![]() ![]() This equation matches the one that we calculated by hand. ![]() We can double check our results by inputting our data into the simple linear regression calculator: A one pound increase in weight is associated with a 0.2001 inch increase in height. When weight is zero pounds, the predicted height is 32.783 inches. Sometimes the value for b 0 can be useful to know, but in this example it doesn’t actually make sense to interpret b 0 since a person can’t weigh zero pounds.ī 1 = 0.2001. Here is how to interpret this estimated linear regression equation: ŷ = 32.783 + 0.2001xī 0 = 32.7830. In our example, it is ŷ = 0.32783 + (0.2001)*x How to Interpret a Simple Linear Regression Equation The estimated linear regression equation is: ŷ = b 0 + b 1*x Step 5: Place b 0 and b 1 in the estimated linear regression equation. The equation below is what we want to fit. If you want a recap on what Alpha and Beta is, please read this article. Regression Example (Alpha and Beta) Finding the Alpha and Beta of a Portfolio. Use the following steps to fit a linear regression model to this dataset, using weight as the predictor variable and height as the response variable. Else, let’s see how we can use Excel to find the Alpha and Beta of a portfolio. ![]() Suppose we have the following dataset that shows the weight and height of seven individuals: Linear analysis is one type of regression analysis. Example: Simple Linear Regression by Hand Regression analysis, as mentioned earlier, is majorly used to find equations that will fit the data. This tutorial explains how to perform simple linear regression by hand. ![]() Simple linear regression is a statistical method you can use to quantify the relationship between a predictor variable and a response variable. ![]()
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