![]() ![]() ![]() ![]() Next, we’ll fit a multiple linear regression model using Exam Score as the response variable and Study Hours and Current Grade as the predictor variables. Step 1: Create the Dataįor this example, we’ll create a dataset that contains the following variables for 12 different students: This tutorial provides a step-by-step example of how to calculate the standard error of a regression model in Excel. One way to measure the dispersion of this random error is by using the standard error of the regression model, which is a way to measure the standard deviation of the residuals ϵ. No matter how well X can be used to predict the values of Y, there will always be some random error in the model. Where ϵ is an error term that is independent of X. Whenever we fit a linear regression model, the model takes on the following form: ![]()
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