Straightforward Statistics

Straightforward Statistics is written in plain language and connects material in a clear, logical manner to help students across the social and behavioral sciences develop a "big picture" understanding of foundational statistics. Each new chapter is purposefully connected with the previous chapter for a gradual accrual of knowledge from simple to more complex concepts-this effective, cumulative approach to statistics through logical transitions eases students into statistics and prepares them for success in more advanced quantitative coursework and their own research.

Table of Contents:
Preface Acknowledgments About the Author Chapter 1: Introduction to Statistics What Is Statistics? Population Versus Sample Descriptive Statistics and Inferential Statistics Sampling a Population Random Sampling Methods Simple Random Sampling Systematic Sampling Stratified Sampling Cluster Sampling Scales of Measurement Nominal Scale Ordinal Scale Interval Scale Ratio Scale Variable Classifications Discrete Versus Continuous Variables Independent Variables Versus Dependent Variables Required Mathematical Skills for This Course Statistical Notation Exercise Problems Solutions With EXCEL Step-by-Step Instructions When Needed Chapter Resources What You Learned Key Words Learning Assessment Chapter 2: Summarizing and Organizing Data What You Know and What Is New Frequency Distribution Table Organizing and Summarizing Categorical Variables Organizing and Summarizing Numerical Variables Graphs Bar Graphs and Histograms Pie Charts Common Distribution Shapes Uniform Distribution Normal Distribution Skewed Distribution EXCEL Step-by-Step Instruction for Calculating ?X from Frequency Table and Constructing a Bar Graph Exercise Problems Solutions Chapter Resources What You Learned Key Words Learning Assessment Chapter 3: Descriptive Statistics What You Know and What Is New Measures of Central Tendency Mode Median Mean Measures of Variability Range Variance and Standard Deviation for a Population Variance and Standard Deviation for a Sample Boxplot: 5-Number Summary Exercise Problems Solutions With EXCEL Step-by-Step Instructions Chapter Resources What You Learned Key Words Learning Assessment Chapter 4: Standard Z Scores What You Know and What Is New Standard Z Scores Z Scores for a Population Z Scores for a Sample Empirical Rule for Variables With a Normal Distribution Exercise Problems Solutions Chapter Resources What You Learned Key Words Learning Assessment Chapter 5: Basic Principles of Probability What You Know and What Is New Basic Terms and Mathematical Operations in Probability Basic Terms in Probability Mathematical Operations for Probabilities Binomial Probability Distribution Practical Probability Application: Winning the Mega-Million Lottery The Dice Game Linkage Between Probability and Z Score in Normal Distribution Probabilities, Z Scores, and Raw Scores Exercise Problems Solutions Chapter Resources What You Learned Key Words Learning Assessment Chapter 6: The Central Limit Theorem What You Know and What Is New Sampling Error Sampling Distribution of the Sample Means and the Central Limit Theorem The Law of Large Numbers Relationships Between Sample Means and the Population Mean Exercise Problems Solutions Chapter Resources What You Learned Key Words Learning Assessment Chapter 7: Hypothesis Testing What You Know and What Is New Type I Error and Type II Error The Four-Step Process to Conduct a Hypothesis Test Step 1: Explicitly State the Pair of Hypotheses Step 2: Identify the Rejection Zone for the Hypothesis Test Step 3: Calculate the Test Statistic Step 4: Make the Correct Conclusion Examples of the Four-Step Hypothesis Test in Action Directional Versus Non-Directional Hypothesis Testing Exercise Problems Solutions Chapter Resources What You Learned Key Words Learning Assessment Chapter 8: One-Sample t Test When Sigma Is Unknown What You Know and What Is New The Unknown Sigma and Conducting the One-Sample t Test The t-Distribution, a Specific Curve for Every Degree of Freedom Confidence Intervals Point Estimate Interval Estimate Exercise Problems Solutions With EXCEL Step-by-Step Instructions Chapter Resources What You Learned Key Words Learning Assessment Chapter 9: Independent Samples t Tests What You Know and What Is New Introducing Independent Samples and the Decision Rule on Equal Variances Decision Rule for Equal Variances Assumed Versus Equal Variances Not Assumed Equal Variances Assumed Equal Variances Not Assumed Using SPSS to Run Independent-Samples t Tests Confidence Intervals of the Mean Difference Effect Sizes Exercise