Data Analysis for the Social Sciences

Douglas Bors - University of Toronto at Scarborough

Additional resources:

January 2018 | 664 pages | SAGE Publications Ltd

Accessible, engaging, and informative, this text will help any social science student approach statistics with confidence.

With a well-paced and well-judged integrated approach rather than a simple linear trajectory, this book progresses at a realistic speed that matches the pace at which statistics novices actually learn. Packed with global, interdisciplinary examples that ground statistical theory and concepts in real-world situations, it shows readers not only how to apply newfound knowledge using IBM® SPSS® Statistics, but also why they would want to. Spanning statistics basics like variables, constants, and sampling to t-tests, multiple regression, and factor analysis, it builds statistical literacy while also covering key research principles like research questions, error types, and results reliability.

Readers will learn how to:

Describe data with graphs, tables, and numbers
Calculate probability and value distributions
Test a priori and post hoc hypotheses
Conduct Chi-squared tests and observational studies
Structure ANOVA, ANCOVA, and factorial designs

Supported by extensive visuals and a companion website with interactive demonstrations, author video, and practice datasets, this book is the student-focused companion to support learners through their statistics journeys.

Available Formats

ISBN: 9781446298473	Hardcover	Suggested Retail Price: $217.00	Bookstore Price: $173.60
ISBN: 9781446298480	Paperback	Suggested Retail Price: $122.00	Bookstore Price: $97.60
ISBN: 9781526422316	Electronic Version	Suggested Retail Price: $104.00	Bookstore Price: $104.00

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Part I: The Foundations

Chapter 1: Overview

The general framework

Recognizing randomness

Lies, damn lies, and statistics

Testing for randomness

Research design and key concepts

Paradoxes

Chapter 2: Descriptive Statistics

Numerical Scales

Histograms

Measures of Central Tendency: Measurement Data

Measures of Spread: Measurement Data

What creates Variance?

Measures of Central Tendency: Categorical Data

Measures of Spread: Categorical Data

Unbiased Estimators

Practical SPSS Summary

Chapter 3: Probability

Approaches to probability

Frequency histograms and probability

The asymptotic trend

The terminology of probability

The laws of probability

Bayes’ Rule

Continuous variables and probability

The standard normal distribution

The standard normal distribution and probability

Using the z-tables

Part II: Basic Research Designs

Chapter 4: Categorical data and hypothesis testing

The binomial distribution

Hypothesis testing with the binomial distribution

Conducting the binomial test with SPSS

Null hypothesis testing

The x2 goodness-of-fit test

The x2 goodness-of-fit test with more than two-categories

Conducting the x2 goodness-of-fit test with SPSS

Power and the x2 goodness-of-fit test

G -test

Can a failure to reject indicate support for a model?

Chapter 5: Testing for a Difference: Two Conditions

Building on the z-score

Testing a single sample

Independent-samples t-test

t-test assumptions

Pair-samples t-test

Confidence limits and intervals

Randomization test and bootstrapping

Nonparametric tests

Chapter 6: Observational studies: Two categorical variables

x2 goodness-of-fit test reviewed

x2 test of independence

The phi coefficient

Necessary assumptions

x2 test of independence SPSS example

Power, sample size, and the x2 test of independence

The third-variable problem

Multi-category nominal variables

Tests of independence with ordinal variables

Chapter 7: Observational studies: Two measurement variables

Tests of association for categorical data reviewed

The scatterplot

Covariance

The Pearson-Product Moment Correlation Coefficient

Simple regression analysis

The Ordinary Least Squares Regression Line (OLS)

The assumptions necessary for valid correlation and regression coefficients

Chapter 8: Testing for a difference: Multiple between-subject conditions (ANOVA)

Reviewing the t-test and the x2 test of independence

The logic of ANOVA: Two unbiased estimates of o2

ANOVA and the F-test

Standardized effect sizes and the F-test

Using SPPS to run an ANOVA F-test: Between-subjects design

The third-variable problem: Analysis of covariance (ANCOVA)

