Programming

Programming related posts

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!

Fisher’s Exact Test in R: How to Interpret & do Post Hoc Analysis

Unlock the power of Fisher’s Exact Test in R and find associations in your categorical data. Dive into interpretation, post-hoc analysis, and data visualization. Discover how to go beyond statistics and turn insights into actions.

Cronbach’s Alpha in R: How to Assess Internal Consistency

Learn to calculate Cronbach’s Alpha in R for assessing internal consistency. Explore manual methods and convenient packages like psych and performance.

Cross-Tabulation in R: Creating & Interpreting Contingency Tables

Cross-tabulation in R: Explore diverse methods for analyzing categorical data. Learn basic and advanced techniques using functions like table(), dplyr, and sjPlot. Enhance your data analysis skills now!

How to Sum Rows in R: Master Summing Specific Rows with dplyr

Explore how to sum rows in R using dplyr’s powerful functions and enhance your data analysis. Sum across specific rows and based on conditions.

How to Check if a File is Empty in R: Practical Examples

In this post, you will learn how to efficiently determine if a file is empty in R using the file.info() and file.size() functions. We will explore practical examples and scenarios, including reading multiple files. Mastering these techniques empowers streamlined file validation for effective data processing and analysis.

Modulo in R: Practical Example using the %% Operator

Unlock the potential of Modulo in R with practical applications. Explore data segmentation, odd/even checks, day filtering, and optimized iterations for streamlined coding efficiency.

Python Check if File is Empty: Data Integrity with OS Module

Learn how to use Python to check if a file is empty. Here we use the os, glob, zipfile, and rarfile modules to check if 1) a file is empty, 2) many files are empty, and 3) files contained in Zip and Rar files are empty.

Check R Version in RStudio: A Quick and Simple Tutorial

Learn how to check the R version in RStudio and ensure reproducibility. Discover the best method for compatibility and smooth data analysis. Follow simple steps for quick access to version details.

Z Test in R: A Tutorial on One Sample & Two Sample Z Tests

Z test in R is a crucial statistical tool for hypothesis testing. This comprehensive guide covers one-sample and two-sample Z tests, providing practical examples utilizing base R and the BSDA package.

Coefficient of Variation in Python with Pandas & NumPy

Discover the Coefficient of Variation in Python using NumPy and Pandas. Pearn to find data variability in your data effortlessly!

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