Essentials of Statistics for the Behavioral Sciences / Edition 8

by Frederick Gravetter

Overview

Does the thought of taking a statistics course make your students nervous? Authors Frederick Gravetter and Larry B. Wallnau use interesting real-world examples and applications to quell student fears and to reveal the ESSENTIALS OF STATISTICS FOR THE BEHAVIORAL SCIENCES. This book helps students get beyond thinking of statistics as merely a course they have to take and come to appreciate it as a set of essential tools that helps us make sense of data in our information-driven world. Gravetter and Wallnau skillfully demonstrate that having a basic understanding of a variety of statistical procedures will help students understand published findings, as well as become savvy consumers of information. The authors employ an intuitive, straightforward writing style as well as numerous learning checks, both of which support students' interest in and understanding of the material.

Product Details

ISBN-13:	2901133956579
Publication date:	01/01/2013
Edition description:	NE
Pages:	648
Product dimensions:	7.90(w) x 9.90(h) x 0.90(d)

About the Author

The late Frederick J Gravetter was professor emeritus of psychology at State University of New York, Brockport. While teaching at Brockport, Dr. Gravetter specialized in statistics, experimental design and cognitive psychology. He received his bachelor’s degree in mathematics from M.I.T. and his Ph.D. in psychology from Duke University. In addition to publishing several research articles, Dr. Gravetter co-authored STATISTICS FOR THE BEHAVIORAL SCIENCES and ESSENTIAL OF STATISTICS FOR THE BEHAVIORAL SCIENCES.

Larry B. Wallnau is Professor Emeritus of Psychology at The College at Brockport, State University of New York. While teaching at Brockport, he published numerous research articles in biopsychology and provided editorial consultation for journals in his field. He has taught statistics, animal behavior, biopsychology, psychopharmacology and introductory psychology. With Dr. Frederick J Gravetter, he co-authored all previous editions of STATISTICS FOR THE BEHAVIORAL SCIENCES, now in its 10th edition. Dr. Wallnau received his bachelor's degree from the University of New Haven and his Ph.D. in psychology from the State University of New York at Albany. In his leisure time, he is an avid runner with his canine companion, Gracie.

Lori-Ann B Forzano is a professor of psychology at State University of New York, Brockport, where she regularly teaches undergraduate and graduate courses in research methods, statistics, learning, animal behavior and the psychology of eating. Her research examines impulsivity and self-control in adults and children and has been published in the Journal of the Experimental Analysis of Behavior, Learning and Motivation and The Psychological Record. Dr. Forzano also co-authored ESSENTIALS OF STATISTICS FOR THE BEHAVIORAL SCIENCES. She received her PhD in experimental psychology from the State University of New York at Stony Brook.

James E. Witnauer is Associate Professor of Psychology at The College at Brockport, State University of New York, where he teaches undergraduate courses in experimental psychology and graduate courses in statistics and biopsychology. He earned a Ph.D. in cognitive psychology from State University of New York, Binghamton, and a B.A. in psychology from State University of New York, Buffalo State College.

