16.2 Topics to cover

• Fitting a straight sine by Least Squares (LS)
• The Analysis of variance (ANOVA)
• Confidence intervals and test for $\beta$
• Dummy variables
• Multicollinearity
• Non-linear relationships

Basic Prerequisite Knowledge to Tackle Regression

• Distributions: Normal, t and F.
• Confidence Intervals and Hypothesis Testing.
• Elements of Matrix Algebra

16.2.1 Our Monet Case

Let’s revisit the example with Monet Paintings. In Section 6.5.1 we observe a linear relationship between Price and Size.

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Source:A Shiny app for simple linear regression by hand and in R