Reading Statistics and Research
Häftad, Engelska, 2011
4 249 kr
Finns i fler format (1)
Employing a non-intimidating writing style that emphasizes concepts rather than formulas, this uniquely welcoming text shows consumers of research how to read, understand, and critically evaluate the statistical information and research results contained in technical research reports. Some key topics covered in this thoroughly revised text 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). A number of 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. Additionally, the sixth edition also includes over 488 new excerpts (tables, figures, passages of text) taken from current research reports. Written specifically for students in non-thesis Master’s Programs but also perfectly suitable for students in upper-level undergraduate statistics courses, doctoral students who must conduct dissertation research, and independent researchers who want a better handle on how to decipher and critique statistically-based research reports.
Thoroughly updated and revised to reflect advances in the field, Reading Statistics and Research, Sixth Edition gives consumers of research exactly what they are seeking in this caliber of text, that being the knowledge necessary to better understand research and statistics, and the confidence and ability to ultimately decipher and critique research reports on their own.
Produktinformation
- Utgivningsdatum2011-04-21
 - Mått10 x 10 x 10 mm
 - Vikt790 g
 - FormatHäftad
 - SpråkEngelska
 - Antal sidor592
 - Upplaga6
 - FörlagPearson Education
 - ISBN9780132178631
 
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Schuyler W. Huck was born in Chicago, Illinois in 1943. He attended school in two Chicago suburbs (Riverside and Glenview), receiving a high school diploma in 1961 from Glenbrook North H.S. His undergraduate work was taken at DePauw University (Greencastle, Indiana) where he graduated in 1965 with a major in psychology and a minor in sociology. He pursued a doctorate in Educational Psychology at Northwestern University (Evanston, Illinois), receiving the Ph.D. in 1970. His doctoral specialization was applied statistics, testing, and research design.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.
- Brief Contents1 The Typical Format of a Journal Article X2 Descriptive Statistics: The Univariate Case XX3 Bivariate Correlation XX4 Reliability and Validity XX5 Foundations of Inferential Statistics XX6 Estimation XXX7 Hypothesis Testing XXX8 Effect Size, Power, CIs, and Bonferroni XXX9 Statistical Inferences Concerning Bivariate Correlation Coefficients XXX10 Inferences Concerning One or Two Means XXX11 Tests on Three or More Means Using a One-Way ANOVA XXX12 Post Hoc and Planned Comparisons XXX13 Two-Way Analyses of Variance XXX14 Analyses of Variance with Repeated Measures XXX15 The Analysis of Covariance XXX16 Bivariate, Multiple, and Logistic Regression XXX17 Inferences on Percentages, Proportions, and Frequencies XXX18 Statistical Tests on Ranks (Nonparametric Tests) XXX19 Multivariate Tests on Means XXX20 Factor Analysis XXX21 Structural Equation Modeling XXXEpilogue XXX ContentsPreface XXX1 The Typical Format of a Journal Article XXXAbstract XXXIntroduction XXXMethod XXXResults XXXDiscussion XXX References XXXNotes XXXTwo Final Comments XXXReview Terms XXXThe Best Items in the Companion Website XXX2 Descriptive Statistics: The Univariate Case XXXPicture Techniques XXXDistributional Shape XXXMeasures of Central Tendency XXXMeasures of Variability XXXStandard Scores XXXA Few Cautions XXXReview Terms XXXThe Best Items in the Companion Website XXX3 Bivariate Correlation XXXThe Key Concept behind Correlation: Relationship XXXScatter Diagrams XXXThe Correlation Coefficient XXXThe Correlation Matrix XXXDifferent Kinds of Correlational Procedures XXXWarnings about Correlation XXXReview Terms XXXThe Best Items in the Companion Website XXX4 Reliability and Validity XXXReliability XXXValidity XXXFour Final Comments XXXReview Terms XXXThe Best Items in the Companion Website XXX5 Foundations of Inferential Statistics XXXStatistical Inference XXXThe Concepts of Statistic and Parameter XXXTypes of Samples XXXThe Problems of Low Response Rates, Refusals to Participate, and Attrition XXXA Few Warnings XXXReview Terms XXXThe Best Items in the Companion Website XXX6 Estimation XXXInterval Estimation XXXPoint Estimation XXXWarnings Concerning Interval and Point Estimation XXXReview Terms XXXThe Best Items in the Companion Website XXX7 Hypothesis Testing XXXAn Ordered List of the Six Steps XXXA Detailed Look at Each of the Six Steps XXXResults That Are Highly Significant and Near Misses XXXA Few Cautions XXXReview Terms XXXThe Best Items in the Companion Website XXX8 Effect Size, Power, CIs, and Bonferroni XXXThe Seven-Step Version of Hypothesis Testing: Estimating Effect Size XXXThe Nine-Step Version of Hypothesis Testing: Power