Statistics for the Behavioral Sciences

Title
Copyright
About the authors
Brief Contents
Contents
Preface
Chapter 1 An Introduction to Statistics and Research Design
	The Two Branches of Statistics
		Descriptive Statistics
		Inferential Statistics
		Distinguishing Between a Sample and a Population
	How to Transform Observations into Variables
		Discrete Observations
		Continuous Observations
	Variables and Research
		Independent, Dependent, and Confounding Variables
		Reliability and Validity
	Introduction to Hypothesis Testing
		Conducting Experiments to Control for Confounding Variables
		Between-Groups Design Versus Within-Groups Design
		Correlational Research
	Next Steps: Outlier Analysis
Chapter 2 Frequency Distributions
	Frequency Distributions
		Frequency Tables
		Grouped Frequency Tables
		Histograms
		Frequency Polygons
	Shapes of Distributions
		Normal Distributions
		Skewed Distributions
	Next Steps: Stem-and-Leaf Plot
Chapter 3 Visual Displays of Data
	How to Lie with Visual Statistics
		“The Most Misleading Graph Ever Published”
		Techniques for Misleading with Graphs
	Common Types of Graphs
		Scatterplots
		Line Graphs
		Bar Graphs
		Pictorial Graphs
		Pie Charts
	How to Build a Graph
		Choosing the Appropriate Type of Graph
		How to Read a Graph
		Guidelines for Creating a Graph
		The Future of Graphs
	Next Steps: Multivariable Graphs
Chapter 4 Central Tendency and Variability
	Central Tendency
		Mean, the Arithmetic Average
		Median, the Middle Score
		Mode, the Most Common Score
		How Outliers Affect Measures of Central Tendency
		Which Measure of Central Tendency Is Best?
	Measures of Variability
		Range
		Variance
		Standard Deviation
	Next Steps: The Interquartile Range
Chapter 5 Sampling and Probability
	Samples and Their Populations
		Random Sampling
		Convenience Sampling
		The Problem with a Biased Sample
		Random Assignment
	Probability
		Coincidence and Probability
		Expected Relative-Frequency Probability
		Independence and Probability
	Inferential Statistics
		Developing Hypotheses
		Making a Decision About a Hypothesis
	Type I and Type II Errors
		Type I Errors
		Type II Errors
	Next Steps: The Shocking Prevalence of Type I Errors
Chapter 6 The Normal Curve, Standardization, and z Scores
	The Normal Curve
	Standardization, z Scores, and the Normal Curve
		The Need for Standardization
		Transforming Raw Scores into z Scores
		Transforming z Scores into Raw Scores
		Using z Scores to Make Comparisons
		Transforming z Scores into Percentiles
	The Central Limit Theorem
		Creating a Distribution of Means
		Characteristics of the Distribution of Means
		Using the Central Limit Theorem to Make Comparisons with z Scores
	Next Steps: The Normal Curve and Catching Cheaters
Chapter 7 Hypothesis Testing with z Tests
	The z Table
		Raw Scores, z Scores, and Percentages
		The z Table and Distributions of Means
	The Assumptions and Steps of Hypothesis Testing
		The Three Assumptions for Conducting Analyses
		The Six Steps of Hypothesis Testing
	An Example of the z Test
	Next Steps: Replication
Chapter 8 Confidence Intervals, Effect Size, and Statistical Power
	The New Statistics
	Confidence Intervals
		Interval Estimates
		Calculating Confidence Intervals with z Distributions
	Effect Size
		The Effect of Sample Size on Statistical Significance
		What Effect Size Is
		Cohen’s d
	Next Steps: Meta-Analysis
	Statistical Power
		The Importance of Statistical Power
		Five Factors That Affect Statistical Power
Chapter 9 The Single-Sample t Test
	The t Distributions
		Estimating Population Standard Deviation from a Sample
		Calculating Standard Error for the t Statistic
		Using Standard Error to Calculate the t Statistic
	The Single-Sample t Test
		The t Table and Degrees of Freedom
		The Six Steps of the Single-Sample t Test
		Calculating a Confidence Interval for a Single-Sample t Test
		Calculating Effect Size for a Single-Sample t Test
	Next Steps: Dot Plots
Chapter 10 The Paired-Samples t Test
	The Paired-Samples t Test
		Distributions of Mean Differences
		The Six Steps of the Paired-Samples t Test
	Beyond Hypothesis Testing
		Calculating a Confidence Interval for a Paired-Samples t Test
		Calculating Effect Size for a Paired-Samples t Test
	Next Steps: Order Effects and Counterbalancing
Chapter 11 The Independent-Samples t Test
	Conducting an Independent-Samples t Test
		A Distribution of Differences Between Means
		The Six Steps of the Independent-Samples t Test
		Reporting the Statistics
	Beyond Hypothesis Testing
