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

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