Non-parametric alternatives

Chapter 9: Testing for a difference: Multiple related-samples

Reviewing the between-subject ANOVA and the t-test

The logic of the randomized block design

Running a randomized block design with SPSS

The logic of the repeated-measures design

Running a repeated-measures design with SPSS

Non-parametric alternatives

Chapter 10: Testing for specific differences: Planned and unplanned tests

A priori versus post hoc tests

Per-comparison versus family-wise error rates

Planned comparisons: A priori test

Testing for polynomial trends

Unplanned comparisons: Post hoc tests

Non-parametric follow-up comparisons

Part III: Analyzing Complex Designs

Chapter 11: Testing for Differences: ANOVA and Factorial Designs

Reviewing the independent-samples ANOVA

The logic of factorial designs: Two between-subject independent variables

Main and simple effects

Two Between-Subject Factorial ANOVA with SPSS

Fixed versus random factors

Analyzing a mixed-design ANOVA with SPSS

Non-parametric alternatives

Chapter 12: Multiple Regression

Regression revisited

Introducing a second predictor

A detailed example

Issues concerning normality

Missing data

Testing for linearity and homoscedasticity

A multiple regression: The first pass

Addressing multicollinearity

Interactions

What can go wrong?

Chapter 13: Factor analysis

What is factor analysis?

Correlation coefficients revisited

The correlation matrix and PCA

The component matrix

The rotated component matrix

A detailed example

Choosing a method of rotation

Sample size requirements

Hierarchical multiple factor analysis

The effects of variable selection

An engaging textbook that delivers.

Miss Helen Coleman

Library Science, Glyndwr University

February 8, 2018

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THE BOOKS FROM SAGE HAVE TREMENDOUSLY HELPED ME ALL THROUGH MY RESEARCH AND ARE STILL HELPFUL, SUCH THAT I CANNOT HELP BUT ADOPT ALL THE BOOKS FROM THEM THAT I HAVE USED. THANKS, SAGE PUBLISHERS.

Mrs Catherine Otene

Faculty of Engineering & Science, Greenwich University

May 28, 2018

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Gathering data is the easy part of the empirical research process but often students do not think carefully enough about the analysis of their data before they start to gather it. This book gives clear guidance on the methodology and process of data analysis giving clear and concise approaches to data analysis methods and tools. A very useful addition to the methodological bookshelf.

Mr Paul Hopkins

Faculty of Education (Hull), Hull University

April 18, 2018

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Key features

KEY FEATURES:

Includes a math diagnostics test to help readers understand their current strengths and weaknesses
Introduces statistics at a gradual, student-friendly pace designed to build confidence
Highly visual and designed to ensure key points are not lost in overwhelming amounts of text
Supported by interactive demonstrations, simulations, and author videos

To counter student fear of statistics it starts from the very basics - including a maths diagnostics test to help students understand their current maths strengths and weaknesses
It introduces statistics at a gradual, student-friendly pace designed to build confidence and makes no assumptions of prior knowledge.
Highly visual (over 600 figures and SPSS screenshots and boxed definitions and clarifying explanations of tricky concepts) - designed to make sure key points don’t get lost in overwhelming amounts of text.
Supported by interactive demonstrations, simulations and author videos so students can take advantage of a variety of ways to learn and digest the important information.
Focusing on real-world situations, this book demonstrates not only step-by-step instruction about how to approach statistical tests and use SPSS software, but also illustrates how and why these types of tests are relevant to the reality outside of the classroom.
Provides students with the ability to click through tests and apply their knowledge to different research scenarios.

To counter student fear of statistics it starts from the very basics - including a maths diagnostics test to help students understand their current maths strengths and weaknesses

It introduces statistics at a gradual, student-friendly pace designed to build confidence and makes no assumptions of prior knowledge.

Highly visual (over 600 figures and SPSS screenshots and boxed definitions and clarifying explanations of tricky concepts) - designed to make sure key points don’t get lost in overwhelming amounts of text.

Supported by interactive demonstrations, simulations and author videos so students can take advantage of a variety of ways to learn and digest the important information.

Focusing on real-world situations, this book demonstrates not only step-by-step instruction about how to approach statistical tests and use SPSS software, but also illustrates how and why these types of tests are relevant to the reality outside of the classroom.

Provides students with the ability to click through tests and apply their knowledge to different research scenarios