शुरू करेंमुफ़्त में शुरू करें

Running the bootstrap

Good job writing calc_gender_coef() in the last exercise! This function creates a bootstrap sample, imputes it and, outputs the linear regression coefficient describing the impact of movie subject's being a female on the movie's earnings.

In this exercise, you will use the boot package in order to obtain a bootstrapped distribution of such coefficients. The spread of this distribution will capture the uncertainty from imputation. You will also look at how the bootstrapped distribution differs from a single-time imputation and regression. Let's do some bootstrapping!

यह अभ्यास पाठ्यक्रम का हिस्सा है

Handling Missing Data with Imputations in R

पाठ्यक्रम देखें

अभ्यास निर्देश

  • Load the boot package.
  • Run bootstrapping on biopics, passing calc_gender_coef as statistic and set R to 50; assign the result to boot_results.
  • print() and plot() the bootstrapping results.

इंटरैक्टिव व्यावहारिक अभ्यास

इस अभ्यास को इस नमूना कोड को पूरा करके आज़माएँ।

# Load the boot library
___

# Run bootstrapping on biopics data
boot_results <- ___(___, statistic = ___, R = ___)

# Print and plot bootstrapping results
___
___
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