Fundamental Statistics for the Behavioral Sciences

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ISBN: 9780534358211 | 0534358217
Cover: Hardcover
Copyright: 8/1/1998

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With an emphasis on looking at data before jumping into a test, author David C. Howell's practical approach focuses on the context of statistics in behavioral research. This approach promotes an understanding of the logic behind the statistics: why and how certain methods are used, rather than just doing techniques by rote. Howell takes students beyond crunching numbers to discover the meaning of statistical results and how they relate to the research questions being asked. Howell uses real data and research studies as a basis and moves through an analysis of data. As FUNDAMENTAL STATISTICS FOR THE BEHAVIORAL SCIENCES, Fourth Edition clearly demonstrates, it is not only important to concentrate on whether there is a difference between two groups but also to understand what the difference means.

Introduction

(14)

The Importance of Context

(2)

Basic Terminology

(3)

Selection Among Statistical Procedures

(2)

Using Computers

(2)

Summary

(1)

Exercises

(3)

Basic Concepts

(15)

Scales of Measurement

(4)

Variables

(1)

Random Sampling

(1)

Notation

(2)

Summary

(1)

Exercises

(5)

Displaying Data

(24)

A First Look at the Data

(3)

Stem-and-Leaf Displays

(3)

Histograms

(3)

Alternative Methods of Plotting Data

(3)

Describing Distributions

(3)

Using Computer Programs to Display Data

(1)

Summary

(1)

Exercises

(6)

Measures of Central Tendency

(9)

The Mode

(1)

The Median

(1)

The Mean

(1)

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

(2)

Obtaining Measures of Central Tendency Using Minitab

(1)

Summary

(1)

Exercises

(2)

Measures of Variability

(23)

Range

(1)

Interquartile Range and Other Range Statistics

(1)

The Average Deviation

(1)

The Variance

(1)

The Standard Deviation

(1)

Computational Formulae for the Variance and the Standard Deviation

(2)

The Mean and the Variance as Estimators

(2)

Boxplots: Graphical Representations of Dispersions and Extreme Scores

(4)

Obtaining Measures of Dispersion Using JMP

(2)

A Final Worked Example

(2)

Summary

(1)

Exercises

(3)

The Normal Distribution

(18)

The Normal Distribution

(4)

The Standard Normal Distribution

(6)

Setting Probable Limits on an Observation

(1)

Measures Related to z

(1)

Summary

100

(1)

Exercises

100

(4)

Basic Concepts of Probability

104

(14)

Probability

105

(2)

Basic Terminology and Rules

107

(4)

Discrete versus Continuous Variables

111

(1)

Probability Distributions for Discrete Variables

112

(1)

Probability Distributions for Continuous Variables

113

(2)

Summary

115

(1)

Exercises

116

(2)

Sampling Distributions and Hypothesis Testing

118

(23)

Two Simple Examples Involving Course Evaluations and Rude Motorists

120

(2)

Sampling Distributions

122

(1)

Hypothesis Testing

123

(2)

The Null Hypothesis

125

(1)

Test Statistics and Their Sampling Distributions

126

(1)

Using the Normal Distribution to Test Hypotheses

127

(3)

Type I and Type II Errors

130

(3)

One- and Two-Tailed Tests

133

(3)

A Final Worked Example

136

(1)

Back to Course Evaluations and Rude Motorists

137

(1)

Summary

138

(1)

Exercises

139

(2)

Correlation

141

(31)

Scatter Diagrams

142

(6)

An Example: The Relationship Between Speed and Accuracy

148

(3)

The Covariance

151

(1)

The Pearson Product-Moment Correlation Coefficient (r)

152

(2)

Correlations with Ranked Data

154

(1)

Factors That Affect the Correlation

155

(3)

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

158

(1)

Testing the Significance of a Correlation Coefficient

159

(2)

Intercorrelation Matrices

161

(2)

Other Correlation Coefficients

163

(1)

Using Minitab and SPSS to Obtain Correlation Coefficients

164

(2)

A Final Worked Example

166

(2)

Summary

168

(1)

Exercises

169

(3)

Regression

172

(25)

The Relationship Between Stress and Health

173

(2)

The Basic Data

175

(1)

The Regression Line

176

(4)

The Accuracy of Prediction

180

(6)

Hypothesis Testing in Regression

186

(1)

Computer Solution Using SPSS

187

(2)

A Final Worked Example

189

(2)

Summary

191

(1)

Exercises

192

(5)

Multiple Regression

197

(26)

Course Evaluations Again

200

(5)

Residuals

205

(2)

The Visual Representation of Multiple Regression

207

(1)

Hypothesis Testing

208

(2)

Refining the Regression Equation

210

(1)

A Second Example: Height and Weight

211

(3)

A Third Example: Psychological Symptoms in Cancer Patients

214

(4)

Summary

218

(1)

Exercises

219

(4)

Hypothesis Tests Applied to Means: One Sample

223

(24)

