# 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!

## 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!

## Binning in R: Create Bins of Continuous Variables

three methods to create bins in R

## How to Create a Word Cloud in R

Dive into the fascinating world of data visualization with word cloud in R! Discover how to craft captivating word clouds, unlocking valuable insights from your text data. This comprehensive guide will take you step-by-step, allowing you to create visually stunning representations of word frequencies and explore the power of R’s wordcloud package.

## Coefficient of Variation in R

By exploring the correlation of coefficients in R, you can identify patterns and dependencies among variables, enhancing your understanding of data relationships.

## Find the Highest Value in Dictionary in Python

ooking to find the highest value in a dictionary in Python? Discover different methods to achieve this task efficiently. Explore built-in functions, sorting, collections, and Pandas. Learn the pros and cons of each approach, and determine the best method for your specific needs.

## Correlation in R: Coefficients, Visualizations, & Matrix Analysis

Discover the power of correlation in R as you find hidden relationships in your data. From calculating correlation coefficients to visualizing patterns, dive into the world of data analysis and uncover the insights that lie within. Get ready to unlock the secrets of correlation in R.

## ggplot Center Title: A Guide to Perfectly Aligned Titles in Your Plots

In this R tutorial, you will discover how to use ggplot to center the title effectively. Centering the title is crucial to creating visually appealing plots, and, e.g., enabling better communication of insights. We will explore examples from hearing science and psychology to demonstrate the significance of centering titles in ggplot2 objects.

## How to Randomly Select Rows in R – Sample from Dataframe

How to randomly select rows in R? Learn the sample() and slice_sample() functions to take random samples from dataframes. Explore practical examples and synthetic datasets for hands-on learning. Enhance your data analysis skills and unlock new possibilities with random row selection in R.

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