AnalysesHypothesis Testing Using Confidence Intervals XXXAdjusting for an Inflated Type I Error Rate XXXA Few Cautions XXXReview Terms XXXThe Best Items in the Companion Website XXX9 Statistical Inferences Concerning Bivariate Correlation Coefficients XXXStatistical Tests Involving a Single Correlation Coefficient XXXTests on Many Correlation Coefficients (Each of Which Is Treated Separately) XXXTests of Reliability and Validity Coefficients XXXStatistically Comparing Two Correlation Coefficients XXXThe Use of Confidence Intervals around Correlation Coefficients XXXCautions XXXReview Terms XXXThe Best Items in the Companion Website XXX10 Inferences Concerning One or Two Means XXXInferences Concerning a Single Mean XXXInferences Concerning Two Means XXXMultiple Dependent Variables XXXEffect Size Assessment and Power Analyses XXXUnderlying Assumptions XXXComments XXXReview Terms XXXThe Best Items in the Companion Website XXX11 Tests on Three or More Means Using a One-Way ANOVA XXXThe Purpose of a One-Way ANOVA XXXThe Distinction between a One-Way ANOVA and Other Kinds of ANOVA XXXThe One-Way ANOVA’s Null and Alternative Hypotheses XXXPresentation of Results XXXAssumptions of a One-Way ANOVA XXXStatistical Significance versus Practical Significance XXXCautions XXXA Final Comment XXXReview Terms XXXThe Best Items in the Companion Website XXX12 Post Hoc and Planned Comparisons XXXPost Hoc Comparisons XXXPlanned Comparisons XXXComments XXXReview Terms XXXThe Best Items in the Companion Website XXX13 Two-Way Analyses of Variance XXXSimilarities between One-Way and Two-Way ANOVAs XXXThe Structure of a Two-Way ANOVA XXXThree Research Questions XXXThe Three Null Hypotheses (and Three Alternative Hypotheses) XXXPresentation of Results XXXFollow-Up Tests XXXPlanned Comparisons XXXAssumptions Associated with a Two-Way ANOVA XXXEstimating Effect Size and Conducting Power Analyses in Two-Way ANOVAs XXXThe Inflated Type I Error Rate in Factorial ANOVAs XXXA Few Warnings Concerning Two-Way ANOVAs XXXReview Terms XXXThe Best Items in the Companion Website XXX14 Analyses of Variance with Repeated Measures XXXOne-Way Repeated Measures ANOVAs XXXTwo-Way Repeated Measures ANOVAs XXXTwo-Way Mixed ANOVAs XXXThree Final Comments XXXReview Terms XXXThe Best Items in the Companion Website XXX15 The Analysis of Covariance XXXThe Three Different Variables Involved in Any ANCOVA Study XXXThe Covariate’s Role XXXNull Hypotheses XXXThe Focus, Number, and Quality of the Covariate Variable(s) XXXPresentation of Results XXXThe Statistical Basis for ANCOVA’s Power Advantage and Adjustment Feature XXXAssumptions XXXANCOVA When Comparison Groups Are Not Formed Randomly XXXRelated Issues XXXA Few Warnings XXXReview Terms XXXThe Best Items in the Companion Website XXX16 Bivariate, Multiple, and Logistic Regression XXXBivariate Regression XXXMultiple Regression XXXLogistic Regression XXXFinal Comments XXXReview Terms XXXThe Best Items in the Companion Website XXX17 Inferences on Percentages, Proportions, and Frequencies XXXThe Sign Test XXXThe Binomial Test XXXFisher’s Exact Test XXXChi-Square Tests: An Introduction XXXThree Main Types of Chi-Square Tests XXXIssues Related to Chi-Square Tests XXXMcNemar’s Chi-Square XXXThe Cochran Q Test XXXThe Use of z-Tests When Dealing with Proportions XXXA Few Final Thoughts XXXReview Terms XXXThe Best Items in the Companion Website XXX18 Statistical Tests on Ranks (Nonparametric Tests) XXXObtaining Ranked Data XXXReasons for Converting Scores on a Continuous Variable into Ranks XXXThe Median Test XXXThe Mann-Whitney U Test XXXThe Kruskal-Wallis H Test XXXThe Wilcoxon Matched-Pairs Signed-Ranks Test XXXFriedman’s Two-Way Analysis of Variance of Ranks XXXLarge-Sample Versions of the Tests on Ranks XXXTies XXXThe Relative Power of Nonparametric Tests XXXA Few Final Comments XXXReview Terms XXXThe Best Items in the Companion Website XXX19 Multivariate Tests on Means XXXThe Versatility of Multivariate Tests XXXThe Multivariate Null Hypothesis XXXTesting the Multivariate Null Hypothesis XXXAssumptions XXXStatistical Significance and Practical SignificancePost Hoc Investigations XXXThree Final Comments XXXReview Terms XXXThe Best Items in the Companion Website XXX20 Factor Analysis XXXThe Goal (and Basic Logic) or Factor Analysis XXXThe Multivariate Null Hypothesis XXXThe Three Main Uses of Factor Analysis XXXExploratory and Confirmatory Factor Analysis XXXExploratory Factor Analysis XXXConfirmatory Factor Analysis XXXAssumptions XXXTwo Final Comments XXXReview Terms XXXThe Best Items in the Companion Website XXX20 Structural Equation Modeling XXXKey Terms and Concepts of Structural Equation Modeling XXXElements in a Study Using Structural Equation Modeling XXXOther Uses of SEM XXXIssues and Considerations XXXReview Terms XXXThe Best Items in the Companion Website XXXEpilogue XXXReview Questions XXXAnswers to Review Questions XXXCredits XXX Index XXX