Table of Contents

Chapter 1	Introduction to Statistics	1
1.1	Statistics, Science, and Observations	2
1.2	Populations and Samples	3
1.3	The Scientific Method and the Design of Research Studies	8
1.4	Scales of Measurement	14
1.5	Discrete and Continuous Variables	17
1.6	Statistical Notation	19
	Summary	24
	Focus on Problem Solving	25
	Problems	27
Chapter 2	Frequency Distributions	29
2.1	Introduction	30
2.2	Frequency Distribution Tables	30
2.3	Frequency Distribution Graphs	36
2.4	The Shape of a Frequency Distribution	40
	Summary	43
	Focus on Problem Solving	44
	Problems	46
Chapter 3	Central Tendency	50
3.1	Introduction	51
3.2	The Mean	52
3.3	The Median	60
3.4	The Mode	62
3.5	Selecting a Measure of Central Tendency	64
	In the Literature: Reporting Measures of Central Tendency	67
3.6	Central Tendency and the Shape of the Distribution	70
	Summary	72
	Focus on Problem Solving	73
	Problems	74
Chapter 4	Variability	76
4.1	Introduction	77
4.2	The Range	78
4.3	The Interquartile Range and Semi-interquartile Range	79
4.4	Standard Deviation and Variance for a Population	81
4.5	Standard Deviation and Variance for Samples	88
4.6	More about Variance and Standard Deviation	92
	In the Literature: Reporting the Standard Deviation	97
	Summary	98
	Focus on Problem Solving	99
	Problems	100
Chapter 5	z-Scores: Location of Scores and Standardized Distributions	103
5.1	Overview	104
5.2	Introduction to z-Scores	104
5.3	z-Scores and Location in a Distribution	106
5.4	Using z-Scores to Standardize a Distribution	110
5.5	Other Standardized Distributions Based on z-Scores	113
	Summary	116
	Focus on Problem Solving	116
	Problems	119
Chapter 6	Probability	121
6.1	Introduction to Probability	122
6.2	Probability and the Normal Distribution	127
	Summary	139
	Focus on Problem Solving	139
	Problems	141
Chapter 7	Probability and Samples: The Distribution of Sample Means	144
7.1	Samples and Sampling Error	145
7.2	The Distribution of Sample Means	145
7.3	Probability and the Distribution of Sample Means	152
7.4	More about Standard Error	155
	In the Literature: Reporting Standard Error	158
	Summary	161
	Focus on Problem Solving	161
	Problems	163
Chapter 8	Introduction to Hypothesis Testing	166
8.1	The Logic of Hypothesis Testing	167
8.2	Uncertainty and Errors in Hypothesis Testing	176
8.3	An Example of a Hypothesis Test	180
	In the Literature: Reporting the Results of the Statistical Test	182
8.4	Directional (One-Tailed) Hypothesis Tests	186
8.5	The General Elements of Hypothesis Testing: A Review	190
	Summary	193
	Focus on Problem Solving	194
	Problems	196
Chapter 9	Introduction to the t Statistic	200
9.1	Overview	201
9.2	Hypothesis Tests with the t Statistic	207
	In the Literature: Reporting the Results of a t Test	211
	Summary	216
	Focus on Problem Solving	217
	Problems	219
Chapter 10	The t Test for Two Independent Samples	222
10.1	Overview	223
10.2	The t Statistic for an Independent-Measures Research Design	224
10.3	Hypothesis Tests with the Independent-Measures t Statistic	230
	In the Literature: Reporting the Results of an Independent-Measures t Test	234
10.4	Assumptions Underlying the Independent-Measures t Formula	239
	Summary	241
	Focus on Problem Solving	242
	Problems	244
Chapter 11	The t Test for Two Related Samples	249
11.1	Overview	250
11.2	The t Statistic for Related Samples	251
11.3	Hypothesis Tests for the Repeated-Measures Design	255
	In the Literature: Reporting the Results of a Repeated-Measures t Test	258
11.4	Uses and Assumptions for Related-Samples t Tests	261
	Summary	264
	Focus on Problem Solving	265
	Problems	268
Chapter 12	Estimation	272
12.1	An Overview of Estimation	273
12.2	Estimation with the t Statistic	278
12.3	A Final Look at Estimation	287
	Summary	289
	Focus on Problem Solving	290
	Problems	294
Chapter 13	Introduction to Analysis of Variance	298
13.1	Introduction	299
13.2	The Logic of Analysis of Variance	302
13.3	ANOVA Notation and Formulas	306
13.4	The Distribution of F-Ratios	314
13.5	Examples of Hypothesis Testing with ANOVA	316
	In the Literature: Reporting the Results of Analysis of Variance	319
13.6	Post Hoc Tests	327
	Summary	333
	Focus on Problem Solving	333
	Problems	336
Chapter 14	More Advanced Analysis of Variance: Repeated-Measures and Two-Factor Designs	341
14.1	Overview	342
14.2	Repeated-Measures Analysis of Variance (ANOVA)	342
	In the Literature: Reporting the Results of a Repeated-Measure ANOVA	353
14.3	Two-Factor Analysis of Variance (Independent Measures)	355
	In the Literature: Reporting the Results of a Two-Factor ANOVA	369
	Summary	373
	Focus on Problem Solving	373
	Problems	379
Chapter 15	Correlation and Regression	384
15.1	Introduction	385
15.2	The Pearson Correlation	388
15.3	Using and Interpreting the Pearson Correlation	393
15.4	Hypothesis Tests with the Pearson Correlation	399
	In the Literature: Reporting Correlations	401
15.5	The Spearman Correlation	404
15.6	Introduction to Regression	410
	Summary	417
	Focus on Problem Solving	418
	Problems	421
Chapter 16	The Chi-Square Statistic: Tests for Goodness of Fit and Independence	426
16.1	Parametric and Nonparametric Statistical Tests	427
16.2	The Chi-Square Test for Goodness of Fit	428
	In the Literature: Reporting the Results for Chi-Square	436
16.3	The Chi-Square Test for Independence	438
16.4	Assumptions and Restrictions for Chi-Square Tests	448
	Summary	449
	Focus on Problem Solving	450
	Problems	453
Appendix A	Basic Mathematics Review	1
Appendix B	Statistical Tables	24
Appendix C	Solutions for Odd-Numbered Problems in the Text	35
	Statistics Organizer	50
	References	61
	Index	62

Editorial Reviews

Teaches methods of statistics and how to apply them appropriately. This fifth edition contains revised problems and learning checks, and is divided into sections on descriptive statistics, foundations of inferential statistics, inferential statistics for sample mean differences, and non-parametric statistics. Each section is preceded by a brief synopsis of goals and direction of material to be covered. Includes chapter summaries, problem solving tips, worked examples, and problems. The authors are affiliated with the State University of New York College at Brockport. Annotation c. Book News, Inc., Portland, OR (booknews.com)

Booknews

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