---
title: "14.3 Course Wrap"
---

```{r}
#| label: setup
#| include: false
knitr::opts_chunk$set(
  echo = TRUE,
  message = FALSE,
  warning = FALSE,
  fig.width = 6,
  fig.height = 3.6,
  fig.align = "center",
  dpi = 120,
  error = TRUE,
  fig.path = "_figs/course-wrap/"
)
library(tidyverse)
```

Question, tidy, plot, model, communicate. Iterate.

## 1. The lifecycle

A data analysis is a loop, not a straight line:

1. a question
2. tidy the table
3. plot
4. model
5. communicate

You go around more than once. A plot changes the question. A model sends you back to the table. The last step is a document someone else can rerun.

---

## 2. Tools you have now

Job
What you reach for




Rows, columns, groups
dplyr verbs, `across()`, `case_when()`


Pictures
ggplot2


Files in and out
readr


Wider / longer tables
tidyr


Two tables
joins


Strings, factors, dates
stringr, forcats, lubridate


A mean difference or a line
`t.test()`, `lm()`


A writeup
Quarto / R Markdown

Iteration — loops and `purrr::map` — is the last verb: do the same thing to many pieces.

---

## 3. Last lesson

Iterate. Save the file. Render again. The competence is not one clever plot. It is being able to change a step and get a new document that still runs.

You already have the verbs. Week 14 is the habit of applying them to many pieces at once.

---

## 4. Practice

Write five bullets of work you can do now that you could not do in week 1. Be specific (a verb and a data set), not "I learned R."