Reading Statistics and Research, 6th edition
Published by Pearson (February 24, 2011) © 2012
- Schuyler W. Huck University of Tennessee
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While instructing its readers on how to read, understand, and critically evaluate the statistical information and research results contained in technical research reports, the text methodically presents basic statistical and research concepts and illustrates how to employ them in making sound educational decisions.
Key topic areas introduced include: descriptive statistics, correlation, reliability and validity, estimation, h hypothesis testing, t-tests, ANOVA, ANCOVA, regression, multivariate analysis, factor analysis, and structural equation modeling (SEM).
Additionally, new mini-topics related to research and statistics are also discussed, such as the geometric mean, Tau-b correlation, Guttman split-half reliability, sensitivity, specificity, and the Sobel test. Dispersed throughout the text are 488 boxed features featuring excerpts that are completely new to this edition, utilizing accounts from the most contemporary research reports out today. New, re-written chapters cover Multivariate Tests (Chapter 19), Factor Analysis (Chapter 20), and Structural Equation Modeling (Chapter 21).
NEW! All 488 boxed excerpts, found throughout the text and taken from current research reports are 1) completely new to this edition, and 2) feature accounts from the most contemporary research reports out today.
NEW! Chapter 19 on Multivariate Tests covering means (i.e., ANOVA and ANCOVA) and supporting the fact that more and more researchers today are using these types of assessments.
NEW! Chapter 20 has been completely re-written to cover Factor Analysis in order to give readers an understanding of the subject matter, presenting the important new topic in research, “structural equation modeling.”
NEW! Chapter 21 on Structural Equation Modeling (SEM), the valuable new tool being used by many researchers in the social sciences today, is covered in a completely revised and re-written chapter.
NEW! Chapter 16 explains the differences of “Moderated” and “Mediated” Multiple Regression in great detail and why the differences matter.
NEW! Chapter content covers a myriad of mini-topics related to research and statistics–such as the geometric mean, Tau-b correlation, Guttman split-half reliability, sensitivity, specificity, and the Sobel test. Mini-topics are dispersed throughout the text in appropriate places to give readers a better grasp at understanding the material, and ultimately deciphering and critiquing research reports on their own.
Brief Contents
1 The Typical Format of a Journal Article X
2 Descriptive Statistics: The Univariate Case XX
3 Bivariate Correlation XX
4 Reliability and Validity XX
5 Foundations of Inferential Statistics XX
6 Estimation XXX
7 Hypothesis Testing XXX
8 Effect Size, Power, CIs, and Bonferroni XXX
9 Statistical Inferences Concerning Bivariate Correlation Coefficients XXX
10 Inferences Concerning One or Two Means XXX
11 Tests on Three or More Means Using a One-Way ANOVA XXX
12 Post Hoc and Planned Comparisons XXX
13 Two-Way Analyses of Variance XXX
14 Analyses of Variance with Repeated Measures XXX
15 The Analysis of Covariance XXX
16 Bivariate, Multiple, and Logistic Regression XXX
17 Inferences on Percentages, Proportions, and Frequencies XXX
18 Statistical Tests on Ranks (Nonparametric Tests) XXX
19 Multivariate Tests on Means XXX
20 Factor Analysis XXX
21 Structural Equation Modeling XXX
Epilogue XXX
Contents
Preface XXX
1 The Typical Format of a Journal Article XXX
Abstract XXX
Introduction XXX
Method XXX
Results XXX
Discussion XXX
References XXX
Notes XXX
Two Final Comments XXX
Review Terms XXX
The Best Items in the Companion Website XXX
2 Descriptive Statistics: The Univariate Case XXX
Picture Techniques XXX
Distributional Shape XXX
Measures of Central Tendency XXX
Measures of Variability XXX
Standard Scores XXX
A Few Cautions XXX
Review Terms XXX
The Best Items in the Companion Website XXX
3 Bivariate Correlation XXX
The Key Concept behind Correlation: Relationship XXX
Scatter Diagrams XXX
The Correlation Coefficient XXX
The Correlation Matrix XXX
Different Kinds of Correlational Procedures XXX
Warnings about Correlation XXX
Review Terms XXX
The Best Items in the Companion Website XXX
4 Reliability and Validity XXX
Reliability XXX
Validity XXX
Four Final Comments XXX
Review Terms XXX
The Best Items in the Companion Website XXX
5 Foundations of Inferential Statistics XXX
Statistical Inference XXX
The Concepts of Statistic and Parameter XXX
Types of Samples XXX
The Problems of Low Response Rates, Refusals to Participate, and Attrition XXX
A Few Warnings XXX
Review Terms XXX
The Best Items in the Companion Website XXX
6 Estimation XXX
Interval Estimation XXX
Point Estimation XXX
Warnings Concerning Interval and Point Estimation XXX
Review Terms XXX
The Best Items in the Companion Website XXX
7 Hypothesis Testing XXX
