Preface to the Instructor 

xi  
Introduction to the Student 

xix  

Displaying the Order in a Group Of Numbers 


1  (34) 

The Two Branches of Statistical Methods 


2  (1) 


2  (4) 

Box 11: Important Trivia for Poetic Statistics Students 


5  (1) 


6  (6) 

Box 12: Math Anxiety, Statistics Anxiety, and Yon: A Message, forThose of you Who Are Truly Worried about this Course 


10  (2) 


12  (6) 

Shapes of Frequency Distributions 


18  (4) 

Controversy: Misleading Graphs 


22  (4) 

Box 13: Gender, Ethnicity, and Math Performance 


24  (2) 

Frequency Tables, Histograms, and Frequency Polygons in Research Articles 


26  (1) 


27  (1) 


28  (1) 

Example WorkedOut Computational Problems 


28  (1) 


29  (6) 

The Mean, Variance, Standard Deviation, and Z Scores 


35  (34) 


35  (4) 

Other Measures of Central Tendency 


39  (4) 

The Variance and the Standard Deviation 


43  (8) 


51  (7) 

Box 21: The Sheer Joy (Yes, Joy) of Statistical Analysis 


52  (6) 

Controversy: The Tyranny of the Mean 


58  (3) 

The Mean and Standard Deviation in Research Articles 


61  (1) 


62  (1) 


63  (1) 

Example WorkedOut Computational Problems 


63  (2) 


65  (4) 


69  (44) 

Graphing Correlations: The Scatter Diagram 


70  (5) 


75  (5) 

The Degree of Linear Correlation: The Correlation Coefficient 


80  (8) 

Box 31: Galton: Gentleman Genius 


82  (6) 

Correlation and Causality 


88  (4) 

Box 32: Illusory Correlation: When You Know Perfectly Well that If It's Big, It's Fatand you are Perfectly Wrong 


91  (1) 

Issues in Interpreting the Correlation Coefficient 


92  (3) 

Controversy: What Is a Large Correlation? 


95  (1) 

Correlation in Research Articles 


96  (2) 


98  (1) 


99  (1) 

Example WorkedOut Computational Problems 


99  (2) 


101  (8) 

Chapter Appendix: Hypothesis Tests and Power for the Correlation Coefficient 


109  (4) 


113  (44) 

Predictor and Criterion Variables 


114  (1) 

Prediction Using Z Scores 


114  (3) 

RawScore Prediction Using the ZScore Prediction Model 


117  (2) 

RawScore Prediction Using the Direct RawScore Prediction Model 


119  (6) 


125  (3) 

Error and Proportionate Reduction in Error 


128  (8) 


136  (2) 

Limitations of Regression 


138  (1) 

Controversy: Comparing Predictors 


139  (1) 

Box 41: Clinical Versus Statistical Prediction 


139  (1) 

Prediction in Research Articles 


140  (3) 


143  (1) 


144  (1) 

Example WorkedOut Computational Problems 


144  (3) 


147  (10) 

Some Key Ingredients for Inferential Statistics: The Normal Curve, Probability, and Population Versus Sample 


157  (32) 


158  (11) 

Box 51: De Moivre, the Eccentric Stranger Who Invented the Normal Curve 


159  (10) 


169  (4) 

Box 52: Pascal Begins Probability Theory at the Gambling Table, then Learns to Bet on God 


170  (3) 


173  (4) 

Box 53: Surveys, Polls, and 1948's Costly ``Free Sample'' 


176  (1) 

Controversies: Is the Normal Curve Really Normal?, What Does Probability Really Mean?, and Using Nonrandom Samples 


177  (3) 

Normal Curves, Probabilities, Samples, and Populations in Research Articles 


180  (1) 


181  (1) 


182  (1) 

Example WorkedOut Computational Problems 


182  (2) 


184  (3) 

Chapter Appendix: Probability Rules and Conditional Probabilities 


187  (2) 

Introduction to Hypothesis Testing 


189  (28) 

A HypothesisTesting Example 


190  (1) 

The Core Logic of Hypothesis Testing 


191  (1) 

The HypothesisTesting Process 


191  (8) 

OneTailed and TwoTailed Hypothesis Tests 


199  (5) 

Controversy: Should Significance Tests Be Banned? 


