Social Statistics

Managing Data, Conducting Analyses, Presenting Results

Thomas J. Linneman

• Publisher: Routledge
• Year: 2021
• ISBN:
  9781000508451
• Edition: 4
• Topic: Social Sciences
• Subtopic: Social Science Research & Methodology
• Index: Social Sciences

With a clear, engaging writing style and fascinating examples using a variety of real data, this text covers the contemporary statistical techniques that students will encounter in the world of social research. It covers these techniques at an introductory level and carefully guides students through increasingly complex examples without intimidating them. Recurrent examples using four timely topics—health, immigration, income inequality, and everyday harassment—help students understand how the techniques fit together, and how to use the techniques in combination with one another. A superb author-created web resource accompanies the text. How to make clear presentations of research results is also a feature of the text.

New to this edition:

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• New research shows how the techniques has changed over time in the academic literature, showing students that social scientists really do use the statistical techniques the book teaches and giving them ample motivation to learn the techniques.

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• Examples throughout the book use the most recent data from the General Social Survey. Four timely topics are threaded throughout the book: immigration, health, income inequality, and everyday harassment. Linneman uses these topics recurrently with different statistical techniques to illustrate how the techniques are related to one another.

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• The new edition more explicitly emphasizes that the various techniques the students are learning are often used in combination with one another. After introducing a new technique and showing how to use it on its own, Linneman then systematically offers examples of how to combine that technique with techniques students learned in previous chapters.

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• Most of the literature examples that end each chapter are new and use very recent research from top academic journals (three quarters from 2015 or later, nearly half from 2019). They feature research that covers timely topics such as Black Lives Matter, transgender health, social media, police behavior, and climate change. The SPSS demonstrations are completely redone, both in the book and on the website's demonstration videos, using more recent data. Linneman applies his experience teaching his own students SPSS (knowing where students get confused) to clarify his explanations in these demonstrations.

Chapter 1

Life in a Data-Laden Age

Finding and Managing Datasets

DOI: 10.4324/9781003220770-1

This chapter covers …

• … what data look like in their raw form within a dataset
• … how to work with data to get them ready to analyze
• … the wide variety of datasets that are readily available for analysis
• … how to build an additive index and check if it is acceptable
• … the newer forms that data take, from Internet databases to media analyses
• … types of variables used in statistical analysis
• … a classification of statistical procedures we’ll cover in this book
• … an example of how researchers used the Internet and algorithms to study popular music
• … an example of how researchers used content analysis to study racial stereotyping

Introduction

Though considered a rude question in other parts of the world, a very typical first question at American parties when people are meeting other people for the first time is “What do you do for a living?” I occasionally have attended parties, and so I have had the following conversation many times:

OG (other guest): What do you do for a living?

TL (that’s me): I’m a professor.

OG: Really? What do you teach?

TL: Introductory sociology.

OG: Nice!

TL: Social change.

OG: Interesting!

TL: And statistics.

OG: Yikes! I’m sorry. That must be horrible for you.

TL: No, I love it.

OG: Really? (at this point, OG usually tilts her head to one side and squints a little). Well, I hated my statistics course when I was in school …

Let’s get one thing out in the open right away: statistics has a bad reputation. Though I’m not a fan of speaking in odds (more on that much later in the book), I would bet that odds are good that you are not thrilled to be sitting in front of a book on statistics. Other emotions likely are in play: boredom, trepidation, fear. Maybe not all of these, but if you’re like many students taking a course in statistics, the probability is high that some of these emotions are involved. Any effort I make here to dispel such emotions likely will elicit another set of reactions: skepticism, disbelief, anger. I realize it might take me a while to win you over. But I will do my best. I’d even say that the odds are high that at some point, perhaps not right away, but somewhere down the road, you will, perhaps secretly, start to like statistics.

OK, you may not get to that point. But I do hope to convince you that understanding statistics is completely possible if you have the right combination of guides (your instructor and me). It is not only possible to understand statistics; it is also absolutely essential to being an informed and effective student, citizen, activist, or employee. We live in an age in which information is overwhelmingly everywhere, and a lot of this information is statistical. Legislators measure the success of social policies based on statistics. A philanthropist considering a large donation to a nonprofit organization may ask for evidence of the organization’s prior success, and this evidence is often statistical in nature. Start-up companies have made fortunes by developing better statistical models to help people mine the data created daily by people’s Internet searches and by consumer behavior (a journalist even went so far as to call these people “the Numerati” [Baker, 2008]). Therefore, if you can’t speak statistics, you could very well be left out of all of these loops.

Did I just say, “speak statistics”? Yes, I did. In many ways, for many people, learning statistics is very similar to learning a foreign language. If I started speaking, say, Farsi or Swahili right now, I’d probably lose your interest rather quickly (unless, of course, you’re a speaker of these languages, in which case you’d probably perk right up). But do I lose you any less slowly when I say, “Adding the squared age term raises the explained variation by 0.04 (with an F-test significant at p < .01) a...