R for Data Science: Analysis and Visualization

2h 47mBeginner2023-01-23

Authors

Barton Poulson

Professor, Designer, Data Analytics Expert

Course details

If you want to participate in the data revolution, you need the right tools and skills. R is a free, open-source language for data science that is among the most popular platforms for professional analysts. Learn the basics of R and get started finding insights from your own data, in this course with professor and data scientist Barton Poulson. The lessons explain how to get started with R, including installing R, RStudio, and code packages that extend R’s power. You also see first-hand how to use R and RStudio for beginner-level data modeling, visualization, and statistical analysis. By the end of the course, you’ll have a thorough introduction to the power and flexibility of R, and understand how to leverage this tool to explore and analyze a wide variety of data.

Skills covered

RStatisticsLearningProgramming LanguagesData ScienceOpen SourceSoftware Development

Concepts

0. Introduction

01 - R for data science
02 - Using the exercise files

1. What Is R

03 - R in context

2. Getting Started

04 - Installing R
05 - Environments for R
06 - Installing RStudio
07 - Navigating the RStudio environment
08 - Entering data
09 - Data types and structures
10 - Comments and headers
11 - Packages for R
12 - The tidyverse
13 - Piping commands with
14 - Sample datasets
15 - Importing data from a spreadsheet

3. Data Visualization

16 - Using colors in R
17 - Creating bar charts
18 - Creating histograms
19 - Creating box plots
20 - Creating scatterplots
21 - Creating line charts
22 - Creating cluster charts

4. Data Wrangling

23 - Selecting cases and subgroups
24 - Recoding variables
25 - Computing new variables

5. Data Analysis

26 - Computing frequencies
27 - Computing descriptives
28 - Computing correlations
29 - Computing a linear regression
30 - Computing contingency tables

Conclusion

31 - Next steps