1. INTRODUCTION 

The Importance of Context: An Example 

Basic Terminology 

Selection Among Statistical Procedures 

Using Computers 

Summary 

Exercises 

2. BASIC CONCEPTS 

Scales of Measurement 

Variables 

Random Sampling 

Notation 

Summary 

Exercises 

3. DISPLAYING DATA 

Plotting Data 

StemandLeaf Displays 

Histograms 

Reading Graphs 

Alternative Methods of Planning Data 

Describing Distributions 

Using Computer Programs to Display Data 

Summary 

Exercises 

4. MEASURES OF CENTRAL TENDENCY 

The Mode 

The Median 

The Mean 

Advantages and Disadvantages of the Mode, the Median and the Mean 

Obtaining Measures of Central Tendency Using MINITAB 

A Simple Demonstrationâ€”Seeing Statistics 

Summary 

Exercises 

5. MEASURES OF VARIABILITY 

Range 

Interquartile Range and Other Range Statistics 

The Average Deviation 

The Variance 

The Standard Deviation 

Computational Formulae for the Variance and the Standard Deviation 

The Mean and the Variance as Estimators 

Boxplots: Graphical Representations of Dispersion and Extreme Scores 

Obtaining Measures of Dispersion Using JMP 

A Final Worked Example 

Seeing Statistics 

Summary 

Exercises 

6. THE NORMAL DISTRIBUTION 

The Normal Distribution 

The Standard Normal Distribution 

Setting Probable Limits on an Observation 

Measures Related to z 

Summary 

Exercises 

7. BASIC CONCEPTS OF PROBABILITY 

Probability 

Basic Terminology and Rules 

Discrete versus Continuous Variables 

Probability Distributions for Discrete Variables 

Probability Distributions for Continuous Variables 

Summary 

Exercises 

8. SAMPLING DISTRIBUTIONS AND HYPOTHESIS TESTING 

Two Simple Examples Involving Course Evaluations and Rude Motorists 

Sampling Distributions 

Hypothesis Testing 

The Null Hypothesis 

Test Statistics and Their Sampling Distributions 

Using the Normal Distribution to Test Hypotheses 

Type I and Type II Errors 

One and TwoTailed Tests 

Seeing Statistics 

A Final Worked Example 

Back to Course Evaluations and Rude Motorists 

Summary 

Exercises 

9. CORRELATION 

Scatter Diagrams 

The Relationship Between Speed and Accuracy 

The Covariance 

The Pearson Productâ€“Moment Correlation Coefficient (r) 

Correlations with Ranked Data 

Factors That Affect the Correlation 

If Something Looks Too Good To Be True, Perhaps It Is 

Testing the Significance of a Correlation Coefficient 

Intercorrelation Matrices 

Other Correlation Coefficients 

Using MINITAB and SPSS to Obtain Correlation Coefficients 

Seeing Statistics 

A Final Worked Example 

Summary 

Exercises 

10. REGRESSION 

The Relationship Between Stress and Health 

The Basic Data 

The Regression Line 

The Accuracy of Prediction 

The Influence of Extreme Values 

Hypothesis Testing in Regression 

Computer Solution Using SPSS 

Seeing Statistics 

A Final Worked Example 

Summary 

Exercises 

11. MULTIPLE REGRESSION 

Overview 

Course Evaluations Again 

Residuals 

The Visual Representation of Multiple Regression 

Hypothesis Testing 

Refining the Regression Equation 

A Second Example: Height and Weight 

A Third Example: Psychological Symptoms in Cancer Patients 

Summary 

Exercises 

12. HYPOTHESIS TESTS APPLIED TO MEANS: ONE SAMPLE 

Sampling Distribution of the Mean 

Testing Hypotheses About Means When σ Is Known 

Testing a Sample Mean When σ Is Unknown (The OneSample t Test) 

Factors That Affect the Magnitude of t and the Decision About H0. A Second Example: The Moon Illusion 

