Intermediate Statistics: A Conceptual Course
Autor Brett W. Pelhamen Limba Engleză Hardback – 22 oct 2012
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Hands on Data Analysis: A Second Course in Statistics 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.
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Specificații
ISBN-13: 9781412994989
ISBN-10: 1412994985
Pagini: 448
Dimensiuni: 178 x 254 x 30 mm
Greutate: 0.96 kg
Ediția:1
Editura: SAGE Publications
Colecția Sage Publications, Inc
Locul publicării:Thousand Oaks, United States
ISBN-10: 1412994985
Pagini: 448
Dimensiuni: 178 x 254 x 30 mm
Greutate: 0.96 kg
Ediția:1
Editura: SAGE Publications
Colecția Sage Publications, Inc
Locul publicării:Thousand Oaks, United States
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Recenzii
“The text is highly readable, and the author has done a good job making difficult topics like path analysis easy for students to comprehend. As much as possible, the author uses simple language and explains things in ways that students would be able to grasp. His incorporation of numerous examples helps to facilitate this goal as well.”
“The key strengths of this text are is applied perspective, focusing on conceptual understanding of data analyses rather than arcane statistical proofs. It finds just the right balance of technical, conceptual and practical perspectives. In addition, the heavy reliance on real-world examples and supplemental information in appendices will render it an invaluable resource for young graduate students as they progress in their research training.”
“This is a breath of fresh air compared to most statistics texts—rigorous but highly readable. The author does an impressive job of making statistical concepts feel intuitive. In addition, the integration of datasets and SPSS problems to solve make this book unique.”
“The key strengths of this text are is applied perspective, focusing on conceptual understanding of data analyses rather than arcane statistical proofs. It finds just the right balance of technical, conceptual and practical perspectives. In addition, the heavy reliance on real-world examples and supplemental information in appendices will render it an invaluable resource for young graduate students as they progress in their research training.”
“This is a breath of fresh air compared to most statistics texts—rigorous but highly readable. The author does an impressive job of making statistical concepts feel intuitive. In addition, the integration of datasets and SPSS problems to solve make this book unique.”
Cuprins
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
Notă biografică
Descriere
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