The Analysis of Variance

1. Front Matter

   Pages i-xxxv

   PDF

2. Introduction

   • Hardeo Sahai, Mohammed I. Ageel

   Pages 1-9

3. One-Way Classification

   • Hardeo Sahai, Mohammed I. Ageel

   Pages 11-123

4. Two-Way Crossed Classification Without Interaction

   • Hardeo Sahai, Mohammed I. Ageel

   Pages 125-175

5. Two-Way Crossed Classification with Interaction

   • Hardeo Sahai, Mohammed I. Ageel

   Pages 177-280

6. Three-Way and Higher-Order Crossed Classifications

   • Hardeo Sahai, Mohammed I. Ageel

   Pages 281-345

7. Two-Way Nested (Hierarchical) Classification

   • Hardeo Sahai, Mohammed I. Ageel

   Pages 347-394

8. Three-Way and Higher-Order Nested Classifications

   • Hardeo Sahai, Mohammed I. Ageel

   Pages 395-429

9. Partially Nested Classifications

   • Hardeo Sahai, Mohammed I. Ageel

   Pages 431-460

10. Finite Population and Other Models

    • Hardeo Sahai, Mohammed I. Ageel

    Pages 461-482

11. Some Simple Experimental Designs

    • Hardeo Sahai, Mohammed I. Ageel

    Pages 483-542

12. Analysis of Variance Using Statistical Computing Packages

    • Hardeo Sahai, Mohammed I. Ageel

    Pages 543-567

13. Back Matter

    Pages 569-742

    PDF

The analysis of variance (ANOYA) models have become one of the most widely used tools of modern statistics for analyzing multifactor data. The ANOYA models provide versatile statistical tools for studying the relationship between a dependent variable and one or more independent variables. The ANOYA mod­ els are employed to determine whether different variables interact and which factors or factor combinations are most important. They are appealing because they provide a conceptually simple technique for investigating statistical rela­ tionships among different independent variables known as factors. Currently there are several texts and monographs available on the sub­ ject. However, some of them such as those of Scheffe (1959) and Fisher and McDonald (1978), are written for mathematically advanced readers, requiring a good background in calculus, matrix algebra, and statistical theory; whereas others such as Guenther (1964), Huitson (1971), and Dunn and Clark (1987), although they assume only a background in elementary algebra and statistics, treat the subject somewhat scantily and provide only a superficial discussion of the random and mixed effects analysis of variance.

• Generalized linear model
• SAS
• SPSS
• STATISTICA
• Statistik
• analysis of variance
• calculus
• classification
• correlation
• ksa
• statistics

"Intended as a text for an introductory analysis of variance service course, it requires little more than a precalculus understanding of probability, estimation, and hypothesis testing…. The student and practitioner will benefit from a well-balanced mixture of statistical theory, formulas, and explanations and the great care exercised by the authors in discussing properties and analysis of fixed, random, and mixed models in parallel…. The book employs several devices to aid readability…. In summary, the text is…a valuable source for the practitioner and nonstatistics major… It is well organized and well written at a difficulty level that precisely meets the target audience’s needs."   —JASA

• University of Puerto Rico, San Juan, USA

  Hardeo Sahai

• University of Veracruz, Xalapa, Veracruz, Mexico

  Hardeo Sahai

• Abha Campus, King Saud University, Abha, Saudi Arabia

  Mohammed I. Ageel

Policies and ethics