In: Statistics and Probability
What is a simple regression analysis?
What is simple regression analysis?
Simple Linear regression models are used to show or predict the relationship between two variables or factors. The factor that is being predicted (the factor that the equation solves for) is called the dependent variable. The factors that are used to predict the value of the dependent variable are called the independent variables.
In linear regression, each observation consists of two values. One value is for the dependent variable and one value is for the independent variable. In this simple model, a straight line approximates the relationship between the dependent variable and the independent variable.
Formula For a Simple Linear Regression Model
The two factors that are involved in simple linear regression analysis are designated x and y. The equation that describes how y is related to x is known as the regression model.
The simple linear regression model is represented by:
The linear regression model contains an error term that is represented by ε. The error term is used to account for the variability in y that cannot be explained by the linear relationship between x and y. If ε were not present, that would mean that knowing x would provide enough information to determine the value of y.