Multiple Regression with a Single Dependent Variable
In this chapter we examine the principles that are basic to a proper understanding of the issues involved in the analysis of management data. The chapter cannot provide the depth of a specialized econometric book. It is, however, designed to provide the elements of econometric theory essential for a researcher to develop and evaluate regression models. Multiple regression is not a multivariate technique in the strictest sense because the focus of the analysis is a single dependent variable. Nevertheless, the multivariate normal distribution is involved in the distribution of the error term, which, combined with the fact that there are multiple independent or predictor variables, leads to considering simple multiple regression within the domain of multivariate data analysis techniques.
KeywordsMaximum Likelihood Estimator Generalize Little Square Ordinary Little Square Estimator Unrestricted Model Good Linear Unbiased Estimator
Basic Technical Readings
- Hatten, K. J., & Schendel, D. (1977). Heterogeneity within an industry: Firm conduct in the U.S. Brewing Industry, 1952–71. Strategic Management Journal, 26(2), 97–113.Google Scholar