The most basic regression relationship is a simple linear regression. In this case, E( Y | X ) = μ ( X ) = β 0 + β 1 X , a line with intercept β 0 and slope β 1 .

Simple linear regression is commonly used in forecasting and financial analysis—for a company to tell how a change in the GDP could affect sales, for example.

Linear Regression vs. Multiple Regression Example Consider an analyst who wishes to establish a relationship between the daily change in a company's stock prices and daily changes in trading volume .

Course TopicsLinear models, generalized linear models, and nonlinear models are examples of parametric regression models because we know the function that describes the relationship between the ...

In simple linear regression 1, we model how the mean of variable Y depends linearly on the value of a predictor variable X; this relationship is expressed as the conditional expectation E(Y|X ...