Using R for introductory statistics in social sciences Mark A. Perkins

Format:

Book

Author/Creator:

Perkins, Mark A., author.

Series:

Quantitative methods in the humanities and social sciences 2199-0964

Language:

English

Subjects (All):

Social sciences--Statistical methods--Data processing.

Social sciences.

R (Computer program language).

Physical Description:

1 online resource

Edition:

1st ed.

Place of Publication:

Cham Springer 2026

Summary:

This book teaches R programming for fundamental statistical and data analysis skills, specifically tailored to social scientists and others new to quantitative research. Traditionally, this audience has relied on costly software packages such as SPSS, STATA, and SAS. However, R is a free, open-source alternative that, with proper guidance, is accessible and powerful for their needs. Many existing resources, whether books or online, are overly technical or difficult to follow. This book fills that gap by offering a concise, practical guide to mastering essential statistical processes, equipping readers with skills they can use throughout their careers. Data analysts, institutional researchers, and other professionals will use the book to perform statistical analyses and generate reports for their organizations. The included code -- both in the book and online -- helps them apply techniques to their own data. Readers will gain the following skills: Install and set up R and RStudio; write R scripts and create R Markdown documents. Understand variable types, measurement scales, and the basics of descriptive and inferential statistics. Conduct chi-square tests, t-tests, ANOVA, regression, and time series analysis in R. Assess and interpret statistical outputs; write results in APA format. Visualize data using ggplot2 and related libraries; create publication-ready charts and tables Evaluate statistical assumptions and apply techniques responsibly to real-world datasets Communicate findings clearly and concisely using professional standards

Contents:

Chapter 1. Introduction to the R Environment

Chapter 2. Statistical Concepts

Chapter 3. Running Descriptive Statistics and Frequencies in R

Chapter 4. Concepts for Research and Inferential Statistics

Chapter 5. The Chi-Square Family of Tests

Chapter 6. Group Comparisons with Scale Dependent Variables

Chapter 7. One-Way Dependent Samples and Time Series Tests

Chapter 8. Correlation and Regression Modeling

Notes:

Includes bibliographical references

Online resource; title from PDF title page (SpringerLink, viewed June 1, 2026)

ISBN:

9783032171450

3032171458

OCLC:

1593475444

Access Restriction:

Restricted for use by site license