204  (3) 

Box 61: To Be or Not to BeBut Can Not Being Be? The Problem of Whether and When to Accept the Null Hypothesis 


206  (1) 

Hypothesis Tests in Research Articles 


207  (1) 


208  (1) 


209  (1) 

Example WorkedOut Computational Problems 


209  (1) 


210  (7) 

Hypothesis Tests With Means of Samples 


217  (36) 

The Distribution of Means 


217  (9) 

Hypothesis Testing with a Distribution of Means 


226  (7) 

Box 71: More about Polls: Sampling Errors and Errors in Thinking about Samples 


227  (6) 

Estimation, Standard Errors, and Confidence Intervals 


233  (5) 

Controversy: Confidence Intervals or Significance Tests? 


238  (2) 

Hypothesis Tests about Means of Samples, Standard Errors, and Confidence Intervals in Research Articles 


240  (2) 


242  (1) 


243  (1) 

Example WorkedOut Computational Problems 


244  (1) 


245  (8) 

Making Sense of Statistical Significance: Effect Size, Decision Error, and Statistical Power 


253  (46) 


254  (7) 

Box 81: Effect Sizes for Relaxation and Meditation: A Restful MetaAnalysis 


259  (2) 


261  (3) 


264  (7) 

What Determines the Power of a Study? 


271  (12) 

Box 82: The Power of Typical Psychology Experiments 


279  (4) 

The Role of Power When Planning a Study 


283  (1) 

The Importance of Power When Evaluating the Results of a Study 


284  (3) 

Controversy: Statistical Significance Controversy ContinuedEffect Size Versus Statistical Significance 


287  (2) 

Effect Size, Decision Errors, and Power in Research Articles 


289  (2) 


291  (1) 


292  (1) 

Example WorkedOut Computational Problems 


292  (1) 


293  (6) 

Introduction to the t Test 


299  (42) 

The t Test For a Single Sample 


300  (12) 

Box 91: William S. Gosset, Alias ``Student'': Not a Mathematician, but a Practical Man 


301  (11) 

The t Test for Dependent Means 


312  (10) 


322  (1) 

Effect Size and Power for the t Test for Dependent Means 


323  (3) 

Controversy: Advantages and Disadvantages of RepeatedMeasures Designs 


326  (1) 

Box 92: The Power of Studies Using Difference Scores: How the Lanarkshire Milk Experiment Could Have Been Milked for More 


327  (1) 

t Tests in Research Articles 


327  (2) 


329  (1) 


329  (1) 

Example WorkedOut Computational Problems 


329  (2) 


331  (10) 

The t Test For Independent Means 


341  (36) 

The Distribution of Differences between Means 


342  (7) 

Hypothesis Testing With a t Test for Independent Means 


349  (7) 

Assumptions of the t Test for Independent Means 


356  (3) 

Box 101: Monte Carlo Methods: When Mathematics Becomes Just an Experiment and Statistics Depend on a Game of Chance 


357  (2) 

Effect Size and Power for the t Test for Independent Means 


359  (3) 

Controversy: The Problem of Too Many t Tests 


362  (2) 

The t Test for Independent Means in Research Articles 


364  (2) 


366  (1) 


366  (1) 

Example WorkedOut Computational Problems 


366  (3) 


369  (8) 

Introduction to the Analysis Of Variance 


377  (40) 

Basic Logic of the Analysis of Variance 


378  (8) 

Box 111: Sir Ronald Fisher, Caustic Genius of Statistics 


384  (2) 

Carrying Out an Analysis of Variance 


386  (8) 

Hypothesis Testing with the Analysis of Variance 


394  (4) 

Assumptions in the Analysis of Variance 


398  (2) 


400  (4) 

Controversy: Omnibus Tests versus Planned Comparisons 


404  (1) 

Analyses of Variance in Research Articles 


405  (1) 


406  (1) 


407  (1) 

Example WorkedOut Computational Problems 


407  (2) 


409  (8) 

The Structural Model in the Analysis Of Variance 


417  (34) 

Principles of the Structural Model 


418  (5) 

Box 121: Analysis of Variance as a Way of Thinking About the World 


421  (2) 

Using the Structural Model to Figure an Analysis of Variance 


423  (5) 

Assumptions in the Analysis of Variance with Unequal Sample Sizes 


428  (3) 


431  (2) 

Effect Size and Power for the Analysis of Variance 


433  (4) 

Controversy: The Independence Assumption and the Unit of Analysis Question 


437  (2) 

Structural Model Analysis of Variance and PostHoc Comparisons in Research Articles 


439  (1) 


439  (2) 


441  (1) 

Example WorkedOut Computational Problems 


441  (3) 


444  (7) 

Factorial Analysis of Variance 


451  (56) 

Basic Logic of Factorial Designs and Interaction Effects 


452  (4) 