Problems Solutions Chapter Resources What You Learned Key Words Learning Assessment Chapter 10: Dependent-Sample t Test What You Know and What Is New Introducing Dependent-Sample t Tests Calculations and the Hypothesis-Testing Process in Dependent-Sample t Tests Mean, Standard Deviation, and Standard Error of the Differences Hypothesis Testing for Dependent-Sample t Tests Confidence Interval of the Differences Effect Size for the Dependent-Sample t Test Using SPSS to Run Dependent-Sample t Tests Exercise Problems Solutions Chapter Resources What You Learned Key Words Learning Assessment Chapter 11: Correlation What You Know and What Is New Pearson’s Correlation Pearson’s Correlation Formulas Describing and Interpreting Pearson’s r Showing the Pearson’s Correlation in Action Hypothesis Testing for the Pearson’s Correlation Interpretations and Assumptions of Pearson’s Correlation Interpretations of Pearson’s Correlation Assumptions of Pearson’s Correlation Special Types of Correlation Spearman’s Rank Correlation Partial Correlation Formula Point Biserial Correlation EXCEL Step-by-Step Instruction for Constructing a Scatterplot EXCEL Step-by-Step Instruction on Calculating Pearson’s r Exercise Problems Solutions Chapter Resources What You Learned Key Words Learning Assessment Chapter 12: Simple Regression What You Know and What Is New Y-Intercept and Slope Hypothesis Testing With Simple Regression Standard Error of the Estimate The Mathematical Relationship Between Pearson’s r and the Regression Slope, b Assumptions for Simple Regression Step-by-Step Instructions on SPSS Exercise Problems Solutions Chapter Resources What You Learned Key Words Learning Assessment Chapter 13: One-Way Analysis of Variance What You Know and What Is New Introducing ANOVA Between-Group Variance and Within-Group Variance Sum of Squares Between Sum of Squares Within Degrees of Freedom for Between Groups (dfB) and Within Groups (dfW) Hypothesis Testing With ANOVA Post Hoc Comparisons Statistical Assumptions of an ANOVA Effect Size for One-Way ANOVA Step-by-Step Instructions for Using SPSS to Run an ANOVA Exercise Problems Solutions Chapter Resources What You Learned Key Words Learning Assessment Chapter 14: Chi-Square Tests for Goodness-of-Fit and Independence What You Know and What Is New The Chi-Square Expected Frequency Expected Frequency Under a One-Way Frequency Table Expected Frequency Under a Two-Way Contingency Table Goodness-of-Fit Tests Hypothesis Testing With the Chi-Square Goodness-of-Fit Test Chi-Square for Independence Hypothesis Testing With the Chi-Square Test for Independence Exercise Problems Solutions Chapter Resources What You Learned Key Words Learning Assessment Appendix A. The Standard Normal Distribution Table (Z Table) Appendix B. The t-Distribution Table (t Table) Appendix C. The F Table Appendix D. The Critical Values of Pearson′s Correlation Table (r Table) Appendix E. The Cirtical Values for Spearman′s Rank Correlation Table (rS Table) Appendix F. The Critical Values for the Point Biserial Correlation Table (rpbi Table) Appendix G. The Critical Values of the Studentized Range Distribution Table (q Table) Appendix H. The Critical Values for the Chi-Square Tests (Chi2 Table) Answers to the Learning Assessments Glossary References Index

About the Author :
Chieh-Chen Bowen is an Associate Professor in the Department of Psychology at Cleveland State University. She received her Ph.D. in Industrial and Organizational Psychology and a doctoral minor in Statistics from Penn State. She teaches undergraduate and graduate level Statistics, Personnel Psychology, Job Analysis, and Performance Management. Her research interests are comparing cross-cultural management practices, investigating women’s issues in the workplace, and validating personality questionnaires for employee selection. When she is not teaching or doing research, she can be found providing expert witness consulting services to attorneys who are involved in employment discrimination cases. On her days off, she works on figuring out the probability of a black-and-white cat selectively shedding only white fur on navy blue carpet while shedding only black fur on white ceramic tiles.

Review :
"This book does an admirable job of presenting the rationale for the formulas, which should help the student understand the material more deeply. Additionally, the examples used by the author do a nice job of helping students walk through the process of applying the formulas to address research hypotheses." "I have been impressed with the author’s ability to explain statistical constructs in a straightforward manner."