Statistical Applications for the Behavioral Sciences

, by Laurence G. Grimm (Univ. of Illinois-Chicago)

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ISBN: 9780471509820 | 0471509825
Cover: Hardcover
Copyright: 2/1/1993

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Explains the conceptual foundations of statistical analyses (particularly inferential statistics), emphasizing the research context. Teaches students how to ''work the formulas'' by presenting cleary defined steps for dealing with statistical problems. Covers chi-square and other nonparametric tests, one/two-way and repeated-measures ANOVA, data analytic procedures such as linear correlation and regression. Boxed features highlight the topics under discussion using published and unpublished research and contain biographical sketches of luminaries in the field of statistics. Each chapter concludes with an extended summary, the relevant formulas and numerous work problems.

PART 1: BASIC CONCEPTS OF RESEARCH AND DESCRIPTIVE STATISTICS

(120)

Basic Concepts in Research

(21)

Why Study Research Design in Conjunction with Statistics?

(2)

An Overview of the Research Process

(2)

Basic Concepts in the Conduct of Research

(17)

Feeling Good and Helping Others A Study with a Confound

(4)

Summary

(1)

Work Problems

(4)

Scales of Measurement and Data Display

(23)

Measurement and Its Scales

(3)

Discrete Variables, Continuous Variables, and the Real Limits of Numbers

(4)

Some Notes on the History of Statistics

(1)

Using Tables to Organize Data

(4)

Using Graphs to Display Data

(6)

Using a Graph to Provide a Visual Display of Data

(1)

The Shape of Things to Come

(6)

Summary

(1)

Work Problems

(2)

Measures of Central Tendency

(22)

Describing a Distribution of Scores

(1)

Populations and Samples

(1)

The Rounding Rule

(1)

The Mean

(5)

The Median

(4)

The Mode

(1)

How the Shape of Distributions Affects Measures of Central Tendency

(2)

When to Use the Mean, Median, and Mode

(1)

Experimental Research and the Mean: A Glimpse of Things to Come

(7)

Learning to Control Your Heart Rate

(2)

Summary

(1)

Key Formulas for Chapter 3

(1)

Work Problems

(3)

Measures of Variability

(23)

The Importance of Measures of Variability

(1)

Range

(3)

Mean Deviation

(2)

The Variance

(6)

The Substantive Importance of the Variance

(1)

The Standard Deviation

(2)

The Origins of the Standard Deviation

(1)

Simple Transformations and Their Effect on the Mean and Variance

(1)

Deciding Which Measure of Variability to Use

(8)

Summary

(1)

Key Formulas for Chapter 4

(1)

Work Problems

(4)

The Normal Curve and Transformation: Percentiles, z Scores and T Scores

(29)

Percentile Rank

(8)

The Normal Distributions

(4)

Abraham De Moivre

101

(2)

Standard Scores: z Scores and T Scores

103

(18)

With z Scores You Can Compare Apples and Oranges

115

(1)

Summary

115

(1)

Key Formulas for Chapter 5

116

(1)

Work Problems

116

(5)

PART 2: INFERENTIAL STATISTICS: PARAMETRIC TESTS

121

(306)

Hypothesis Testing and Sampling Distributions

123

(17)

Inferential Statistics

123

(1)

Two Kinds of Inferential Procedures

124

(6)

Sampling Distributions

130

(10)

Population and Sample Distributions A Sampling Distribution of Means Summary

137

(1)

Key Formulas for Chapter 6

138

(1)

Work Problems

138

(2)

Testing the Significance of a Single Mean: The Single-Sample z and t Tests

140

(27)

The Research Context

140

(2)

Using the Sampling Distribution of Means for the Single-Sample z Test

142

(8)

The Implications of Rejecting the Null Hypothesis

150

(1)

Type I and Type II Errors

151

(2)

Is a Significant Finding ``Significant''?

