In this OpenSesame tutorial we will learn how to use images as stimuli and how to load the trials; including filenames, correct responses, and conditions from a pre-generated CSV file. To follow this tutorial you don’t need to know Python programming. However, we are going to generate the CSV file using a short Python script. This can be done manually, of course. See also this OpenSesame tutorial.
Category: Open Science
In this post you are going to learn how to create a simple experiment using the free experiment building software OpenSesame. As I have previously written about, OpenSesame, is an application, based on Python, for creating Psychology, Neuroscience, and Economics experiments. It offers a nice and easy to use interface. In this interface you can drag-and-drop different objects. This means that you don’t have to know any Python programming at all to create an experiment. If you need to know how to use images as stimuli you can see this OpenSesame Tutorial.
PsychoPy, as I have previously written about (e.g., Free and Useful Software and PsychoPy tutorial) is really a great Python tool for creating Psychology experiments. You can write Python code by either using “code view” or import the package in your favourite IDE. Furthermore, you can use the builder mode and just drag and drop different items and PsychoPy will create a Python Script for you.
If need inline scripts (in Python, of course) can be inserted. That is, you can combine drag-and-drop building with some coding.
In this post I have collected some tutorial videos that can be useful for someone unfamiliar with PsychoPy.
Descriptive Statistics After data collection, most Psychology researchers use different ways to summarise the data. In this tutorial we will learn how to do descriptive…
The aim of this post is to show you why you, as a psychology student or researcher (or any other kind researcher or student) should learn to program. The post is structured as follows. First I start with discussing why you should learn programming and then give some examples when programming skills are useful. I continue to suggest two programming languages that I think all Psychology students and researchers should learn.
Good resources for learning R as a Psychologist are hard to find. By that I mean that there are so many great sites and blogs around the internet to learn R. Thus, it may be hard to find learning resources that targets Psychology researchers.
Recently I wrote about 4 good R books targeted for Psychology students and researchers (i.e., R books for Psychologists). There are, however, of course other good resources for Psychological researchers to learn R programming.
Therefore, this post will list some of the best blogs and sites to learn R. The post will be divided into two categories; general and Psychology focused R sites and blogs. For those who are not familiar with R I will start with a brief introduction on what R is (if you know R already; click here to skip to the links).
What is R?
R is a free and open source programming language and environment. Data analysis in R is carried out by writing scripts and functions. Finally, R is a complete, interactive, and object-oriented language.
In R statistical environment you are able to carry out a variety of statistical and graphical techniques. For instance, linear and nonlinear modeling, classical statistical tests, time-series analysis, classification, and many more can be carried using both frequentist and Bayesian paradigms.
You may want to start with R commander. It provides a menu which may make learning R a bit easier at the beginning. R can be downloaded here: The Comprehensive R Archive Network.
R resources
One of the main things that I like with R is the broad and helpful community. This also means that there are many good resources for learning the language.
I recently wrote a post on the RStudio like Python IDE Rodeo (RStudio-like Python IDEs – Rodeo and Spyder). In that post, I installed and…
In this post I will discuss two Python Integrated Development Environments (IDE); Rodeo and Spyder. Both Python IDEs might be useful for researchers used to work with R and RStudio (a very good and popular IDE for R) because they offer similar functionalities and graphical interfaces as RStudio. That is, Rodeo and Spyder can both be seen as the RStudio for Python.
I recently asked which programming language I should learn next year (i.e., 2016). In this post I will evaluate the alternatives that I have by asking the question in different places around the internet. The post will end with the choice I made and how to install the language
To summarize my earlier post, I mainly use programming for creating Psychology experiments and, thus, need a powerful language. Furthermore, in Psychological experiments stimuli are typically being presented (e.g., sounds, images, text, or video). Responses need to be collected from the keyboard, mouse and specially built equipment (e.g., via USB; Arduino). For some experiments timing of the presentation and collection of responses might be significant. The language should, of course, be free, open source, and work on a computer running Windows, Linux, and OS-X. However, mobile platforms such as Smartphones and Tablets might also be interesting in the future. Note that all languages considered are more or less general purpose languages and might, therefore, be attractive to anyone that want to extend their stack and learn a new programming language 2016.
One of the most valuable answers I got was that I should look for a functional language.