# cm011 - October 30, 2017

## Overview

• Define statistical learning
• Review the major goals of statistical learning
• Explain the difference between parametric and non-parametric methods
• Introduce linear models and ordinary least squares regression
• Demonstrate how to estimate a linear model in R using lm()
• Demonstrate how to extract model statistics using broom and modelr
• Practice estimating and interpreting linear models

## Before class

• Read chapters 22-25 in R for Data Science
• If you want a more rigorous introduction to the fundamentals of statistical learning and linear models, read chapters 2 and 3 in An Introduction to Statistical Learning. However this text assumes a much stronger knowledge of math, probability, and statistics.

## What you need to do

• Install the titanic package using the command install.packages("titanic"). We will be using this package in-class next time