In this section, you learn how to:
- Visualize the ANOVA decomposition of variability
- Calculate and interpret (R^2) – the coefficient of determination
- Calculate and interpret (s^2) – the mean square error
- Explain the components of the ANOVA table
Video Overview of the Section (Alternative .mp4 Version – 10:46 min)
Although statistics is the science of summarizing data, it is also the art of arguing with data. This section develops some of the basic tools used to justify the basic linear regression model. A scatter plot may provide strong visual evidence that x influences y; developing numerical evidence will enable us to quantify the strength of the relationship. Further, numerical evidence will be useful when we consider other data sets where the graphical evidence is not compelling.