Hits: 39

Summarise Data in R – How to determine pearson spearman correlation in R

Determining the correlation between two variables is a common task in data analysis and statistics. Correlation is a measure of the relationship between two variables and it can be used to understand how changes in one variable are related to changes in another variable.

In R, there are two main ways to determine the correlation between two variables: Pearson correlation and Spearman correlation.

Pearson correlation is a measure of the linear relationship between two variables. It ranges from -1 to 1, where -1 represents a perfect negative correlation, 0 represents no correlation, and 1 represents a perfect positive correlation. The Pearson correlation coefficient can be calculated in R using the cor() function.

Spearman correlation is a non-parametric measure of the rank-based correlation between two variables. It also ranges from -1 to 1, where -1 represents a perfect negative correlation, 0 represents no correlation, and 1 represents a perfect positive correlation. The Spearman correlation coefficient can be calculated in R using the cor(x, y, method = “spearman”) function.

In summary, determining the correlation between two variables is a common task in data analysis and statistics. Correlation is a measure of the relationship between two variables and it can be used to understand how changes in one variable are related to changes in another variable. In R, there are two main ways to determine the correlation between two variables: Pearson correlation and Spearman correlation. Pearson correlation is a measure of the linear relationship between two variables and it can be calculated in R using the cor() function. Spearman correlation is a non-parametric measure of the rank-based correlation between two variables and it can be calculated in R using the cor(x, y, method = “spearman”) function.

In this Applied Machine Learning & Data Science Recipe (Jupyter Notebook), the reader will find the practical use of applied machine learning and data science in R programming: How to determine pearson spearman correlation in R.

Summarise Data in R – How to determine pearson spearman correlation in R

Disclaimer: The information and code presented within this recipe/tutorial is only for educational and coaching purposes for beginners and developers. Anyone can practice and apply the recipe/tutorial presented here, but the reader is taking full responsibility for his/her actions. The author (content curator) of this recipe (code / program) has made every effort to ensure the accuracy of the information was correct at time of publication. The author (content curator) does not assume and hereby disclaims any liability to any party for any loss, damage, or disruption caused by errors or omissions, whether such errors or omissions result from accident, negligence, or any other cause. The information presented here could also be found in public knowledge domains.