Research Methods for Graduate Business and Social Science Students is a fundamental and easy guide to studying research methods. In addition to the general concepts relating to research methods, broad research issues and theoretical concepts critical to research are discussed. The book is written in a reader-friendly manner and contains plenty of examples and helpful practical exercises at the end of each chapter to reinforce and enjoy learning.
Chapter 13: Advanced Statistical Analysis
Advanced Statistical Analysis
In this chapter, we shall consider some of the most widely used advanced statistical methods such as factor analysis, logistic regression and path analysis. Factor analysis is widely used in business research to reflect hidden or latent variables which cannot be directly measured, but tend to be indirectly measured by other measures such as a bank or series of questions. Some examples are intelligence quotient, ambition, commitment and technical prowess.
Logistic regression is used when the outcome variable is binary or dichotomous, for example, success or failure, good credit risk or bad credit risk. In effect, there are just two outcomes. This technique has become very widely used in business decision-making, especially in the financial sector. On the other hand, path ...