# R package for Math 300Z

Most students will want to use POSIT.cloud. Use the “Z-Section” project.

- You will use the same project for all the Lessons adding a new file each class day.
- The
`{math300}`

R package will already be installed. If you find otherwise, use the commands given in the laptop section to install/update the needed packages for the Z-section package.

## Accessing the daily worksheet

Almost all class days there will be a worksheet in the form of an Rmd file.

From within your POSIT.cloud project, download the Rmd file using this command, substituting the number of the relevant Lesson:

`::get_lesson_worksheet(19) math300`

- Make a habit of reading each day’s Rmd file
*before*class. This way you can note what doesn’t yet make sense so that you can be receptive to the topic in class. - Complete the worksheet after class.

## Math 300Z R commands

There will be only a dozen commands that you will be using in the second half of Math 300Z. Almost all of them involve constructing or summarizing models.

As a reminder, here are some of the commands/syntax that should be familiar to you from the first half of the course.

`lm()`

fits (or “trains”) a “linear model” on data from a data frame.`ggplot()`

sets things up for a new graphic. Use`aes()`

as an argument.- graphics layers to add onto the output of
`ggplot()`

:`geom_point()`

,`geom_jitter(alpha=0.5)`

`filter()`

,`mutate()`

and`summarize()`

are basic data-wrangling commands we will use often.

New commands in the second half of the course:

- summarize a
**model**:`conf_intervals()`

,`R2()`

- evaluate a
**model**:`model_eval()`

- graphic of a
**model**:`model_plot()`

(This replaces the`geom_smooth()`

used in the first half of the course.) - variance of a variable in a data frame:
`DF %>% summarize(NM = var(VAR))`

- draw a DAG:
`dag_draw()`

- sample from a DAG:
`sample(DAG, size=100)`

A few other commands will be used occasionally in examples and demonstrations. You should know what they do, but typically there will be a reminder of the syntax: `zero_one()`

, `shuffle()`

, `do() * {}`

, `dag_intervene()`

, `tibble()`

, `regression_summary()`

, `anova_summary()`

.

## Running R/RStudio on your laptop?

Install the `{math300}`

and other packages with these two commands:

```
install.packages(c("mosaic", "ggplot", "dplyr", "openintro", "moderndive", "nycflights13", "knitr"))
# additional package for Math 300Z
::install_github("dtkaplan/math300") remotes
```