An Ordered List of the Six Steps XXX
A Detailed Look at Each of the Six Steps XXX
Results That Are Highly Significant and Near Misses XXX
A Few Cautions XXX
Review Terms XXX
The Best Items in the Companion Website XXX
8 Effect Size, Power, CIs, and Bonferroni XXX
The Seven-Step Version of Hypothesis Testing: Estimating Effect Size XXX
The Nine-Step Version of Hypothesis Testing: Power Analyses
Hypothesis Testing Using Confidence Intervals XXX
Adjusting for an Inflated Type I Error Rate XXX
A Few Cautions XXX
Review Terms XXX
The Best Items in the Companion Website XXX
9 Statistical Inferences Concerning Bivariate Correlation Coefficients XXX
Statistical Tests Involving a Single Correlation Coefficient XXX
Tests on Many Correlation Coefficients (Each of Which Is Treated Separately) XXX
Tests of Reliability and Validity Coefficients XXX
Statistically Comparing Two Correlation Coefficients XXX
The Use of Confidence Intervals around Correlation Coefficients XXX
Cautions XXX
Review Terms XXX
The Best Items in the Companion Website XXX
10 Inferences Concerning One or Two Means XXX
Inferences Concerning a Single Mean XXX
Inferences Concerning Two Means XXX
Multiple Dependent Variables XXX
Effect Size Assessment and Power Analyses XXX
Underlying Assumptions XXX
Comments XXX
Review Terms XXX
The Best Items in the Companion Website XXX
11 Tests on Three or More Means Using a One-Way ANOVA XXX
The Purpose of a One-Way ANOVA XXX
The Distinction between a One-Way ANOVA and Other Kinds of ANOVA XXX
The One-Way ANOVA’s Null and Alternative Hypotheses XXX
Presentation of Results XXX
Assumptions of a One-Way ANOVA XXX
Statistical Significance versus Practical Significance XXX
Cautions XXX
A Final Comment XXX
Review Terms XXX
The Best Items in the Companion Website XXX
12 Post Hoc and Planned Comparisons XXX
Post Hoc Comparisons XXX
Planned Comparisons XXX
Comments XXX
Review Terms XXX
The Best Items in the Companion Website XXX
13 Two-Way Analyses of Variance XXX
Similarities between One-Way and Two-Way ANOVAs XXX
The Structure of a Two-Way ANOVA XXX
Three Research Questions XXX
The Three Null Hypotheses (and Three Alternative Hypotheses) XXX
Presentation of Results XXX
Follow-Up Tests XXX
Planned Comparisons XXX
Assumptions Associated with a Two-Way ANOVA XXX
Estimating Effect Size and Conducting Power Analyses in Two-Way ANOVAs XXX
The Inflated Type I Error Rate in Factorial ANOVAs XXX
A Few Warnings Concerning Two-Way ANOVAs XXX
Review Terms XXX
The Best Items in the Companion Website XXX
14 Analyses of Variance with Repeated Measures XXX
One-Way Repeated Measures ANOVAs XXX
Two-Way Repeated Measures ANOVAs XXX
Two-Way Mixed ANOVAs XXX
Three Final Comments XXX
Review Terms XXX
The Best Items in the Companion Website XXX
15 The Analysis of Covariance XXX
The Three Different Variables Involved in Any ANCOVA Study XXX
The Covariate’s Role XXX
Null Hypotheses XXX
The Focus, Number, and Quality of the Covariate Variable(s) XXX
Presentation of Results XXX
The Statistical Basis for ANCOVA’s Power Advantage and Adjustment Feature XXX
Assumptions XXX
ANCOVA When Comparison Groups Are Not Formed Randomly XXX
Related Issues XXX
A Few Warnings XXX
Review Terms XXX
The Best Items in the Companion Website XXX
16 Bivariate, Multiple, and Logistic Regression XXX
Bivariate Regression XXX
Multiple Regression XXX
Logistic Regression XXX
Final Comments XXX
Review Terms XXX
The Best Items in the Companion Website XXX
17 Inferences on Percentages, Proportions, and Frequencies XXX
The Sign Test XXX
The Binomial Test XXX
Fisher’s Exact Test XXX
Chi-Square Tests: An Introduction XXX
Three Main Types of Chi-Square Tests XXX
Issues Related to Chi-Square Tests XXX
McNemar’s Chi-Square XXX
The Cochran Q Test XXX
The Use of z-Tests When Dealing with Proportions XXX
A Few Final Thoughts XXX
Review Terms XXX
The Best Items in the Companion Website XXX
18 Statistical Tests on Ranks (Nonparametric Tests) XXX
Obtaining Ranked Data XXX
Reasons for Converting Scores on a Continuous Variable into Ranks XXX
The Median Test XXX
The Mann-Whitney U Test XXX
The Kruskal-Wallis H Test XXX
The Wilcoxon Matched-Pairs Signed-Ranks Test XXX
Friedman’s Two-Way Analysis of Variance of Ranks XXX
Large-Sample Versions of the Tests on Ranks XXX
Ties XXX
The Relative Power of Nonparametric Tests XXX
A Few Final Comments XXX
Review Terms XXX
The Best Items in the Companion Website XXX
19 Multivariate Tests on Means XXX
The Versatility of Multivariate Tests XXX
The Multivariate Null Hypothesis XXX
Testing the Multivariate Null Hypothesis XXX
Assumptions XXX
Statistical Significance and Practical Significance
Post Hoc Investigations XXX
Three Final Comments XXX
Review Terms XXX
The Best Items in the Companion Website XXX
20 Factor Analysis XXX
The Goal (and Basic Logic) or Factor Analysis XXX
The Multivariate Null Hypothesis XXX
The Three Main Uses of Factor Analysis XXX
Exploratory and Confirmatory Factor Analysis XXX
Exploratory Factor Analysis XXX
Confirmatory Factor Analysis XXX
Assumptions XXX
