![]() ![]() To explore this relationship, we can perform simple linear regression using hours studied as an explanatory variable and exam score as a response variable. studies for an exam and the exam score they receive. Suppose we are interested in understanding the relationship between hours studied and exam score. ![]() Simple Linear Regression in Google Sheets The following examples show how to use this function in practice. This is FALSE by default, but we will specify this to be TRUE in our examples. verbose: Indicates whether or not to provide additional regression statistics beyond just the slope and intercept.This is TRUE by default and we leave it this way for linear regression. calculate_b: Indicates whether or not to calculate the y-intercept.known_data_x: Array of explanatory values. ![]() LINEST(known_data_y, known_data_x, calculate_b, verbose) It’s possible to perform both types of regressions using the LINEST() function in Google Sheets, which uses the following syntax: We use simple linear regression when there is only one explanatory variable and multiple linear regression when there are two or more explanatory variables. Linear regression is a method that can be used to quantify the relationship between one or more explanatory variables and a response variable. ![]()
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