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Part one OVERVIEW1

CHAPTER 1 Statistics and Scientific Method3

Introduction3

Methods of Knowing4

Definitions6

An Overall Example：Mode of Presentation and Retention7

Scientific Research and Statistics9

Random Sampling9

Descriptive and Inferential Statistics10

Using Computers in Statistics10

Statistics and the “Real World”11

WHAT IS THE TRUTH？Data，Data，Where Are the Data？12

WHAT IS THE TRUTH？Authorities Are Nice，But…13

WHAT IS THE TRUTH？Data，Data，What Are the Data？-114

WHAT IS THE TRUTH？Data，Data，What Are the Data？-215

Summary17

Important Terms17

Questions and Problems17

Web Connection20

Part two DESCRIPTIVE STATISTICS21

CHAPTER 2 Basic Mathematical and Measurement Concepts23

Study Hints for the Student23

Mathematical Notation24

Summation25

Measurement Scales：Nominal，Ordinal，Interval，and Ratio Scales27

Nominal Scales27

Ordinal Scales28

Interval Scales29

Ratio Scales29

Measurement Scales in the Behavioral Sciences31

Continuous and Discrete Variables31

Real Limits of a Continuous Variable32

Significant Figures33

Rounding34

Summary35

Important Terms35

Questions and Problems35

Notes36

Web Connection37

CHAPTER 3 Frequency Distributions38

Introduction：Ungrouped Frequency Distributions38

Grouping Scores40

Constructing a Frequency Distribution of Grouped Scores41

Relative Frequency，Cumulative Frequency，and Cumulative Percentage Distributions45

Percentiles46

Computation of Percentile Points47

Percentile Rank50

Computation of Percentile Rank50

Graphing Frequency Distributions53

The Bar Graph53

The Histogram55

The Frequency Polygon56

The Cumulative Percentage Curve56

Shapes of Frequency Curves57

Exploratory Data Analysis58

Stem and Leaf Diagrams58

WHAT IS THE TRUTH？Stretch the Scale，Change the Tale60

Summary62

Important Terms62

Questions and Problems62

Web Connection65

CHAPTER 4 Measures of Central Tendency and Variability66

Introduction66

Measures of Central Tendency：Arithmetic Mean，Median，and Mode67

The Arithmetic Mean67

The Overall Mean70

The Median72

The Mode74

Measures of Central Tendency and Symmetry75

Measures of Variability：Range，Standard Deviation，and Variance76

The Range76

The Standard Deviation76

The Variance82

Summary82

Important Terms82

Questions and Problems82

Notes85

Web Connection85

CHAPTER 5 The Normal Curve and Standard Scores86

Introduction86

The Normal Curve87

Area Contained Under the Normal Curve88

Standard Scores （z Scores）88

Characteristics of z Scores91

Finding Areas Corresponding to Any Raw Score92

Finding the Raw Score Corresponding to a Given Area97

Summary100

Important Terms100

Questions and Problems100

Web Connection102

CHAPTER 6 Correlation103

Introduction103

Relationships104

Linear Relationships104

Positive and Negative Relationships107

Perfect and Imperfect Relationships108

Correlation111

The Linear Correlation Coefficient Pearson r112

Other Correlation Coefficients120

Effect of Range on Correlation124

Effect of Extreme Score125

Correlation Does Not Imply Causation125

WHAT IS THE TRUTH？“Good Principal = Good Elementary School，” or Does It？126

Summary127

Important Terms128

Questions and Problems128

Web Connection133

CHAPTER 7 Linear Regression134

Introduction134

Prediction and Imperfect Relationships135

Constructing the Least-Squares Regression Line：Regression of Y on X137

Regression of X on Y143

Measuring Prediction Errors：The Standard Error of Estimate146

Considerations in Using Linear Regression for Prediction149

Relation Between Regression Constants and Pearson r150

Multiple Regression and Multiple Correlation151

Summary155

Important Terms156

Questions and Problems156

Web Connection158

Part three INFERENTIAL STATISTICS159

CHAPTER 8 Random Sampling and Probability161

Introduction161

Random Sampling162

Techniques for Random Sampling164

Sampling With or Without Replacement165

Probability166

Some Basic Points Concerning Probability Values167

Computing Probability167

The Addition Rule168

The Multiplication Rule173

Multiplication and Addition Rules183

Probability and Normally Distributed Continuous Variables186

WHAT IS THE TRUTH？“Not Guilty，I’m a Victim of Coincidence”：Gutsy Plea or Truth？189