Recognizing and Interpreting Interaction Effects 


456  (7) 

Basic Logic of the TwoWay Analysis of Variance 


463  (4) 

Box 131: Personality and Situational Influences on Behavior: An Interaction Effect 


466  (1) 

Figuring a TwoWay Analysis of Variance 


467  (13) 

Power and Effect Size in the Factorial Analysis of Variance 


480  (3) 

Extensions and Special Cases of the Factorial Analysis of Variance 


483  (2) 

Controversy: Unequal Cell Sizes and Dichotomizing Numeric Variables 


485  (2) 

Factorial Analysis of Variance Results in Research Articles 


487  (2) 


489  (1) 


490  (1) 

Example WorkedOut Computational Problems 


490  (3) 


493  (14) 


507  (36) 

The ChiSquare Statistic and the ChiSquare Test for Goodness of Fit 


509  (8) 

Box 141: Karl Pearson, Inventor of ChiSquare and Center of Controversy 


510  (7) 

The ChiSquare Test for Independence 


517  (9) 

Assumptions for ChiSquare Tests 


526  (1) 

Effect Size and Power for ChiSquare Tests for Independence 


526  (4) 

Controversy: The Minimum Expected Frequency 


530  (1) 

ChiSquare Tests in Research Articles 


531  (1) 


532  (1) 


532  (1) 

Example WorkedOut Computational Problems 


533  (3) 


536  (7) 

Strategies When Population Distributions Are Not Normal: Data Transformations and RankOrder Tests 


543  (26) 

Assumptions in the Standard HypothesisTesting Procedures 


544  (1) 


545  (5) 


550  (5) 


555  (1) 

Controversy: Computer Intensive Methods 


556  (3) 

Data Transformations and RankOrder Tests in Research Articles 


559  (2) 

Box 151: Where Do Random Numbers Come Front? 


560  (1) 


561  (1) 


561  (1) 

Example WorkedOut Computational Problems 


562  (1) 


562  (7) 

Integrating What You Have Learned: The General Linear Model 


569  (30) 

The Relationships Between Major Statistical Methods 


569  (1) 

Review of the Principles of Multiple Regression 


570  (1) 


571  (2) 

The General Linear Model and Multiple Regression 


573  (1) 

Bivariate Regression and Correlation as Special Cases of Multiple Regression 


573  (1) 

The t Test as a Special Case of the Analysis of Variance 


574  (4) 

Box 761: The Golden Age of Statistics: Four Guys around London 


575  (3) 

The t Test as a Special Case of the Significance Test for the Correlation Coefficient 


578  (5) 

The Analysis of Variance as a Special Case of the Significance Test of the Multiple Regression 


583  (5) 

Choice of Statistical Tests 


588  (3) 

Box 162: Two Women Make a Point about Gender and Statistics 


589  (2) 

Controversy: Whay is Causality? 


591  (1) 


592  (1) 


593  (1) 


594  (5) 

Making Sense of Advanced Statistical Procedures in Research Articles 


599  (40) 

Brief Review of Multiple Regression 


600  (1) 

Hierarchial and Stepwise Multiple Regression 


600  (5) 


605  (1) 


606  (2) 


608  (2) 


610  (5) 

Procedures that Compare Groups and Independent and Dependent Variables 


615  (1) 

Analysis of Covariance (ANCOVA) 


616  (1) 

Multivariate Analysis of Variance (MANOVA) and Multivariate Analysis of Covariance (MANCOVA) 


617  (1) 

Overview of Statistical Techniques 


618  (1) 

Controversy: Should Statistics Be Controversial? 


619  (3) 

Box 171: The Forced Partnership of Fisher and Pearson 


620  (2) 

How to Read Results Using Unfamiliar Statistical Techniques 


622  (1) 


623  (1) 


624  (1) 


624  (15) 
Appendix A Tables 

639  (8) 

Table A1 Normal Curve Areas: Percentage of the Normal Curve between the Mean and the Z Scores Shown 


639  (3) 

Table A2 Cutoff Scores for the t Distribution 


642  (1) 

Table A3 Cutoff Scores for the F Distribution 


643  (3) 

Table A4 Cutoff Scores for the ChiSquare Distribution 


646  (1) 

Table A5 Index to Power Tables and Tables Giving Number of Participants Needed for 80% Power 


646  (1) 
Answers To Set I Practice Problems 

647  (30) 
Glossary 

677  (8) 
Glossary of Symbols 

685  (2) 
References 

687  (10) 
Index 

697  