153

(1)

The Statistical Test for the Mean of a Population When is Unknown: The t Distributions

154

(13)

Visual Illusions and Immaculate Perception

160

(2)

Summary

162

(1)

Key Formulas for Chapter 7

162

(1)

Work Problems

163

(4)

Directional and Nondirectional Testing of the Difference Between Two Means: The Independent-Samples t Test

167

(31)

The Research Context

167

(3)

William Gossett

169

(1)

The Independent-Samples t test

170

(14)

Can Epileptic Seizures Be Controlled by Relaxation Training?

183

(1)

Directional Tests of Significance

184

(14)

Summary

189

(1)

Key Formulas for Chapter 8

190

(1)

Work Problems

191

(7)

Testing the Difference Between Two Means: The Dependent-Samples t Test

198

(19)

The Research Context

198

(3)

The Sampling Distribution for the Dependent-Samples t Test

201

(4)

The t Distribution for Dependent-Samples

205

(3)

Comparing the Independent- and Dependent-Samples t Tests

208

(1)

The One-Tailed Test Revisited

209

(1)

An Example of the Questionable Use of a One-Tailed Dependent-Samples t Test

210

(1)

Assumptions of the Dependent-Samples t Test

210

(2)

The First Applications of the t Test

211

(1)

Summary

212

(1)

Key Formulas for Chapter 9

212

(1)

Work Problems

212

(5)

Confidence Intervals and Hypothesis Testing

217

(24)

The Research Context

217

(2)

Confidence Intervals When Q is Known

219

(2)

Sampling Distributions and Confidence Intervals

221

(2)

The Probabilistic Nature of Confidence Intervals

223

(1)

Confidence Intervals When Q is Unknown

224

(3)

Using Confidence Intervals for Hypothesis Testing

227

(14)

Where Did the Passion Go?

228

(4)

Premarital Cohabitation: A New America Institution

232

(2)

Summary

234

(1)

Key Formulas for Chapter 10

235

(1)

Work Problems

236

(5)

Power Analysis and Hypothesis Testing

241

(16)

Decision Making While Hypothesis Testing

242

(1)

Why Study Power?

243

(1)

The Size of the Treatment Effect and Power

244

(3)

Using the Power Table

247

(2)

The Bigger the Treatment Effect the Greater the Power

249

(1)

Determining the Effect Size: The Achilles Heel of the Power Analysis

250

(1)

Determining Sample Size for a Single-Sample Test

251

(2)

Failing to Reject the Null Hypothesis: Can a Power Analysis Help?

253

(4)

Psychopathy and Frontal Lobe Damage

254

(1)

Summary

255

(1)

Key Formulas for Chapter 11

255

(1)

Work Problems

256

(1)

One-Way Analysis of Variance

257

(34)

The Research Context

258

(1)

Sir Ronald Fisher

259

(1)

The Conceptual Basis of ANOVA: Sources of Variation

259

(10)

Computing the F Ratio in ANOVA

269

(6)

Testing for Statistical Significance

275

(2)

The ANOVA Summary Table

277

(1)

Reporting the Results of the ANOVA

278

(2)

Initiation Rites and Club Loyalty

278

(2)

An Example of ANOVA with Unequal Numbers of Subjects

280

(1)

Strength of Association

280

(3)

Locating the Source of Significance: The Protected t Test

283

(8)

Summary

285

(1)

Key Formulas for Chapter 12

285

(1)

Work Problems

286

(5)

Two-Way Analysis of Variance

291

(45)

The Research Context

291

(12)

The Logic of the Two-Way ANOVA

303

(2)

Definitional and Computational Formulas for the Two-Way ANOVA

305

(12)

Testing the Statistical Significance of the F Ratios

317

(4)

Do Firearms Create Aggression?

