### A Second Course for Education and the Behavioral Sciences

### A Second Course for Education and the Behavioral Sciences

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Richard Lomax provides a conceptual, intuitive approach to the subject that requires only a rudimentary knowledge of basic algebra. Concepts are clearly stated and supported by real-life examples. *Statistical Concepts* features comprehensive coverage in a flexible format so instructors can pick and choose topics. It features topics not traditionally found in other textbooks, such as the layout of the data in ANOVA models, the ANOVA linear models, expected mean squares in ANOVA models, and stepwise regression. The book features a thorough and current discussion of assumptions, the effects of their violations, and how to deal with their violation.

This text is designed for a second or intermediate course in statistics for students in education and the behavioral sciences. It includes a number of regression and analysis of variance models, all subsumed under the general linear model (GLM). A prerequisite of introductory statistics (descriptive statistics through t-tests) is assumed.

**Contents: **Preface. Simple Linear Regression. Multiple Regression. One-Factor Analysis of Variance--Fixed-Effects Model. Multiple-Comparison Procedures. Factorial Analysis of Variance--Fixed-Effects Model. Introduction to Analysis of Covariance: The One-Factor Fixed-Effects Model With a Single Covariate. Random- and Mixed-Effects Analysis of Variance Models. Hierarchical and Randomized Block Analysis of Variance Models. Appendix Tables.

Richard Lomax provides a conceptual, intuitive approach to the subject that requires only a rudimentary knowledge of basic algebra. Concepts are clearly stated and supported by real-life examples. *Statistical Concepts* features comprehensive coverage in a flexible format so instructors can pick and choose topics. It features topics not traditionally found in other textbooks, such as the layout of the data in ANOVA models, the ANOVA linear models, expected mean squares in ANOVA models, and stepwise regression. The book features a thorough and current discussion of assumptions, the effects of their violations, and how to deal with their violation.

This text is designed for a second or intermediate course in statistics for students in education and the behavioral sciences. It includes a number of regression and analysis of variance models, all subsumed under the general linear model (GLM). A prerequisite of introductory statistics (descriptive statistics through t-tests) is assumed.

**Contents: **Preface. Simple Linear Regression. Multiple Regression. One-Factor Analysis of Variance--Fixed-Effects Model. Multiple-Comparison Procedures. Factorial Analysis of Variance--Fixed-Effects Model. Introduction to Analysis of Covariance: The One-Factor Fixed-Effects Model With a Single Covariate. Random- and Mixed-Effects Analysis of Variance Models. Hierarchical and Randomized Block Analysis of Variance Models. Appendix Tables.

Richard Lomax provides a conceptual, intuitive approach to the subject that requires only a rudimentary knowledge of basic algebra. Concepts are clearly stated and supported by real-life examples. *Statistical Concepts* features comprehensive coverage in a flexible format so instructors can pick and choose topics. It features topics not traditionally found in other textbooks, such as the layout of the data in ANOVA models, the ANOVA linear models, expected mean squares in ANOVA models, and stepwise regression. The book features a thorough and current discussion of assumptions, the effects of their violations, and how to deal with their violation.

This text is designed for a second or intermediate course in statistics for students in education and the behavioral sciences. It includes a number of regression and analysis of variance models, all subsumed under the general linear model (GLM). A prerequisite of introductory statistics (descriptive statistics through t-tests) is assumed.

**Contents: **Preface. Simple Linear Regression. Multiple Regression. One-Factor Analysis of Variance--Fixed-Effects Model. Multiple-Comparison Procedures. Factorial Analysis of Variance--Fixed-Effects Model. Introduction to Analysis of Covariance: The One-Factor Fixed-Effects Model With a Single Covariate. Random- and Mixed-Effects Analysis of Variance Models. Hierarchical and Randomized Block Analysis of Variance Models. Appendix Tables.

*Statistical Concepts* features comprehensive coverage in a flexible format so instructors can pick and choose topics. It features topics not traditionally found in other textbooks, such as the layout of the data in ANOVA models, the ANOVA linear models, expected mean squares in ANOVA models, and stepwise regression. The book features a thorough and current discussion of assumptions, the effects of their violations, and how to deal with their violation.

**Contents: **Preface. Simple Linear Regression. Multiple Regression. One-Factor Analysis of Variance--Fixed-Effects Model. Multiple-Comparison Procedures. Factorial Analysis of Variance--Fixed-Effects Model. Introduction to Analysis of Covariance: The One-Factor Fixed-Effects Model With a Single Covariate. Random- and Mixed-Effects Analysis of Variance Models. Hierarchical and Randomized Block Analysis of Variance Models. Appendix Tables.

*Statistical Concepts* features comprehensive coverage in a flexible format so instructors can pick and choose topics. It features topics not traditionally found in other textbooks, such as the layout of the data in ANOVA models, the ANOVA linear models, expected mean squares in ANOVA models, and stepwise regression. The book features a thorough and current discussion of assumptions, the effects of their violations, and how to deal with their violation.

**Contents: **Preface. Simple Linear Regression. Multiple Regression. One-Factor Analysis of Variance--Fixed-Effects Model. Multiple-Comparison Procedures. Factorial Analysis of Variance--Fixed-Effects Model. Introduction to Analysis of Covariance: The One-Factor Fixed-Effects Model With a Single Covariate. Random- and Mixed-Effects Analysis of Variance Models. Hierarchical and Randomized Block Analysis of Variance Models. Appendix Tables.

*Statistical Concepts* features comprehensive coverage in a flexible format so instructors can pick and choose topics. It features topics not traditionally found in other textbooks, such as the layout of the data in ANOVA models, the ANOVA linear models, expected mean squares in ANOVA models, and stepwise regression. The book features a thorough and current discussion of assumptions, the effects of their violations, and how to deal with their violation.

**Contents: **Preface. Simple Linear Regression. Multiple Regression. One-Factor Analysis of Variance--Fixed-Effects Model. Multiple-Comparison Procedures. Factorial Analysis of Variance--Fixed-Effects Model. Introduction to Analysis of Covariance: The One-Factor Fixed-Effects Model With a Single Covariate. Random- and Mixed-Effects Analysis of Variance Models. Hierarchical and Randomized Block Analysis of Variance Models. Appendix Tables.