Demonstrate proficiency in the following areas:

LO 3.2.1 Simple linear regression (Ch 3.1)

For example:

A. Define a residual and a residual sum of squares (RSS).

B. Calculate the value of RSS.

C. Recognize and apply the least-squares coefficient estimates.

D. Interpret the least-squares coefficients.

E. Define the population regression line and least-squares line.

F. Define the concept of bias and unbiased estimators.

G. Define standard error and residual standard error.

H. Calculate the standard error of a statistic.

I. Calculate the 95% confidence interval.

J. Describe null and alternative hypotheses.

K. Calculate the t-statistic.

L. Assess the accuracy of linear regression.

M. Calculate the R2 statistic given TSS and RSS.

N. Interpret the given values of R2.

O. Describe the relationship between R2 and correlation.

P. Define the total sum of squares.

Reading 3.2: James, G., D. Witten, T. Hastie and R. Tibshirani. (2013). An Introduction to Statistical Learning: with applications in R. New York, NY: Springer. Chapter 3, Sections 1-3.

Book URL: http://www-bcf.usc.edu/~gareth/ISL/

Errata page URL:https://www.statlearning.com/errata-first-edition