ABSTRACT

The book focuses on problem solving for practitioners and model building for academicians under multivariate situations. This book helps readers in understanding the issues, such as knowing variability, extracting patterns, building relationships, and making objective decisions. A large number of multivariate statistical models are covered in the book. The readers will learn how a practical problem can be converted to a statistical problem and how the statistical solution can be interpreted as a practical solution.

Key features:

  • Links data generation process with statistical distributions in multivariate domain
  • Provides step by step procedure for estimating parameters of developed models
  • Provides blueprint for data driven decision making
  • Includes practical examples and case studies relevant for intended audiences

The book will help everyone involved in data driven problem solving, modeling and decision making.

part I|136 pages

Prerequisites

chapter 1|29 pages

Introduction

chapter 2|40 pages

Basic Univariate Statistics

chapter 3|64 pages

Basic Computations

part II|120 pages

Foundations of Multivariate Statistics

chapter 4|39 pages

Multivariate Descriptive Statistics

chapter 5|27 pages

Multivariate Normal Distribution

chapter 6|50 pages

Multivariate Inferential Statistics

part III|328 pages

Multivariate Models

chapter 7|64 pages

Multivariate Analysis of Variance

chapter 8|46 pages

Multiple Linear Regression

chapter 9|30 pages

Multivariate Multiple Linear Regression

chapter 10|42 pages

Path Model

chapter 11|26 pages

Principal Component Analysis

chapter 12|33 pages

Exploratory Factor Analysis

chapter 13|35 pages

Confirmatory Factor Analysis

chapter 14|48 pages

Structural Equation Modeling