# Statistics for Social Science

Lead Author(s): **Stephen Hayward**

Student Price: **Contact us to learn more**

Statistics for Social Science takes a fresh approach to the introductory class. With learning check questions, embedded videos and interactive simulations, students engage in active learning as they read. An emphasis on real-world and academic applications help ground the concepts presented. Designed for students taking an introductory statistics course in psychology, sociology or any other social science discipline.

**8,525 students**

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## Key features in this textbook

## Comparison of Social Sciences Textbooks

Consider adding Top Hat’s Statistics for Social Sciences textbook to your upcoming course. We’ve put together a textbook comparison to make it easy for you in your upcoming evaluation.

### Top Hat

Steve Hayward et al., Statistics for Social Sciences, Only one edition needed

### Pearson

Agresti, Statistical Methods for the Social Sciences, 5th Edition

### Cengage

Gravetter et al., Essentials of Statistics for The Behavioral Sciences, 9th Edition

### Sage

Gregory Privitera, Essentials Statistics for the Behavioral Sciences, 2nd Edition

### Pricing

Average price of textbook across most common format

#### Up to 40-60% more affordable

Lifetime access on any device

#### $200.83

Hardcover print text only

#### $239.95

Hardcover print text only

#### $92

Hardcover print text only

### Always up-to-date content, constantly revised by community of professors

Content meets standard for Introduction to Anatomy & Physiology course, and is updated with the latest content

### In-Book Interactivity

Includes embedded multi-media files and integrated software to enhance visual presentation of concepts directly in textbook

Only available with supplementary resources at additional cost

Only available with supplementary resources at additional cost

Only available with supplementary resources at additional cost

### Customizable

Ability to revise, adjust and adapt content to meet needs of course and instructor

### All-in-one Platform

Access to additional questions, test banks, and slides available within one platform

## Pricing

Average price of textbook across most common format

### Top Hat

Steve Hayward et al., Statistics for Social Sciences, Only one edition needed

#### Up to 40-60% more affordable

Lifetime access on any device

### Pearson

Agresti, Statistical Methods for the Social Sciences, 5th Edition

#### $200.83

Hardcover print text only

### Pearson

Gravetter et al., Essentials of Statistics for The Behavioral Sciences, 9th Edition

#### $239.95

Hardcover print text only

### Sage

McConnell, Brue, Flynn, Principles of Microeconomics, 7th Edition

#### $92

Hardcover print text only

## Always up-to-date content, constantly revised by community of professors

Constantly revised and updated by a community of professors with the latest content

### Top Hat

Steve Hayward et al., Statistics for Social Sciences, Only one edition needed

### Pearson

Agresti, Statistical Methods for the Social Sciences, 5th Edition

### Pearson

Gravetter et al., Essentials of Statistics for The Behavioral Sciences, 9th Edition

### Sage

Gregory Privitera, Essentials Statistics for the Behavioral Sciences, 2nd Edition

## In-book Interactivity

Includes embedded multi-media files and integrated software to enhance visual presentation of concepts directly in textbook

### Top Hat

Steve Hayward et al., Statistics for Social Sciences, Only one edition needed

### Pearson

Agresti, Statistical Methods for the Social Sciences, 5th Edition

**Pearson**

Gravetter et al., Essentials of Statistics for The Behavioral Sciences, 9th Edition

### Sage

Gregory Privitera, Essentials Statistics for the Behavioral Sciences, 2nd Edition

## Customizable

Ability to revise, adjust and adapt content to meet needs of course and instructor

### Top Hat

Steve Hayward et al., Statistics for Social Sciences, Only one edition needed

### Pearson

Agresti, Statistical Methods for the Social Sciences, 5th Edition

### Pearson

Gravetter et al., Essentials of Statistics for The Behavioral Sciences, 9th Edition

### Sage

Gregory Privitera, Essentials Statistics for the Behavioral Sciences, 2nd Edition

## All-in-one Platform

Access to additional questions, test banks, and slides available within one platform

### Top Hat

Steve Hayward et al., Statistics for Social Sciences, Only one edition needed

### Pearson

Agresti, Statistical Methods for the Social Sciences, 5th Edition

### Pearson

Gravetter et al., Essentials of Statistics for The Behavioral Sciences, 9th Edition

### Sage

Gregory Privitera, Essentials Statistics for the Behavioral Sciences, 2nd Edition

## About this textbook

### Lead Authors

#### Steve HaywardRio Salado College

A lifelong learner, Steve focused on statistics and research methodology during his graduate training at the University of New Mexico. He later founded and served as CEO of Center for Performance Technology, providing instructional design and training development support to larger client organizations throughout the United States. Steve is presently lead faculty member for statistics at Rio Salado College in Tempe, Arizona.

