Social Research with Statistics: New Titles from Sage
Maybe stats are not what you think of for beach reading.
Even if it isn’t the book you pack for a beach getaway, this is a good time to review new texts for future course instruction. You might also find materials that can introduce new approaches and enhance your research skills.
Use the code MSPACEQ223 for a 20% discount, valid until June 30, 2023.
Quantitative Social Science Data with R: An Introduction 2nd edition by Brian J. Fogarty
Gradually introducing applied statistics and the language and functionality of R and R Studio software, it uses examples from across the social sciences to show students how to apply abstract statistical and methodological principles to their own work. Maintaining a student-friendly pace, it goes beyond a normal introductory statistics book. Find online resources here.
Foundations of Programming, Statistics, and Machine Learning for Business Analytics by Ram Gopal, Dan Philps, Tillman Weyde
This book covers all the fundamentals, from statistics to programming to business applications, to equip you with the solid foundational knowledge needed to progress in business analytics. Assuming no prior knowledge of programming or statistics, this book takes a simple step-by-step approach which makes potentially intimidating topics easy to understand, by keeping Maths to a minimum and including examples of business analytics in practice. Find online resources here.
From Social Science to Data Science: Key Data Collection and Analysis Skills in Python by Bernie Hogan
From Social Science to Data Science is a fundamental guide to scaling up and advancing your programming skills in Python. From beginning to end, this book will enable you to understand merging, accessing, cleaning and interpreting data whilst gaining a deeper understanding of computational techniques and seeing the bigger picture.
Practical Multilevel Modeling Using R by Francis L. Huang
Practical Multilevel Modeling Using R provides students with a step-by-step guide for running their own multilevel analyses. Detailed examples illustrate the conceptual and statistical issues that multilevel modeling addresses in a way that is clear and relevant to students in applied disciplines.
Complete Data Analysis Using R: Your Applied Manual by Marco Lehmann
This step-by-step guide shows you how to use R to get data analysis right. The book explores the entire process of analysis, covering key steps from preparing your data to putting your analysis together and writing up your findings. It helps you get to grips with doing different statistical techniques in R. Find online resources here.
Doing Quantitative Research in Education with IBM SPSS Statistics 3rd Edition by Daniel Muijs
This essential guide for education students and researchers explains how to use quantitative methods for analysing educational data using IBM SPSS Statistics. By using datasets from real-life educational research, it demonstrates key statistical techniques that you will need to know, explaining how each procedure can by run on IBM SPSS Statistics. Datasets discussed in the book are downloadable, allowing you to hone your skills as you read.
Computational Thinking and Social Science: Combining Programming, Methodologies and Fundamental Concepts by Matti Nelimarkka
Whilst providing a fundamental understanding of computational social science, this book delves into the tools and techniques used to build familiarity with programming and gain context into how, why and when they are introduced. The overall focus is on helping you understand and design computational social science research, alongside delving into hands-on coding and technical instruction. Find online resources here. See this guest post, and watch a webinar with Dr. Nelimarkka.
Statistics for the Behavioral Sciences 4th edition by Gregory J. Privitera
Gregory Privitera aims to not only inspire students to use statistics properly to better understand the world around them, but also to develop the skills to be lab-ready in applied research settings. Incorporating examples from current, relatable research throughout the text, Privitera shows students that statistics can be relevant, interesting, and accessible.
Statistics with R: A Beginner's Guide, 2nd edition by Robert Stinerock
With a clear step-by-step approach explained using real world examples, learn the practical skills you need to use statistical methods in your research from an expert with over 30 years of teaching experience. With a wealth of hands-on exercises and online resources created by the author, practice your skills using the data sets and R scripts from the book with detailed screencasts that accompany each script.
Statistics for Psychology A Beginner's Guide, 2nd edition by Roger Watt and Elizabeth Collins
Statistics for Psychology is an interactive, highly visual, and accessible guide to the statistical practices you will encounter as a psychology student. Its software-agnostic approach keeps the focus on the core principles, rather than getting bogged down in complicated formulae and jargon. Find online resources here.
More Methodspace posts about data science and statistics
This blog post is the eighth, and final, post in a follow-on to our 2021 “The future of computational social science is Black” series, about a Summer Institute in Computational Social Science organized by Howard University and Mathematica. It continues to bring the power of computational social science to the issues of systemic racism and inequality in America. This marks the third iteration of the successful SICSS model being hosted by a Historically Black College or University.