Compute effect sizes with R. A primer.

A typical “cook book recipe” for doing data analysis is an applied stats course is: report descriptive statistics plot some nice diagrams test hypothesis report effect sizes Let’s have a quick glance at these steps. We will use the dataset flights of the package nycflights13. data(flights, package = "nycflights13") This post will be tidyverse-driven. library(tidyverse) library(skimr) library(mosaic) Let’s compute some summaries: flights %>% select(arr_delay) %>% skim Data summary Name Piped data Number of rows 336776 Number of columns 1 _______________________ Column type …