The main evidence for the conclusion of the original paper comes down to a comparison of the percentages. The information we need was originally in Table S1 in the paper, which we include in dslabs: library(dslabs) data("research_funding_rates") research_funding_rates

Question 1a Construct a two-by-two table of gender (men/women) by award status (awarded/not) using the total numbers across all disciplines. What is the number of men not awarded? What is the number of women not awarded?

Question 1b Use the two-by-two table from Question 1a to compute the percentages of men awarded versus women awarded. What is the percentage of men awarded? What is the percentage of women awarded?

Question 1c Run a chi-squared test External link on the two-by-two table to determine whether the difference in the two success rates is significant. (You can use tidy() to turn the output of chisq.test() into a data frame as well.) What is the p-value of the difference in funding rate?