WHAT IS THE TRUTH？Sperm Count Decline-Male or Sampling Inadequacy？190

WHAT IS THE TRUTH？A Sample of a Sample191

Summary193

Important Terms193

Questions and Problems193

Notes196

Web Connection196

CHAPTER 9 Binomial Distribution197

Introduction197

Definition and Illustration of the Binomial Distribution197

Generating the Binomial Distribution from the Binomial Expansion200

Using the Binomial Table202

Summary211

Important Terms211

Questions and Problems211

Notes213

Web Connection213

CHAPTER 10 Introduction to Hypothesis Testing Using the Sign Test214

Introduction214

An Experiment：Marijuana and the Treatment of AIDS Patients215

Repeated Measures Design217

Alternative Hypothesis （H1）218

Null Hypothesis （H0）218

Decision Rule （α Level）218

Evaluating the Marijuana Experiment Using the Binomial Distribution219

Type Ⅰ and Type Ⅱ Errors220

Alpha Level and the Decision Process221

Evaluating the Tail of the Distribution223

One-and Two-Tailed Probability Evaluations225

Size of Effect：Significant Versus Important232

WHAT IS THE TRUTH？Chance or Real Effect-1？232

WHAT IS THE TRUTH？Chance or Real Effect-2？234

WHAT IS THE TRUTH？“No Product Is Better Than Our Product”235

WHAT IS THE TRUTH？Anecdotal Reports Versus Systematic Research236

Summary238

Important Terms239

Questions and Problems239

Notes242

Web Connection242

CHAPTER 11 Power243

Introduction243

What Is Power？244

Pnull and Preal244

Preal：A Measure of the Size and Direction of the Real Effect245

Power Analysis of the AIDS Experiment246

Effect of N and Size of Real Effect247

Power and Beta （β）251

Power and Alpha （α）252

Alpha-Beta and Reality253

Interpreting Nonsignificant Results253

Calculation of Power254

WHAT IS THE TRUTH？Astrology and Science259

Summary261

Important Terms261

Questions and Problems261

Notes262

Web Connection262

CHAPTER 12 Sampling Distributions，Sampling Distribution of the Mean，the Normal Deviate （z） Test263

Introduction263

Sampling Distributions264

Generating Sampling Distributions264

The Normal Deviate （z） Test268

An Experiment：Evaluating the Reading Program at the Local Public Schools268

Sampling Distribution of the Mean268

The Reading Proficiency Experiment Revisited275

Alternative Solution Using zobt and the Critical Region for Rejection of H0277

Conditions Under Which the z Test Is Appropriate282

Power and the z Test282

Summary290

Important Terms290

Questions and Problems290

Web Connection292

CHAPTER 13 Student’s t Test for Single Samples293

Introduction293

Comparison of the z and t Tests294

An Experiment：Technique for Increasing Early Speaking in Children294

The Sampling Distribution of t295

Degrees of Freedom296

t and z Distributions Compared297

First Word Utterances Experiment Revisited298

Calculating tobt from Original Scores299

Conditions Under Which the t Test Is Appropriate304

t Distribution：Confidence Intervals for the Population Mean304

Construction of the 95onfidence Interval305

Example：Estimating the Mean IQ of Professors at a University306

General Equations for Any Confidence Interval307

Testing the Significance of Pearson r309

Summary312

Important Terms313

Questions and Problems313

Notes315

Web Connection316

CHAPTER 14 Student’s t Test for Correlated and Independent Groups317

Introduction318

Student’s t Test for Correlated Groups319

An Experiment：Brain Stimulation and Eating319

Comparison Between the t Test for Correlated Groups and the t Test for Single Samples320

