MKT 3340 Lecture Notes - Lecture 8: Conjoint Analysis, Logistic Regression, Logit

• School: UT-Dallas
• Department: Marketing Management
• Course: MKT 3340
• Professor: Prasad Ashutosh

Document Summary

Regression (y = alpha + betax + epsilon) relationship between y and function of one or more x. Dummy variable regression the x variables in the regression include categorical variables: exm. brand name, color, number of doors". Logit model when the y variable in the regression is a categorical variable. Logit is used to explain choice or membership of a category. Factor analysis a technique to replace a bunch of metric variables with a smaller number (called factors) that are linear combinations of the original variables: exm. Cluster analysis a technique for clustering respondents into segments: exm. Way to incorporate customer preferences for design features into npd. Conceptualizes a product as a bundle of attributes (such as color, doors, price) at different levels (colors = blue, doors = 2, price = ). The outpoint of conjoint analysis is called part-worths: part-worth: the utility provided by each attribute level to a customer.