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.

This course is designed to supplement and build on the content covered at http://moderndive.com and the slides at htt...

Course Outline

  1. 1

    Applying R Basics

    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. 3

    Scatter-plots & Line-graphs

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

  3. 5

    Barplots

    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

  4. 7

    Filtering, Grouping, & Summarizing

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

  5. 2

    Tidy Data

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

  6. 4

    Histograms & Boxplots

    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

  7. 6

    ggplot2 Review

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

  8. 8

    dplyr Review

    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.

  1. 1

    Applying R Basics

    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. 2

    Tidy Data

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

  3. 3

    Scatter-plots & Line-graphs

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

  4. 4

    Histograms & Boxplots

    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. 5

    Barplots

    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

  6. 6

    ggplot2 Review

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

  7. 7

    Filtering, Grouping, & Summarizing

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

  8. 8

    dplyr Review

    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.

Chester Ismay
Chester Ismay

Senior Curriculum Lead at DataCamp

Chester builds (and helps instructors build) R, Python, SQL, and Spreadsheets courses for DataCamp. He obtained a PhD in Statistics from Arizona State University and has taught courses and led workshops in mathematics, computer science, statistics, data science, and sociology. He is co-author of the fivethirtyeight R package and author of the thesisdown R package. He is also a co-author of ModernDive, an open-source textbook for introductory statistics and data science students using R.

Course Instructor

Chester Ismay
Chester Ismay

Senior Curriculum Lead at DataCamp

Chester builds (and helps instructors build) R, Python, SQL, and Spreadsheets courses for DataCamp. He obtained a PhD in Statistics from Arizona State University and has taught courses and led workshops in mathematics, computer science, statistics, data science, and sociology. He is co-author of the fivethirtyeight R package and author of the thesisdown R package. He is also a co-author of ModernDive, an open-source textbook for introductory statistics and data science students using R.

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