Sampling Distribution of the Mean

225

(2)

Testing Hypotheses About Means When σ is Known

227

(3)

Testing a Sample Mean When σ Is Unknown (One-Sample t Test)

230

(6)

Factors That Affect the Magnitude of t and the Decision About H0

236

(1)

A Second Example: The Moon Illusion

237

(1)

Confidence Limits on the Mean

238

(3)

Using a Computer Program to Run One-Sample t Tests

241

(1)

A Final Worked Example

242

(1)

Summary

243

(1)

Exercises

244

(3)

Hypothesis Tests Applied to Means: Two Related Samples

247

(12)

Related Samples

248

(1)

Student's t Applied to Difference Scores

249

(3)

A Second Example: The Moon Illusion Again

252

(1)

Advantages and Disadvantages of Using Related Samples

253

(1)

Using Computer Software for t Tests on Related Samples

254

(1)

Summary

255

(1)

Exercises

256

(3)

Hypothesis Tests Applied to Means: Two Independent Samples

259

(20)

Distribution of Differences Between Means

260

(7)

Heterogeneity of Variance

267

(1)

Nonnormality of Distributions

268

(1)

A Second Example with Two Independent Samples

269

(1)

Confidence Limits on μ1 -- μ2

270

(1)

Use of Computer Programs for Analysis of Two Independent Sample Means

271

(3)

A Final Worked Example

274

(2)

Summary

276

(1)

Exercises

276

(3)

Power

279

(20)

The Basic Concept

281

(1)

Factors That Affect the Powr of a Test

282

(2)

Effect Size

284

(2)

Power Calculations for the One-Sample t Test

286

(3)

Power Calculations for Differences Between Two Independent Means

289

(3)

Power Calculations for the t Test for Related Samples

292

(2)

Power Considerations in Terms of Sample Size

294

(1)

You Don't Have to Do It by Hand

295

(1)

Summary

296

(1)

Exercises

296

(3)

One-way Analysis of Variance

299

(36)

The General Approach

300

(3)

The Logic of the Analysis of Variance

303

(5)

Calculations for the Analysis of Variance

308

(7)

Unequal Sample Sizes

315

(1)

Multiple Comparison Procedures

316

(8)

Violations of Assumptions

324

(1)

Magnitude of Effect

325

(1)

Using JMP for a One-Way Analysis of Variance

326

(1)

A Final Worked Example

326

(4)

Summary

330

(1)

Exercises

331

(4)

Factorial Analysis of Variance

335

(22)

Factorial Designs

336

(2)

The Extension of the Eysenck Study

338

(5)

Interactions

343

(2)

Simple Effects

345

(3)

Unequal Sample Sizes

348

(1)

Magnitude of Effect

348

(1)

A Final Example: Maternal Adaptation Revisited

349

(2)

Using SPSS for Factorial Analysis of Variance

351

(1)

Summary

352

(1)

Exercises

353

(4)

Repeated-Measures Analysis of Variance

357

(14)

An Example: The Treatment of Migraine Headaches

358

(2)

Multiple Comparisons

360

(2)

Assumptions Involved in Repeated-Measures Designs

362

(1)

Advantages and Diadvantages of Repeated-Measures Designs

362

(1)

Using BMDP to Analyze Data in a Repeated-Measures Design

363

(3)

A Final Worked Example

366

(2)

Summary

368

(1)

Exercises

368

(3)

Chi-Square

371

(22)

One Classification Variable: The Chi-Square Goodness-of-Fit Test

373

(5)

Two Classification Variables: Contingency Table Analysis

378

(2)

Correction for Continuity

380

(1)

Chi-Square for Larger Contingency Tables

381

(1)

The Problem of Small Expected Frequencies

382

(1)

The Use of Chi-Square as a Test on Proportions

383

(2)

Nonindependent Observations

385

(1)

Minitab Analysis of Contingency Tables

386

(1)

A Final Worked Example

386

(2)

Summary

388

(1)

Exercises

389

(4)

Nonparametric and Distribution-Free Statistical Tests

393

(22)

The Mann--Whitney Test

395

(6)

Wilcoxon's Matched-Pairs Signed-Ranks Test

401

(4)

Kruskal--Wallis One-Way Analysis of Variance

405

(1)

Friedman's Rank Test for k Correlated Samples

406

(3)

Summary

409

(1)

Exercises

409

(6)

Choosing the Appropriate Analysis

415

(8)

Exercises and Examples

417

(6)

Appendix A Arithmetic Review

423

(6)

Appendix B Symbols and Notation

429

(3)

Appendix C Basic Statistical Formulae

432

(4)

Appendix D Dataset

436

(2)

Appendix E Statistical Tables

438

(19)

Glossary

457

(8)

References

465

(6)

Answers to Selected Exercises

471

(16)

Index

487

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Fundamental Statistics for the Behavioral Sciences

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Table of Contents

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Fundamental Statistics for the Behavioral Sciences

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