Correlations and Covariance in R with Example | R Tutorial 4.12 | MarinStatsLectures

Correlations and Covariance in R with Example: Learn how to calculate Pearson's correlation, Spearman's rank correlation, Kendall's rank correlation, and covariance in R (with example). 📝 Find R practice dataset (LungCapData) here: (https://statslectures.com/r-scripts-d... )

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In this R video we will learn how to calculate Pearson's correlation, Spearman's rank correlation, and Kendall's rank correlation, create confidence intervals and hypothesis tests and calculate Covariance in R.
Here we will be using "cor", "cor.test","cov" ,"pairs", method”, functions and arguments in R and more.

Pearson’s correlation is a parametric measure of the linear association between two numeric variables, Spearman’s rank correlation is a non-parametric measure of the monotonic association between two numeric variables, Kendall’s rank correlation is another non-parametric measure of the association based on concordance or discordance of x-y pairs. Covariance is a measure of the joint variability of two random variables.



Table of Content:

0:00:08 When should we use Pearson's correlation in statistics and in research?
0:00:16 When should we use Spearman's rank correlation in statistics and in research?
0:00:24 When should we use kendall's rank correlation in statistics and in research?
0:00:54 how to access the help menu in R statistical software for correlation functions
0:01:05 how to produce a scatterplot in the R programming language to explore the relationship between variables using "plot" function
0:01:39 how to calculate the correlation between variables using the "cor" function in R
0:01:46 how to calculate Pearson's correlation using "method" argument in R
0:02:17 how to calculate Spearman's rank correlation using "method" argument in R
0:02:24 how to calculate kendall's rank correlation in R using "method" argument
0:02:34 how to produce a confidence interval and test the hypothesis for the correlation in R using the "cor.test" function
0:03:21 how to calculate the p-value when there are exact values in dataset using "exact" argument in R
0:03:42 how to change the alternative hypothesis using the "alt" argument in R
0:04:03 how to change the confidence level using the "conf.level" function in R
0:04:13 how to calculate the covariance in R using the "cov" function
0:04:27 how to produce all possible pair-wise plots using the "pairs" function in R
0:04:50 how to produce a "pairs" plot only for some of the variables in the dataset by sub-setting data using square brackets in R
0:05:26 how to produce a correlation matrix in R using the "cor" function and "method" argument
0:05:37 how to deal with categorical variables in the dataset when creating a correlation matrix by subsetting data using square brackets in R
0:06:18 how to produce the covariance matrix using the "cov" function in R

These video tutorials are useful for anyone interested in learning data science and statistics with R programming language using RStudio.


► ► Watch More:

► Intro to Statistics Course: https://bit.ly/2SQOxDH
►Data Science with R Course https://bit.ly/1A1Pixc
►Getting Started with R using RStudio (Series 1): https://bit.ly/2PkTneg
►Graphs and Descriptive Statistics in R using RStudio (Series 2): https://bit.ly/2PkTneg
►Probability distributions in R using RStudio (Series 3): https://bit.ly/2AT3wpI
►Bivariate analysis in R using RStudio (Series 4): https://bit.ly/2SXvcRi
►Linear Regression in R using RStudio (Series 5): https://bit.ly/1iytAtm
►ANOVA Concept and with R using RStudio https://bit.ly/2zBwjgL
►Hypothesis Testing: https://bit.ly/2Ff3J9e
►Linear Regression Concept and with R Lectures https://bit.ly/2z8fXg1

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