Describe Your Linear Data

Compute simple statistical linear regression models that relate a dependent to an independent variable.

Learning objectives

At the end of this session you should be able to

• discuss different indicators relevant for the assessment of linear regression results,
• use residual plots to discuss the mean pattern, error spread and normal approximation;
• explain which assumptions need information about the sampling design;
• numerically evaluate properties of linear regressions.

Start with the modeling explanation and the regression example. Then work through Checking Regression Assumptions before Assignment 05.

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