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Intermediate Statistics
ISBN-13:
9781483306025
Veröffentl:
2012
Einband:
EPUB
Seiten:
448
Autor:
Brett W. Pelham
eBook Typ:
EPUB
eBook Format:
Reflowable EPUB
Kopierschutz:
Adobe DRM [Hard-DRM]
Sprache:
Englisch
Beschreibung:
A student-friendly text which enables students to appreciate the logic of descriptive and inferential statistics, and understand which techniques are best suited to which kinds of data or research questions
Intermediate Statistics: A Conceptual Course is a student-friendly text for advanced undergraduate and graduate courses. It begins with an introductory chapter that reviews descriptive and inferential statistics in plain language, avoiding extensive emphasis on complex formulas. The remainder of the text covers 13 different statistical topics ranging from descriptive statistics to advanced multiple regression analysis and path analysis. Each chapter contains a description of the logic of each set of statistical tests or procedures and then introduces students to a series of data sets using SPSS, with screen captures and detailed step-by-step instructions. Students acquire an appreciation of the logic of descriptive and inferential statistics, and an understanding of which techniques are best suited to which kinds of data or research questions.
Chapter 1: A Review of Basic Statistical Concepts
Chapter 2: Descriptive Statistics
Chapter 3: Linear and Curvilinear Correlation
Chapter 4: Non-Parametric Statistics (Tests Involving Nominal Variables)
Chapter 5: Reliability (and a Little Bit of Factor Analysis)
Chapter 6: Single-sample and two-sample t-tests
Chapter 7: One-way and Factorial Analysis of Variance (ANOVA)
Chapter 8: Within-Subjects and Mixed Model Analyses
Chapter 9: Multiple Regression
Chapter 10: Examining Interactions in Multiple Regression
Chapter 11: ANCOVA, Covariate Adjusted Means, and Predicted Scores
Chapter 12: Suppressor Variables
Chapter 13: Mediation and Path Analysis
Chapter 14: Data Cleaning
Chapter 15: Data Merging and Data Management
Chapter 16: Avoiding Bias: Characterizing without Capitalizing
Chapter 2: Descriptive Statistics
Chapter 3: Linear and Curvilinear Correlation
Chapter 4: Non-Parametric Statistics (Tests Involving Nominal Variables)
Chapter 5: Reliability (and a Little Bit of Factor Analysis)
Chapter 6: Single-sample and two-sample t-tests
Chapter 7: One-way and Factorial Analysis of Variance (ANOVA)
Chapter 8: Within-Subjects and Mixed Model Analyses
Chapter 9: Multiple Regression
Chapter 10: Examining Interactions in Multiple Regression
Chapter 11: ANCOVA, Covariate Adjusted Means, and Predicted Scores
Chapter 12: Suppressor Variables
Chapter 13: Mediation and Path Analysis
Chapter 14: Data Cleaning
Chapter 15: Data Merging and Data Management
Chapter 16: Avoiding Bias: Characterizing without Capitalizing