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  3. Case Study: Exploratory Data Analysis in R

Exercise

Filtering for significant countries

Not all slopes are significant, and you can use the p-value to guess which are and which are not.

However, when you have lots of p-values, like one for each country, you run into the problem of multiple hypothesis testing, where you have to set a stricter threshold. The p.adjust() function is a simple way to correct for this, where p.adjust(p.value) on a vector of p-values returns a set that you can trust.

Here you'll add two steps to process the slope_terms dataset: use a mutate to create the new, adjusted p-value column, and filter to filter for those below a .05 threshold.

Instructions

100 XP

Use the p.adjust() function to adjust the p.value column, saving the result into a new p.adjusted column. Then, filter for cases where p.adjusted is less than .05.