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.
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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!
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.
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Correlation in R: Coefficients, Visualizations, & Matrix Analysis
Discover the power of correlation in R as you unravel 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.
Correlation in R: Coefficients, Visualizations, & Matrix Analysis Read More »
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.
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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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Extract P-Values from lm() in R: Empower Your Data Analysis
In this blog post, we will learn how to extract P-values from the regression models in R. We will explore the process of fitting a regression model, and then dive into the methods of extracting P-values using the lm() function. Additionally, we will demonstrate how to extract P-values from all predictors and leverage the tidy() function for a tidy output. Unlock the power of statistical inference with the ability to extract P-values from lm() in R.
Extract P-Values from lm() in R: Empower Your Data Analysis Read More »
Master or in R: A Comprehensive Guide to the Operator
Unlock the potential of or in R! Explore advanced data manipulation techniques and learn how to filter, select, mutate, and summarize data based on multiple conditions. Boost your coding skills and streamline your data analysis workflows with ease.
Master or in R: A Comprehensive Guide to the Operator Read More »
Update R: Keeping Your RStudio Environment Up-to-Date
Keeping your software tools up-to-date is essential for a seamless and efficient workflow, and the R programming language is no exception. In this blog post, we will explore the importance of updating R, discuss the circumstances that may necessitate an update, address the possibility of updating R within RStudio, and explore different methods for upgrading
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Mastering SST & SSE in R: A Complete Guide for Analysts
Learn to calculate and interpret SSE/SSR and SST in R. Understand their significance, generate fake data, fit a linear model, and calculate SST and SSR using different methods, including ANOVA. Gain insights into evaluating model performance and enhance your statistical analysis skills. A comprehensive guide for data analysts and researchers.
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Report Correlation in APA Style using R: Text & Tables
In this post, you will learn how to report correlation according to APA. Adhering to APA (American Psychological Association) guidelines is crucial when reporting correlation analysis in academic research. Whether you are conducting research in psychology, cognitive hearing science, or cognitive science, APA style is often required by journals and conferences. This post will provide
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