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Calculating two-sided p-values

What if the original research hypothesis had focused on any difference in promotion rates between men and women instead of focusing on whether men are more likely to be promoted than women? In this case, a difference like the one observed would occur twice as often (by chance) because sometimes the difference would be positive and sometimes it would be negative.

When there is no directionality to the alternative hypothesis, the hypothesis and p-value are considered to be two-sided. In a two-sided setting, the p-value is double the one-sided p-value.

In this exercise, you'll calculate a two-sided p-value given the original randomization distribution and dataset.

The observed difference is stored in diff_orig and the difference in each permutation is the stat column of disc_perm.

Este exercício faz parte do curso

Foundations of Inference in R

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Instruções do exercício

Calculate the two-sided p-value. This is double the one-sided p-value that you calculated in previous exercises.

Exercício interativo prático

Experimente este exercício completando este código de exemplo.

# Calculate the two-sided p-value
disc_perm %>%
  summarize(p_value = ___)
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