Spring 2017 This video covers a very basic introduction to JASP: where to download the program, open.
A comprehensive software solution designed to help both experts and beginners build complex psychological or sociological experiments
What's new in OpenSesame 3.3.5:
- 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.
- Email: info@jasp-stats.org 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.
- Bug fixes and improvements:
- opensesame:
- Updated to 3.3.5
- log.open() does not update var.logfile or list of data files
OpenSesame is a streamlined piece of software created especially for users that want to build psychology-related experiments. In addition, the application is also well-suited for creating complex experiments in fields like neuroscience and experimental economics.
Right off the bat, it should be noted that the utility is designed from the ground up to make it possible for you to use third party devices such as eye trackers, button boxes and EEG equipment.
Enhance the app's capabilities by adding Python code
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Furthermore, since almost everything related to psychology usually involves high-level complexity, it is worth mentioning that OpenSesame enables you to use Python to further enhance the provided possibilities.
For example, in situations in which the app is no longer sufficient, you can customize its core functionality by adding Python codes to your experiments. This is probably the best time to point out that it is a very good idea to take a while and read the instructions and possibly undergo some of the tutorials provided on the developer's website.
Typical installation process and intuitive interface
The app undergoes a typical installation process, after which it can be launched without the need of configuration on your part. The main window is fairly well structured and the interface makes it easy for you to access all its functions with ease.
On the top part of the main window, you can find the app's top toolbar that provides you quick access to some of the main features and commands, on the extreme left there is a compact panel that offers direct access to some of the most commonly used tools and right next to it an Overview panel that displays the structure of your experiment.
Complex and advanced, cross-platform app for psychology-related experiments
In addition to all this, you should also know that OpenSesame is a cross-platform application which means that you can run it just as efficiently on all major operating systems out there, namely Windows, macOS and Linux.
All in all, OpenSesame is a reliable and useful utility that, once you take the time to read all the complex instructions and learn its functions, can help you develop complex psychological experiments using your computer as the primary platform for doing so.
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OpenSesame was reviewed by Vladimir CiobicaOpenSesame 3.3.5
add to watchlistsend us an update- runs on:
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- filename:
- opensesame_3.3.5-py27-win64-1.zip
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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 | – | – |
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
| Blog Post | Video | GIF |
| 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.
| 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 |