		Calculating a Confidence Interval for an Independent-Samples t Test
		Calculating Effect Size for an Independent-Samples t Test
	Next Steps: The Bayesian Approach to Data Analysis
Chapter 12 One-Way Between-Groups ANOVA
	Using the F Distributions with Three or More Samples
		Type I Errors When Making Three or More Comparisons
		The F Statistic as an Expansion of the z and t Statistics
		The F Distributions for Analyzing Variability to Compare Means
		The F Table
		The Language and Assumptions for ANOVA
	One-Way Between-Groups ANOVA
		Everything About ANOVA but the Calculations
		The Logic and Calculations of the F Statistic
		Making a Decision
	Beyond Hypothesis Testing for the One-Way Between-Groups ANOVA
		R2, the Effect Size for ANOVA
		Post Hoc Tests
		Tukey HSD
	Next Steps: The Bonfferoni Test
Chapter 13 One-Way Within-Groups ANOVA
	One-Way Within-Groups ANOVA
		The Benefits of Within-Groups ANOVA
		The Six Steps of Hypothesis Testing
	Beyond Hypothesis Testing for the One-Way Within-Groups ANOVA
		R2, the Effect Size for ANOVA
		Tukey HSD
	Next Steps: Matched Groups
Chapter 14 Two-Way Between-Groups ANOVA
	Two-Way ANOVA
		Why We Use Two-Way ANOVA
		The More Specific Vocabulary of Two-Way ANOVA
		Two Main Effects and an Interaction
	Understanding Interactions in ANOVA
		Interactions and Public Policy
		Interpreting Interactions
	Conducting a Two-Way Between-Groups ANOVA
		The Six Steps of Two-Way ANOVA
		Identifying Four Sources of Variability in a Two-Way ANOVA
		Effect Size for Two-Way ANOVA
	Next Steps: Variations on ANOVA
Chapter 15 Correlation
	The Meaning of Correlation
		The Characteristics of Correlation
		Correlation Is Not Causation
	The Pearson Correlation Coefficient
		Calculating the Pearson Correlation Coefficient
		Hypothesis Testing with the Pearson Correlation Coefficient
	Applying Correlation in Psychometrics
		Reliability
		Validity
	Next Steps: Partial Correlation
Chapter 16 Regression
	Simple Linear Regression
		Prediction Versus Relation
		Regression with z Scores
		Determining the Regression Equation
		The Standardized Regression Coefficient and Hypothesis Testing with Regression
	Interpretation and Prediction
		Regression and Error
		Applying the Lessons of Correlation to Regression
		Regression to the Mean
		Proportionate Reduction in Error
	Multiple Regression
		Understanding the Equation
		Multiple Regression in Everyday Life
	Next Steps: Structural Equation Modeling (SEM)
Chapter 17 Chi-Square Tests
	Nonparametric Statistics
		An Example of a Nonparametric Test
		When to Use Nonparametric Tests
	Chi-Square Tests
		Chi-Square Test for Goodness of Fit
		Chi-Square Test for Independence
	Beyond Hypothesis Testing
		Cramér’s V, the Effect Size for Chi Square
		Graphing Chi-Square Percentages
		Relative Risk
	Next Steps: Adjusted Standardized Residuals
Chapter 18 Nonparametric Tests with Ordinal Data
	Ordinal Data and Correlation
		When the Data Are Ordinal
		The Spearman Rank-Order Correlation Coefficient
	Nonparametric Hypothesis Tests
		The Wilcoxon Signed-Rank Test
		The Mann–Whitney U Test
		The Kruskal–Wallis H Test
	Next Steps: Bootstrapping
Appendix A: Reference for Basic Mathematics
	A.1: Diagnostic Test: Skills Evaluation
	A.2: Symbols and Notation: Arithmetic Operations
	A.3: Order of Operations
	A.4: Proportions: Fractions, Decimals, and Percentages
	A.5: Solving Equations with a Single Unknown Variable
	A.6: Answers to Diagnostic Test and Self-Quizzes
Appendix B: Statistical Tables
	B.1: The z Distribution
	B.2: The t Distributions
	B.3: The F Distributions
	B.4: The Chi-Square Distributions
	B.5: The q Statistic (Tukey HSD Test)
	B.6: The Pearson Correlation Coefficient
	B.7: The Spearman Correlation Coefficient
	B.8A: Mann–Whitney U for a p Level of .05 for a One-Tailed Test
	B.8B: Mann–Whitney U for a p Level of .05 for a Two-Tailed Test
	B.9: Wilcoxon Signed-Ranks Test for Matched Pairs (T)
	B.10: Random Digits
Appendix C: Solutions to End-of-Chapter Problems
Appendix D: Check Your Learning Solutions
Appendix E: Choosing the Appropriate Statistical Test
	Category 1: Two Scale Variables
	Category 2: Nominal Independent Variable(s) and a Scale Dependent Variable
	Category 3: One or Two Nominal Variables
	Category 4: At Least One Ordinal Variable
Appendix F: Reporting Statistics
	Overview of Reporting Statistics
	Justifying the Study
	Reporting Traditional Statistics
	Reporting the “New Statistics”
Appendix G: Building Better Graphs Using Excel
Glossary
References
Index