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R Statistical Environment
25 Pins
1y
Collection by
Erik
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Standard Deviation
Psychological Science
Reading Data
Standard Deviation
Dataset
Summarize
Argument
Column
Counting
Numbers
How To Use Python
Null Hypothesis
Scatter Plot
Normal Distribution
P Value
Degrees Of Freedom
What Is Need
Syntax
brown forsythe in R via @marsja
Annotating Text
How Do You Find
Data Visualization
Statistics
Summary
via @marsja
Shorts Tutorial
Time Series
How Do I Get
Data Science
via @marsja
Unique Names
Descriptive
Empty
Environment
How to Add an Empty Column to a Dataframe in R (with tibble)
via @marsja
How To Split
Temporary Store
Going To Work
via @marsja
Statistical Analysis
Data Analysis
Psychology Experiments
Writing Scripts
Psychology Student
Learn Programming
Best Blogs
In this post you will find good R resources if you\'re a research psychologist via @marsja
Reading Writing
All Codes
Learn To Read
Excel
Coding
How to Read and Write Stata (.dta) Files in R with Haven
Pc Network
Filing
How to Read and Write Stata (.dta) Files in R with Haven
The Script
No Response
How to Read and Write Stata (.dta) Files in R with Haven
How to Read and Write Stata (.dta) Files in R with Haven
Haven
via @marsja
Central Tendency
Easy Summary Statistics in R usin dplyr()
1 John
R descriptive statistics using tidyverse.
Table of descriptive statistics with R (mean, geometric mean, harmonic mean, and trimmed mean).
Summary statistics calculated using R and the package psych.
Descriptive statistics calculated in R and saved to a latex table.
Variables
Mean value - a common descriptive statistic - calculated in R statistical environment. Here grouped by gender and day (two categorical variables).
How to save summary statistics calculated in R
Summary statistics in R - variance calculated by two groups.
Workbook
R Excel Tutorial: How to Read and Write xlsx files in R -
Cd Binder
Got Map
Script Words
Text Editor
Git
How to Use Binder and R for Reproducible Research - Erik Marsja
Github
In this #RStats Tutorial you will learn how to use R and Binder for Reproducible Research. More specifically, you will learn how to use Git and GitHub, commit your code and set up Binder to get a reproducible computational environment.