#### Joseph F. Crivello, PhDUniversity of Connecticut

Joseph Crivello has taught Anatomy & Physiology for over 34 years, and is currently a Teaching Fellow and Premedical Advisor of the HMMI/Hemsley Summer Teaching Institute.

### Contributing Authors

#### Susan BaileyUniversity of Wisconsin

#### Deborah CarrollSouthern Connecticut State University

#### Alistair CullumCreighton University

#### William Jerry HauseltSouthern Connecticut State University

#### Karen KampenUniversity of Manitoba

#### Adam SullivanBrown University

## Explore this textbook

Read the fully unlocked textbook below, and if you’re interested in learning more, get in touch to see how you can use this textbook in your course today.

### Version 3.3.3

# Table of Contents

**1- ****Introduction to Statistics**

1.01- What is 'Statistics'?

1.02- Populations and Samples

1.03- Parameters and Statistics

1.04- Descriptive Statistics and Inferential Statistics

1.05- Quantitative and Qualitative Data

1.06- Levels of Measurement

1.07- Variables

1.08- Design of Statistical Studies

1.09- Types of Studies

1.10- Validity and Reliability

1.11- Sampling Methods

1.12- A Day Without Statistics

1.13- Case Study: Is Drinking Coffee Good for You?

**2- ****Descriptive Statistics**

2.01-Summarizing Data

2.02- Frequency tables

2.03- Grouped Frequency Tables

2.04- Charts and Graphs

2.05- Modality of a distribution

2.06- Skewness

2.07- Measures of Central Tendency

2.08- Quartiles, Deciles, and Percentiles

2.09- Dispersion of Scores (Variability)

2.10- Population Variance and Standard Deviation

2.11- Sample Variance and Standard Deviation

2.12- Rounding Rules

2.12- Case Study: Statistics Aren't the Whole Story

**3- ****The Normal Distribution and Normal Curve**

3.01- Distributions of Data

3.02- The Normal Distribution

3.03- The Normal Curve

3.04- Characteristics of the Normal Distribution and Its Graph, the Normal Curve

3.05- The Empirical Rule

3.06- Determine Whether a Data Set is Normally Distributed

3.07- Determine Mean and Standard Deviation of a Known Distribution

3.08- Chebyshev's Theorem

3.09- Introduction to z-Scores

3.10- The Standard Normal Distribution

3.11- Calculation of z-Scores

3.12- The Empirical Rule Applied to z-Scores

3.13- The Normal Curve and Probability

3.14- Case Study: U.S. Household Incomes

**4- ****Introduction to Probability**** **

4.01- Why Study Probability?

4.02- What is Probability?

4.03- What is a Probability Experiment?

4.04- What is Sample Space?

4.05- Events

4.06- Types of Probability

4.07- Types of Events

4.08- The Fundamental Counting Principle

4.09- The Multiplication Rule

4.10- The Addition Rule

4.11- Odds

4.12- Case Study: The Monty Hall Problem

**5- ****Discrete Probability Distributions**

5.01- What is a Random Variable?

5.02- Discrete vs. Continuous Random Variables

5.03- Discrete Probability Distributions

5.04- About Factorials!

5.05- Permutations and Combinations

5.06- Binomial Experiment

5.07- Probabilities of Outcomes in Binomial Trials

5.08- Mean, Variance and Standard Deviation of a Binomial

5.09- Distribution of Outcomes in Binomial Trials

5.10- Distributions When Events Are Determined by Multiple Factors

5.11- Case Study: Identity Theft

**6- ****Normal Probability Distributions**** **

6.01- The Normal Curve as a Chart of the Distribution

6.02- The Normal Curve as a Chart of a Variable

6.03- Characteristics of the Normal Curve

6.04- Symmetry and Central Tendency

6.05- Normal Curve and z-Score Review

6.06 Introducing the Standard Normal Table

6.07- Using the Standard Normal Table to Find z-Scores

6.08- z-Score to Raw Score Conversion

6.09- Introduction to Sampling Distributions

6.10- The Central Limit Theorem

6.11- Finding Probabilities for Sample Means

6.12- The Normal Approximation to a Binomial Distribution

6.13- Applying a Continuity Correction

6.14- Case Study: Blood Pressure and Age

**7- ****Four Distributions: z, t, ****x**^{2}**, and F**

7.01- Early History

7.02- The Normal Distribution

7.03- The Standard Normal Distribution

7.04- The Standard Normal Table

7.05- The t-Distribution

7.06- Monte Carlo Experiments

7.07- The t-Table

7.08- The Chi-Square Distributions

7.09- The Chi-Square Table

7.10- The F-Distribution

7.11- The F-Table

7.12- Case Study: Cryptography and Chi-Square

**8- ****Confidence Intervals**

8.01- What are Confidence Intervals and Why Do We Use Them?

