RSQ
TheRSQ
function returns the square of the Pearson productmoment correlation coefficient, which is a measure of the correlation between two sets of data. This function is commonly used in statistical analysis to determine the strength of a linear relationship between two variables.
 How to use
RSQ
formula?  Examples of using
RSQ
formula RSQ
formula not working? Similar formulas to
RSQ
Usage
Use the RSQ
formula with the syntax shown below, it has 2 required parameters:
 data_y (required):
The range or array containing the dependent variable data.  data_x (required):
The range or array containing the independent variable data.
Examples
Here are a few example use cases that explain how to use theRSQ
formula in Google Sheets.
Calculating correlation between two variables
By using the RSQ
function, you can quickly calculate the correlation coefficient between two sets of data. This can help you determine if there is a strong positive or negative relationship between the variables.
Assessing linear regression models
The RSQ
function can be used to assess the goodness of fit of a linear regression model. By comparing the calculated correlation coefficient to the expected value, you can determine how well the model fits the data.
Comparing data sets
If you have two data sets that are related, you can use the RSQ
function to determine how closely they are correlated. This can help you identify patterns or trends in the data.
Common Mistakes
RSQ
not working? Here are some common mistakes people make when using the RSQ
Google Sheets Formula:
Using inconsistent data ranges
Make sure that the two data ranges have the same number of rows and columns, and that they are aligned properly. If the data ranges are not consistent, the RSQ
function will return an error.
Forgetting to enclose the data ranges in parentheses
Remember to enclose the data ranges in parentheses, separated by a comma. If you forget to do this, the RSQ
function will return an error.
Related Formulas
The following functions are similar to RSQ
or are often used with it in a formula:

CORREL
The
CORREL
formula returns the correlation coefficient between two sets of data. This coefficient represents the strength of the linear relationship between the two sets of data, with values ranging from 1 (perfect negative correlation) to 1 (perfect positive correlation). 
PEARSON
The
PEARSON
function calculates the correlation coefficient between two sets of data points,data_y
anddata_x
. This coefficient indicates how closely related the two sets of data are. A high correlation coefficient indicates a strong positive correlation, while a low coefficient indicates a weak or negative correlation. This function is commonly used in statistical analysis and data visualization. 
SLOPE
The
SLOPE
formula calculates the slope of the linear regression line that best fits the input data. It is commonly used in statistics to analyze trends and predict future values based on past performance. 
INTERCEPT
The
INTERCEPT
function calculates the point where the line of best fit for a set of data intercepts the yaxis. This function is commonly used in regression analysis to find the constant b in the equation y=mx+b where m is the slope of the regression line.
Learn More
You can learn more about the RSQ
Google Sheets function on Google Support.