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## Course Description

This course is designed to supplement and build on the content covered at http://moderndive.com and the slides at http://bit.ly/soc301-slides. It assumes that you have completed the Introduction to R course on DataCamp.

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### Training 2 or more people?

Get your team access to the full DataCamp library, with centralized reporting, assignments, projects and more- 1
### Applying R Basics

**Free**Exploring the basics of R on a data set based on the fivethirtyeight.com "Most Police Don’t Live In The Cities They Serve" article.

- 2
### Tidy Data

**Free**Look into tidy data properties on data sets used in articles from fivethirtyeight.com in the fivethirtyeight R package

- 3
### Scatter-plots & Line-graphs

**Free**Create and analyze different plots relating two numerical variables via the ggplot2 package using datasets in and derived from the fivethirtyeight R package

- 4
### Histograms & Boxplots

**Free**Make and interpret different plots relating one categorical variable to one numerical variable via the ggplot2 package using datasets in and derived from the fivethirtyeight R package

- 5
### Barplots

**Free**Generate and examine barplots displaying one categorical variable or relationships between multiple categorical variables via the ggplot2 package using datasets in and derived from the fivethirtyeight R package

Distribution of one categorical variable100 xpDistribution of another categorical variable100 xpMovies over time100 xpBechdel pass/fail over time (stacked)100 xpBechdel pass/fail over time (side-by-side)100 xpBechdel pass/fail over time (faceted)100 xpBechdel pass/fail over time (proportional height)100 xpShowing off100 xp - 6
### ggplot2 Review

**Free**Identifying and creating the appropriate plot based on different types of variables using the ggplot2 package

- 7
### Filtering, Grouping, & Summarizing

**Free**Choose a subset of rows and summarize a data frame in total and across different levels of other variables using the dplyr package

- 8
### dplyr Review

**Free**Create a new column in a data frame, modify an existing column, and sort by one or more columns using the dplyr package. Review the main ideas of the Five Main Verbs of dplyr - filter, summarize, group_by, mutate, and arrange.

- 9
### Supplement to ModernDive textbook

**Free**To supplement learning of the material covered at http://moderndive.com, this chapter provides a playground for you to work with the code and better understand what each of the gray chunks of R code throughout the book does.

Albert Y. Kim

See MoreAssociate Professor of Statistical & Data Sciences, Smith College

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