Introduction to R for social scientists : a tidy programming approach / by Ryan Kennedy, Philip Waggoner.

Format:

Book

Author/Creator:

Kennedy, Ryan (Professor of political science), author.

Waggoner, Philip, author.

Contributor:

EBSCOhost

Series:

Statistics in the social and behavioral sciences series

Chapman & Hall/CRC statistics in the social and behavioral sciences series

Language:

English

Subjects (All):

Social sciences--Data processing.

Social sciences.

R (Computer program language).

Physical Description:

1 online resource (ix, 198 pages) : illustrations (some color.

Edition:

First edition.

Place of Publication:

Boca Raton, FL : CRC Press, Taylor & Francis Group, 2021.

Contents:

Machine generated contents note: 1. Introduction

1.1. Why R?

1.2. Why This Book?

1.3. Why the Tidyverse?

1.4. What Tools Are Needed?

1.5. How This Book Can be Used in a Class

1.6. Plan for the Book

2. Foundations

2.1. Scripting with R

2.2. Understanding R

2.3. Working Directories

2.4. Setting Up an R Project

2.5. Loading and Using Packages and Libraries

2.6. Where to Get Help

2.7. Concluding Remarks

3. Data Management And Manipulation

3.1. Loading the Data

3.2. Data Wrangling

3.3. Grouping and Summarizing Your Data

3.4. Creating New Variables

3.5. Combining Data Sets

3.6. Basic Descriptive Analysis

3.7. Tidying a Data Set

3.8. Saving Your Data Set for Later Use

3.9. Saving Your Data Set Details for Presentation

4. Visualizing Your Data

4.1. The Global Data Set

4.2. The Data and Preliminaries

4.3. Histograms

4.4. Bar Plots

4.5. Scatterplots

4.6. Combining Multiple Plots

4.7. Saving Your Plots

4.8. Advanced Visualizations

4.9. Concluding Remarks

5. Essential Programming

5.1. Data Classes

5.2. Data Structures

5.3. Operators

5.4. Conditional Logic

5.5. User-Defined Functions

5.6. Making Your Code Modular

5.7. Loops

5.8. Mapping with purrr

5.9. Concluding Remarks

6. Exploratory Data Analysis

6.1. Visual Exploration

6.2. Numeric Exploration

6.3. Putting it All Together: Skimming Data

6.4. Concluding Remarks

7. Essential Statistical Modeling

7.1. Loading and Inspecting the Data

7.2. t-statistics

7.3. Chi-square Test for Contingency Tables

7.4. Correlation

7.5. Ordinary Least Squares Regression

7.6. Binary Response Models

7.7. Concluding Remarks

8. Parting Thoughts

8.1. Continuing to Learn with R

8.2. Where To Go from Here

8.3. A Final Word.

Notes:

Includes bibliographical references (pages 189-192) and index.

Electronic reproduction. Ipswich, MA Available via World Wide Web.

Description based on print version record.

Other Format:

ebook version :

ISBN:

9781000353853 (electronic bk.)

1000353850 (electronic bk.)

Publisher Number:

90104435783

Access Restriction:

Restricted for use by site license.