Two Final Comments XXX
Review Terms XXX
The Best Items in the Companion Website XXX
20 Structural Equation Modeling XXX
Key Terms and Concepts of Structural Equation Modeling XXX
Elements in a Study Using Structural Equation Modeling XXX
Other Uses of SEM XXX
Issues and Considerations XXX
Review Terms XXX
The Best Items in the Companion Website XXX
Epilogue XXX
Review Questions XXX
Answers to Review Questions XXX
Credits XXX
Index XXX
In 1970, Dr. Huck joined the faculty at the University of Tennessee, Knoxville as an Assistant Professor. Affiliated with the Department of Educational and Counseling Psychology, he was promoted to Associate Professor in 1974 and to Professor in 1977. Since receiving his doctorate, Dr. Huck has taught at two other educational institutions while on leave from UT. For 10 summers between 1977 and 1986, he was employed as a Visiting Professor in the Psychology and Education Departments at the University of Nevada (Reno). From July, 1988 until July, 1989, he served as a Distinguished Visiting Professor at the United States Air Force Academy in Colorado.
Over the past three decades, Professor Huck has been involved in an ongoing program of research and scholarly activity. He is the senior author of three books: (1) Reading Statistics and Research (with the 3rd edition published in 2000 by Allyn & Bacon/Longman), (2) Rival Hypotheses: Alternative Explanations for Data-Based Conclusions (published in 1979 by Harper & Row), and (3) Statistical Illusions (published in 1984 by Harper & Row); he has had 34 technical papers published in a variety of refereed journals (Teaching Statistics, Educational and Psychological Measurement, Journal of Educational Statistics, American Educational Research Journal, Journal of Educational Measurement, Psychological Bulletin, Journal of Experimental Education, Journal of Applied Psychology, Science Education, Teaching of Psychology, Mathematics Teacher, Journal of Counseling Psychology, Research Quarterly, Physiology & Behavior); and he has made over 60 oral presentations of his work at professional meetings (International Conference on Teaching Statistics, American Educational Research Association, American Psychological Association, and regional meetings affiliated with these two national organizations).
In addition to making his own contributions to the professional literature, Professor Huck has been heavily involved in screening the work of others and in serving as a consultant on others' projects. He has reviewed book prospecti/full manuscripts sent to publishing companies, papers considered for possible publication in professional journals, and abstracts submitted for possible presentation at conventions. In his role as a consultant, Professor Huck has worked on several projects, including (1) test-development efforts conducted by: the American College of Veterinary Internal Medicine, the American Association of State Psychology Boards, Tennessee's State Departments of Education and Human Services, the Child Welfare Institute (Atlanta), and UT's Center for Government Training, (2) a three-year NSF research project designed to assess new procedures for helping math teachers assist students improve their creativity and problem-solving skills, and (3) a trial in which the State of Tennessee was being sued and for which Tennessee's Office of the Attorney General asked Dr. Huck to testify as an Expert Witness in the areas of testing, research design, and applied statistics.
At various points in his career, Dr. Huck has received awards/recognition from students, colleagues, and administrators. While at DePauw, he received the Frank C. Tucker Award for Leadership. Early in his stay at Tennessee, the Student Government Association tapped him as one of the University's Outstanding Teachers. Soon thereafter, colleagues at UT gave him the first Annual Award for Outstanding Faculty Research in the College of Education. The major honors bestowed upon Professor Huck, however, came (1) in 1983 when he was selected to be a UT Distinguished Service Professor, a prestigious title that he holds for the duration of his stay at the University, (2) in 1988 when he was asked to serve, for a year, on the faculty at the Air Force Academy as a Distinguished Visiting Professor, (3) in 1984 and 1990 when the scholarly work of two doctoral advisees received Outstanding Dissertation Awards in national competitions conducted by AERA, (4) in 1991 when he was elected by his colleagues at other universities as President of AERA's Educational Statisticians SIG, (5) in 1993 when he was one of the first two faculty members given the title of Chancellor's Teaching Scholar, a post involving work with UT's Chancellor and other top administrators, and (6) in 1995 when the GTA Mentoring Program (a project that grew out of his idea on how to improve undergraduate education at research universities) was deemed worthy of support by UT and the Alcoa Foundation.
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