Bootstrapping the data

Using the infer package with type = "bootstrap", you can repeatedly sample from the dataset to estimate the sampling distribution and standard error of the slope coefficient. Using the sampling distribution will allow you to directly find a confidence interval for the underlying population slope.

This exercise is part of the course

Inference for Linear Regression in R

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Exercise instructions

Use the infer steps to bootstrap the twins data 1000 times. You don't have to hypothesize() because now you're creating confidence intervals, not hypothesis testing!

Specify Foster versus Biological.
Generate 1000 replicates by bootstrapping.
Calculate the slope statistic.

Hands-on interactive exercise

Have a go at this exercise by completing this sample code.

# Set the seed for reproducibility
set.seed(4747)

# Calculate 1000 bootstrapped slopes
boot_slope <- twins %>%
  # Specify Foster vs. Biological
  ___ %>%
  # Generate 1000 bootstrap replicates
  ___ %>%
  # Calculate the slope statistic
  ___

# See the result  
boot_slope

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