319

(2)

Strength of Association

321

(1)

Multiple Comparisons

321

(4)

Interpreting the Factors in a Two-Way ANOVA

325

(11)

Summary

325

(1)

Key Formulas for Chapter 13

326

(2)

Work Problems

328

(8)

Repeated-Measures Analysis of Variance

336

(25)

The Research Context

337

(2)

The Logic of the Repeated-Measures ANOVA

339

(3)

The Formulas for the Repeated-Measures ANOVA

342

(8)

Testing the Statistical Significance of the F Ratio

350

(1)

Interpreting the Findings

350

(1)

The ANOVA Summary Table

351

(1)

Multiple Comparisons

351

(3)

The Inverted U Relation Between Arousal and Task Performance

353

(1)

Strength of Association

354

(1)

Assumptions of the Repeated-Measures ANOVA

354

(7)

Summary

355

(1)

Key Formulas for Chapter 14

356

(1)

Work Problems

357

(4)

Linear Correlation

361

(35)

The Research Context

361

(1)

The Correlation Coefficient and Scatter Diagrams

362

(15)

Karl Pearson

364

(13)

Testing the Significance of the Pearson r

377

(5)

Maternal Cognitions and Aggressive Children

381

(1)

Factors That Can Create Misleading Correlation Coefficients

382

(14)

Summary

387

(2)

Key Formulas for Chapter 15

389

(1)

Work Problems

389

(7)

Linear Regression

396

(31)

The Research Context

396

(1)

Overview of Regression

397

(3)

Establishing the Regression Line

400

(13)

Sir Francis Galton

411

(2)

Putting It All Together: A Worked Problem

413

(5)

Why is a Prediction Equation Called a Regression Equation?

417

(1)

The Coefficient of Determination in the Context of Prediction

418

(1)

The Pitfalls of Linear Regression

419

(8)

Summary

421

(1)

Key Formulas for Chapter 16

422

(2)

Work Problems

424

(3)

PART 3: INFERENTIAL STATISTICS: NONPARAMETRIC TESTS

427

(64)

The Chi-Square Test

429

(27)

The Research Context

430

(1)

The Chi-Square Test for One-Way Designs: The Goodness-of Fit Test

431

(6)

The Chi-Square Distribution and Degrees of Freedom

437

(3)

Two-Way Designs: The Chi-Square Test for Independence

440

(7)

The Chi-Square Test for a 2 x 2 Contingency Table

447

(1)

What is Beautiful is Good

447

(1)

Which Cells Are Major Contributors to a Significant Chi-Square Test?

448

(2)

Using the Chi-Square Test with Quantitative Variables

450

(1)

Assumptions of the Chi-Square Test

450

(6)

Summary

451

(1)

Key Formulas for Chapter 17

451

(1)

Work Problems

452

(4)

Other Nonparametric Tests

456

(35)

The Research Context

456

(1)

The Use of Ranked Data in Research

457

(1)

The Spearman Rank Correlation Coefficient

458

(7)

The Point-Biserial Correlation Coefficient

465

(5)

The Mann-Whitney U Test

470

(6)

The Wilcoxon Signed-Ranks Test

476

(5)

Do Infants Notice the Difference Between Lip Movements and Speech Sounds?

480

(1)

Using Nonparametric Tests

481

(10)

Summary

482

(1)

Key Formulas for Chapter 18

483

(1)

Work Problems

484

(7)

Appendixes

491

(80)

A. Some Basic Concepts of Probability

491

(11)

B. Statistical Tables

502

(15)

1. z Table

502

(4)

2. t Table

506

(1)

3. Power Table (Finding Power)

507

(1)

4. Power Table (Finding Delta)

508

(1)

5. F Table

508

(3)

6. Pearson r Table

511

(1)

7. Spearman rs Table

512

(1)

8. Chi-Square Table

513

(1)

9. Mann-Whitney U Table

514

(2)

10. Wilcoxon Signed-Ranks Table

516

(1)

C. Answers to Problems

517

(54)

Glossary

571

(6)

References

577

(9)

Index

586

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Statistical Applications for the Behavioral Sciences

Summary

Table of Contents

Supplemental Materials