## Mann Whitney U Test in R: A Comprehensive Guide

Mann whitney u test in R with ggstatsplot

Mann Whitney U Test in R: A Comprehensive Guide Read More »

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!

Mann whitney u test in R with ggstatsplot

Mann Whitney U Test in R: A Comprehensive Guide Read More »

Sometimes, when we use data frames in R, we need to remove rows with specific values. For example, we might want to exclude rows that have missing values, outliers, or errors. Or we might want to subset our data based on some criteria, such as a range of values, a category, or a pattern. In

R: Remove Rows with Certain Values using dplyr Read More »

Here you will learn by examples how to use Pandas to calculate cumulative sum by group.

Pandas: Cumulative Sum by Group Read More »

Discover effective methods for removing specific rows in R using both base functions and dplyr. Improve your data manipulation skills and streamline your analysis process. Explore examples and enhance your coding proficiency.

Remove Specific Row in R: How to & Examples with dplyr Read More »

Learn all you need about variance calculation in R with base R and dplyr. From single-column insights to multi-variable analyses, this tutorial equips you for robust data exploration. Discover efficiency with dplyr’s simplicity or opt for the reliability of base R. Your journey to mastering variance starts here.

Variance in R: How to Find & Calculate Read More »

Discover the four simple steps to change R version in RStudio effortlessly. Navigate to Tools, click on Global Options, choose the specific R version needed, and restart RStudio. Check your R version with ease.

Change R Version in RStudio: A Quick How-To Read More »

Master techniques to disable scientific notation in R. This blogpost guides you through practical methods, empowering precise and readable data analysis. Say goodbye to default settings and take control.

Turn Off Scientific Notation in R Read More »

In data analysis using R, converting character columns to factor is common. Character columns often contain categorical data, and converting them to factors enables R to interpret and analyze the data more effectively. Factors represent categorical variables with distinct levels, aiding in statistical modeling (e.g., ANOVA, MANOVA) and visualization. Data type conversion is a fundamental

Convert All Character Columns to Factor in R: A Guide Read More »

Dive into R’s correlation matrix creation, seamlessly transitioning between base R and the corrr package. Learn to visualize correlations, save APA 7 tables, and discover the pros and cons of each method. Empower your data analysis journey with this comprehensive guide.

Correlation Matrix in R: A Hands-On Guide for Practical Analysis Read More »

Discover versatile methods to convert multiple columns to numeric in R. From base R’s simplicity to dplyr’s efficiency, learn essential techniques. Enhance your data manipulation skills and tackle real-world challenges with confidence. Dive into this comprehensive guide and elevate your R programming expertise.

Convert Multiple Columns to Numeric in R with dplyr Read More »