8.02- Point Estimates and Interval Estimates

8.03- The Level of Confidence

8.04- The Three Most Common Levels of Confidence

8.05- Common Misinterpretations of Confidence Level

8.06- Confidence Interval vs. Confidence Level

8.07- The Margin of Error vs. Sampling Error

8.08- The Central Limit Theorem and Confidence Intervals

8.09- Assumptions for a Confidence Interval

8.10- Confidence Interval for the Mean

8.11- Confidence Intervals for Proportions

8.12- Effects of Changing the Sample Size

8.13- Case Study: The Religious Landscape Study

**9- ****Introduction to Hypothesis Testing**

9.01- What is a Hypothesis?

9.02- The Deductive/Inductive Process

9.03- Elements of an Experiment

9.04- The Scientific Method

9.05- Elements of a Hypothesis

9.06- Preparing to Write a Hypothesis Statement

9.07- The Cutoff Score

9.08- The Alpha or Significance Level

9.09- The p-Value Approach

9.10- Effect Size

9.11- Cohen's d as a Measure of Effect Size

9.12- Decision Error

9.13- Assumptions

9.14- Power of a Test

9.15- Steps of Hypothesis Testing

9.16- Case Study: Attention Span

**10- ****Single-Sample Hypothesis Testing**

10.01- Steps of Hypothesis Testing

10.02- Stating the Hypothesis

10.03- Summary of Logic

10.04- Testing a Hypothesis About the Mean

10.05- Large Sample Testing Using the z-Test

10.06- P-Value Approach

10.07- Small Sample Testing Using the t-Test

10.08- P-Value Approach

10.09- Testing a Hypothesis About a Proportion

10.10- Hypothesis Testing Steps Summary

10.11- Case Study: Autism Prevalence

**11- ****Two-Sample Hypothesis Testing**** **

11.01- Comparisons of Means

11.02- The Standard Error of the Mean

11.03- Large Sample Testing Using the z-Test

11.04- Small Sample Testing Using the t-Test

11.05- Testing a Hypothesis about Two Means--Independent Samples

11.06- P-Value Approach

11.07- Effect Size

11.08- Confidence Interval for the Difference between Two Means--Independent Samples

11.09- Testing a Hypothesis about Two Means--Dependent Samples

11.10- Confidence Interval for the Difference between Two Means--Dependent Samples

11.11- Testing a Hypothesis about Two Proportions

11.12- Case Study: Online vs. Traditional Classroom Environments

**12- ****ANOVA and the F-distribution**

12.01- The F-Distribution

12.02- Assumptions of the ANOVA Model

12.03- The F-Statistic

12.04- Using the F-Table

12.05- One-way ANOVA

12.06- Understanding and Calculating Effect Size: R2

12.07- Three-Sample ANOVA

12.08- Post-hoc Testing for Three or More Samples

12.09- The Logic and Interpretation of Within-Groups ANOVA

12.10- Two-Way ANOVA--Factorial Designs

12.11- ANOVA Summary

12.12- Case Study: The Flipped Classroom Study

**13- ****Tests for Goodness of Fit and Independence**

13.01- When Would I Use Chi-Square?

13.02- Goodness of Fit Test

13.03- Test of Independence

13.04- The Chi-Square Distribution

13.05- The Chi-Square Statistic

13.06- Using the Chi-Square Table

13.07- Chi-Square Tests Overview

13.08- Goodness of Fit Test

13.09- Test of Independence

13.10- Case Study: Sleep Patterns among Adults in Different Family Types

**14- ****Correlation and Regression**

14.01- What Are Correlation and Regression?

14.02- Types of Correlation Coefficient

14.03- Strength of a Correlation

14.04- Direction of a Correlation

14.05- Visualizing the Correlation with a Scatterplot

14.06- Calculating Pearson's r

14.07- The Coefficient of Determination

14.08- Rank Correlation

14.09- Significance of a Correlation

14.10- Correlation and Causality

14.11- Simple Linear Regression

14.12- The Standard Error of the Estimate

14.13- Case Study: Do Guns Make a Nation Safer?

**Reference Tables**

**Appendix: Two-Way Non-Parametric Tests**

-** **Procedure: Tests of Ranked Data

- Kruskal-Wallis H Test

- Mann-Whitney U Test

- Wilcoxon Signed-Rank Test

- The Friedman Test

**R Module - Basics of R**

1. Preface

2. Getting Started in R

3. Data in R

4. Tidy Data

5. Graphics in R

**R Module - Statistical Analyses in R**

- Descriptive Statistics in R

- The Normal Distribution in R

- Probability in R

- Discrete Probability Distributions in R

- Normal Probability Distributions in R

- Four Distributions: z, t, chi-square, and F in R

- Confidence Intervals in R

- Single-Sample Hypothesis Testing in R

- Two-Sample Hypothesis Testing in R

- ANOVA in R

- Goodness of Fit Tests in R

- Correlation and Regression in R

- Non-Parametric Tests in R