In this category you will find posts that are related to programming and should be interesting for psychologists, cognitive scientists, and neuroscientists. Well, almost every researcher would probably find some of the information useful at some time!
Every research psychologist, cognitive scientist, and neuroscientist, should know how to program.. Knowing how to program and write scripts will make many of a researchers everyday tasks much easier. For instance, instead of going through line after line of raw data you can write a Python script that runs through each cell in each column. Furthermore, you get the possibility to use more advanced, and cutting edge, statistical techniques by using R statistical programming environment.
Another example might be to create experiments using PsychoPy (either by coding using Python or using the drag-and-drop interface) and the cheap and open-source Arduino microcontroller. Also, coding is fun and relaxing!
In this Python data analysis tutorial, you will learn how to perform a paired sample t-test in Python. First, you will learn about this type of t-test (e.g. when to use it, the assumptions of the test). Second, you will learn how to check whether your data follow the assumptions and what you can do […]
How to use Python to Perform a Paired Sample T-test Read More »
In this tutorial, related to data analysis in Python, you will learn how to deal with your data when it is not following the normal distribution. One way to deal with non-normal data is to transform your data. In this post, you will learn how to carry out Box-Cox, square root, and log transformation in
How to use Square Root, log, & Box-Cox Transformation in Python Read More »
In this post, you will learn what you need to add new columns to your dataframe in R. We will work both with base R and some of the great Tidyverse packages.
How to Add a Column to a Dataframe in R with tibble & dplyr Read More »
In this R tutorial, you will learn how to rename factor levels in R using 1) levels and 2)
How to Rename Factor Levels in R using levels() and dplyr Read More »
In this R tutorial, you will learn how to remove duplicate rows and columns from a data frame. We will use the duplicated() and unique() functions from base R. Furthermore, we will use the distinct() function from the dplyr package.
How to Remove Duplicates in R – Rows and Columns (dplyr) Read More »
In this Python tutorial, you will learn how to 1) perform Bartlett’s Test, and 2) Levene’s Test. Both are tests that are testing the assumption of equal variances. Equality of variances (also known as homogeneity of variance, and homoscedasticity) in population samples is assumed in commonly used comparison of means tests, such as Student’s t-test
Levene’s & Bartlett’s Test of Equality (Homogeneity) of Variance in Python Read More »
In this R tutorial, you will learn how to add a column to a dataframe based on other columns.
R: Add a Column to Dataframe Based on Other Columns with dplyr Read More »
Are you an R enthusiast struggling to understand %in% in R and how it can be used in your data analysis and manipulation tasks? Look no further! This post will explore the ins and outs of the %in% operator. We’ll start with the basics, including what %in% means in R and how it differs from
How to use %in% in R: 8 Example Uses of the Operator Read More »
In this hands on tutorial, you will learn how to transpose a matrix and a dataframe in R statistical programming environment.
How to Transpose a Dataframe or Matrix in R with the t() Function Read More »
In this Pandas tutorial, you will learn how to count occurrences in column using the value_counts() method.
Pandas Count Occurrences in Column – i.e. Unique Values Read More »
