ABSTRACT
Chapter 4 presents simple and multiple linear regression analysis, appropriate techniques to assess the influence of one or more than one independent metric variable on a dependent variable, also metric. For example, how much do sales vary due to a price change? Likewise, what is the effect of advertising expenditures on sales? Chapter 4 includes the commands to perform the analysis and interpret results, such as how to evaluate the importance of each independent variable and the model explanatory power. Additionally, it shows how to incorporate qualitative independent variables, such as dummy and trend. It also discusses the main assumptions, normality, homoscedasticity, and multicollinearity. The techniques are illustrated with theoretical description, followed by an example with the SPSS commands, and the results tables with comments. The chapter also includes exercises, such as a road map to perform the analysis, an interpretative exercise with results tables, and a market context to guide a research design.
