Ahmad Mousavi

Ahmad Mousavi

Assistant Prof. of Data Science,
Dept. of Math. and Stat.,
American University

Lab 11: Tests and Models

DATA 412/612 · Week 11 · PDF · Source (.qmd)

A t-test, an ANOVA, a linear model, and a column summary.

Work in a Quarto document. Do 11.1 and 11.2 first. Prefer mtcars, palmerpenguins, or iris so the lab runs without extra files. Sleuth3 is optional.

library(tidyverse)
library(palmerpenguins)

1. Two-sample t-test

  1. Boxplot of a numeric variable by a two-level group.
  2. t.test() with the formula y ~ group. Save the object.

Use mpg by am in mtcars, or Adelie vs Gentoo bill length in penguins after filter() and droplevels(). State H0 in words. Report the p-value as evidence against that H0.

2. ANOVA

aov() of a numeric variable by a factor with three or more levels. Save the fit and summary() it.

bill_length_mm ~ species in penguins, mpg ~ factor(cyl) in mtcars, or Sepal.Length ~ Species in iris are all fine. State H0 in words.

3. Regression

lm() with two predictors. Interpret one coefficient in a sentence (holding the other predictor fixed). Glance at the residual-versus-fitted plot (plot(fit, which = 1) or broom::augment()).

mpg ~ wt + hp in mtcars is the intended default.

4. Column summaries

  1. across() on every numeric column: mean and sd, .names = "{.col}_{.fn}", na.rm via a formula ~ mean(.x, na.rm = TRUE).
  2. If skimr is installed, skimr::skim() on the same table.