How Large Is Our Effect? Confidence Limits on the Mean 

Using JMP to Run OneSample t Tests 

A Final Worked Example 

Seeing Statistics 

Summary 

Exercises 

13. HYPOTHESIS TESTS APPLIED TO MEANS: TWO RELATED SAMPLES 

Related Samples 

An Example: Student's t Applied to Difference Scores 

A Second Example: The Moon Illusion Again 

Advantages and Disadvantages of Using Related Samples 

How Large an Effect Have We Found? Using SPSS for t Tests on Related Samples 

Summary 

Exercises 

14. HYPOTHESIS TESTS APPLIED TO MEANS: TWO INDEPENDENT SAMPLES 

Distribution of Differences Between Means 

Heterogeneity of Variance 

Nonnormality of Distributions 

A Second Example with Two Independent Samples 

Effect Size Again 

Confidence Limits on μ1â€“μ2. Use of Computer Programs for Analysis of Two Independent Sample Means 

A Final Worked Example 

Seeing Statistics 

Summary 

Exercises 

15. POWER 

The Basic Concept 

Factors That Affect the Power of a Test 

Effect Size 

Power Calculations for the OneSample t Test 

Power Calculations for Differences Between Two Independent Means 

Power Calculations for the t Test for Related Samples 

Power Considerations in Terms of Sample Size 

You Don't Have to Do It by Hand 

Seeing Statistics 

Summary 

Exercises 

16. ONE WAY ANALYSIS OF VARIANCE 

The General Approach 

The Logic of the Analysis of Variance 

Calculations for the Analysis of Variance 

Unequal Sample Sizes 

Multiple Comparison Procedures 

Violations of Assumptions 

Magnitude of Effect 

Use of JMP for a OneWay Analysis of Variance 

A Final Worked Example 

Seeing Statistics 

Summary 

Exercises 

17. FACTORIAL ANALYSIS OF VARIANCE 

Factorial Designs 

The Extension of the Eysenck Study 

Interactions 

Simple Effects 

Unequal Sample Sizes 

Measures of Effect Size 

A Second Example: Maternal Adaptation Revisited 

Using SPSS for Factorial Analysis of Variance 

Seeing Statistics 

Summary 

Exercises 

18. REPEATEDMEASURES ANALYSIS OF VARIANCE 

An Example: The Treatment of Migraine Headaches 

Multiple Comparisons 

Effect Size 

Assumptions Involved in RepeatedMeasures Designs 

Advantages and Disadvantages of RepeatedMeasures Designs 

Using SPSS to Analyze Data in a RepeatedMeasures Design 

A Final Worked Example 

Summary 

Exercises 

19. CHISQUARE 

One Classification Variable: The ChiSquare GoodnessofFit Test 

Two Classification Variables: Contingency Table Analysis 

Correction for Continuity 

ChiSquare for Larger Contingency Tables 

The Problem of Small Expected Frequencies 

The Use of ChiSquare as a Test on Proportions 

NonIndependent Observations 

MINITAB Analysis of Contingency Tables 

A Final Worked Example 

Effect Size 

Seeing Statistics 

Summary 

Exercises 

20. NONPARAMETRIC AND DISTRIBUTIONÂˇVFREE STATISTICAL TESTS 

The Mannâ€“Whitney Test 

Wilcoxon's MatchedPairs SignedRanks Test 

Kruskalâ€“Wallis OneWay Analysis of Variance 

Friedman's Rank Test for k Correlated Samples 

Summary 

Exercises 

21. CHOOSING THE APPROPRIATE ANALYSIS 

Exercises and Examples 

Appendix A: Arithmetic Review 

Appendix B: Symbols and Notation 

Appendix C: Basic Statistical Formulae 

Appendix D: Dataset 

Appendix E: Statistical Tables 

Glossary 

References 

Answers to Selected Exercises 

Index 