Brain Stimulation Experiment Revisited and Analyzed321

t Test for Correlated Groups and Sign Test Compared326

Assumptions Underlying the t Test for Correlated Groups327

z and t Tests for Independent Groups327

Independent Groups Design327

z Test for Independent Groups328

An Experiment：Hormone X and Sexual Behavior328

The Sampling Distribution of the Difference Between Sample Means （X1-X2）329

An Experiment：Hormone X Experiment Revisited330

Student’s t Test for Independent Groups331

Comparing the Equations for zobt and tobt331

Analyzing the Hormone X Experiment with the t Test for Independent Groups333

Calculating tobt When n1 = n2334

Assumptions Underlying the t Test for Independent Groups338

Violation of the Assumptions of the t Test for Independent Groups339

Size of Effect339

Power of the t Test341

Correlated Groups and Independent Groups Designs Compared342

Summary345

Important Terms346

Questions and Problems347

Notes352

Web Connection353

CHAPTER 15 Introduction to the Analysis of Variance354

Introduction：The F Distribution354

F Test and the Analysis of Variance （ANOVA）356

Overview of the One-Way Analysis of Variance Technique357

Within-Groups Variance Estimate，s W2359

Between-Groups Variance Estimate，s B2360

The F Ratio362

Analyzing Data with the ANOVA Technique362

An Experiment：Different Situations and Stress362

Logic Underlying the One-Way ANOVA366

The Relationship Between the Analysis of Variance and the t Test370

Example：Dating—Sorority Versus Dormitory Women370

Assumptions Underlying the Analysis of Variance372

Size of Effect373

Power of the Analysis of Variance373

Power and N374

Power and the Real Effect of the Independent Variable374

Power and Sample Variability374

WHAT IS THE TRUTH？Much Ado About Almost Nothing375

Summary376

Important Terms377

Questions and Problems377

Web Connection380

CHAPTER 16 Multiple Comparisons381

Introduction381

A Priori，or Planned，Comparisons382

A Posteriori，or Post Hoc，Comparisons384

The Tukey Honestly Significant Difference （HSD） Test385

The Newman-Keuls Test386

HSD and Newman-Keuls Tests with Unequal n391

Comparison Between Planned Comparisons，Tukey’s HSD，and the Newman-Keuls Tests391

Summary392

Important Terms392

Questions and Problems393

Notes393

Web Connection394

CHAPTER 17 Introduction to Two-Way Analysis of Variance395

Introduction to the Two-Way Analysis of Variance-Qualitative Presentation395

Quantitative Presentation of the Two-Way Analysis of Variance399

Within-Cells Variance Estimate （sw2）400

Row Variance Estimate （sR 2）402

Column Variance Estimate （sC2）404

Row × Column Variance Estimate （sRC2）405

Computing F Ratios406

Analyzing an Experiment with Two-Way ANOVA406

An Experiment：Effect of Exercise on Sleep406

Interpreting the Results410

Multiple Comparisons420

Assumptions Underlying the Two-Way ANOVA421

Summary421

Important Terms422

Questions and Problems422

Web Connection424

CHAPTER 18 Chi-Square and Other Nonparametric Tests425

Introduction：Distinction Between Parametric and Nonparametric Tests426

Chi-Square （x2）427

Single Variable Experiments427

An Experiment：Preference for Different Brands of Light Beer427

Test of Independence Between Two Variables431

An Experiment：Political Affiliation and Attitude432

Assumptions Underlying x2440

The Wilcoxon Matched-Pairs Signed Ranks Test441

An Experiment：Promoting More Favorable Attitudes Toward Wildlife Conservation441

Assumptions of the Wilcoxon Signed Ranks Test444

The Mann-Whitney U Test444

An Experiment：The Effect of a High-Protein Diet on Intellectual Development444

Tied Ranks448

Assumptions Underlying the Mann-Whitney U Test450

The Kruskal-Wallis Test450

An Experiment：Evaluating Two Weight Reduction Programs450

Assumptions Underlying the Kruskal-Wallis Test454

WHAT IS THE TRUTH？Statistics and Applied Social Research-Useful or “Abuseful”？455

Summary457

Important Terms458

Questions and Problems458

Notes464

Web Connection464

CHAPTER 19 Review of Inferential Statistics465

Introduction465

Terms and Concepts466

Process of Hypothesis Testing467

Single Sample Designs468

z Test for Single Samples468

t Test for Single Samples469

t Test for Testing the Significance of Pearson r469

Two-Condition Experiments：Correlated Groups Design470

t Test for Correlated Groups470

Wilcoxon Matched-Pairs Signed Ranks Test471

Sign Test471

Independent Groups Design：Two Groups472

t Test for Independent Groups472

Mann-Whitney U Test473

Multigroup Experiments474

One-Way Analysis of Variance，F Test474

One-Way Analysis of Variance，Kruskal-Wallis Test477

Two-Way Analysis of Variance，F Test477

Two-Way Analysis of Variance，F Test478

Analyzing Nominal Data479

Chi-Square Test479

Choosing the Appropriate Test480

Questions and Problems482

Web Connection488

Appendixes489

A.Review of Prerequisite Mathematics491

B.Equations501

C.Answers to End-of-Chapter Questions and Problems509

D.Tables524

Glossary549

Index552