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  3. Inference for Numerical Data in R
  • 1

    Bootstrapping for estimating a parameter

    Free

    In this chapter you'll use bootstrapping techniques to estimate a single parameter from a numerical distribution.

  • 2

    Introducing the t-distribution

    In this chapter you'll use Central Limit Theorem based techniques to estimate a single parameter from a numerical distribution. You will do this using the t-distribution.

  • 3

    Inference for difference in two parameters

    In this chapter you'll extend what you have learned so far to use both simulation and CLT based techniques for inference on the difference between two parameters from two independent numerical distributions.

  • 4

    Comparing many means

    In this chapter you will use ANOVA (analysis of variance) to test for a difference in means across many groups.

Initializing

Exercise

EDA for vocabulary score vs. social class

Before we conduct inference, we should take a look at the distributions of vocabulary scores across the levels of (self identified) social class.

Instructions

100 XP
  • Using gss, plot the distribution of vocabulary scores, wordsum.
  • Make this a histogram, using an appropriate binwidth.
  • Facet this histogram, wrapping by social class level.
  • Look at the plot! Compare the distributions of vocabulary scores across the levels of (self identified) social class.