Schuyler Huck - Böcker

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.

This engaging book helps readers identify and then discard 52 misconceptions about data and statistical summaries. The focus is on major concepts contained in typical undergraduate and graduate courses in statistics, research methods, or quantitative analysis. Interactive Internet exercises that further promote undoing the misconceptions are found on the book's website.The author’s accessible discussion of each misconception has five parts:The Misconception - a brief description of the misunderstandingEvidence that the Misconception Exists – examples and claimed prevalenceWhy the Misconception is Dangerous – consequence of having the misunderstandingUndoing the Misconception - how to think correctly about the conceptInternet Assignment - an interactive activity to help readers gain a firm grasp of the statistical concept and overcome the misconception.The book's statistical misconceptions are grouped into 12 chapters that match the topics typically taught in introductory/intermediate courses. However, each of the 52 discussions is self-contained, thus allowing the misconceptions to be covered in any order without confusing the reader. Organized and presented in this manner, the book is an ideal supplement for any standard textbook.An ideal supplement for undergraduate and graduate courses in statistics, research methods, or quantitative analysis taught in psychology, education, business, nursing, medicine, and the social sciences. The book also appeals to independent researchers interested in undoing their statistical misconceptions.

This engaging book helps readers identify and then discard 52 misconceptions about data and statistical summaries. The focus is on major concepts contained in typical undergraduate and graduate courses in statistics, research methods, or quantitative analysis. Interactive Internet exercises that further promote undoing the misconceptions are found on the book's website.The author’s accessible discussion of each misconception has five parts:The Misconception - a brief description of the misunderstandingEvidence that the Misconception Exists – examples and claimed prevalenceWhy the Misconception is Dangerous – consequence of having the misunderstandingUndoing the Misconception - how to think correctly about the conceptInternet Assignment - an interactive activity to help readers gain a firm grasp of the statistical concept and overcome the misconception.The book's statistical misconceptions are grouped into 12 chapters that match the topics typically taught in introductory/intermediate courses. However, each of the 52 discussions is self-contained, thus allowing the misconceptions to be covered in any order without confusing the reader. Organized and presented in this manner, the book is an ideal supplement for any standard textbook.An ideal supplement for undergraduate and graduate courses in statistics, research methods, or quantitative analysis taught in psychology, education, business, nursing, medicine, and the social sciences. The book also appeals to independent researchers interested in undoing their statistical misconceptions.