Back to Tutorials HomepageMarketing Research - Tutorial 3
Overview
Measurement
Types of research designs/Causal Designs; Inferring Causality, Experimentation
First part of class
You are Keal in the Sail A' Way (A) Case. Write down your inferences from each Table. View the Tables in the following order; 1, 3, 5, 2, and 4. Based on your inferences, which ports would you target ? Why ?
Next, view the tables in the Sail A' Way (B) Case. Write down you inferences from each Table. View the Tables in the following order: 1, 3, 4, and 2; 6, 7, and 5; 10, 9, and 8; 12, 13, and 11. Based on your inferences, what demographics are related to the type of boat chosen ? What criteria should be used in targeting markets ? What size(s) of craft(s) should you buy ?
Discussion - 5 minutes
(Points to ponder - What types of evidence of causality do you have in these tables ? Can you be certain of your causal inferences ?)
Learning points
Evidence for causality: Concomitant variation; Time order of occurrence of variables; Elimination of other possible causal factors
Second part of class
View the video on smoking and write down the different studies that have attempted to show a causal link between smoking and cancer. Evaluate each of these studies in terms of inferring causality. Use the types of evidence of causality to evaluate each study. In light of these studies, what is your view of the issue.
Discussion - 5 minutes
(Point to ponder - What constitutes "proof" of causality in the social sciences ? )
Learning points
Evidence for causality: Concomitant variation; Time order of occurrence of variables; Elimination of other possible causal factors
Experiments - An experiment is a design that aims to assess causality
Extraneous variables in experiments that should be minimized/eliminated: History; Maturation; Testing; Instrument variation; Statistical regression; Selection bias; Experimental mortality
Third part of class - View the video on measurement. Evaluate the measurement in terms of reliability and validity.
Learning points
Difficulty in measurement - conceptual versus operational definitions
Measurement error - Systematic & random error
Reliability - the extent to which a measure is free of random error
Validity - does the measure measure what it aims to measure
Different types of validity-
Pragmatic - does measure predict well
Content - does the measure capture the content of a domain
Construct - what is the measure measuring (nomological, convergent,
& discriminant validity provide evidence of construct validity
Developing measures - define the domain, generate items, collect data, purify measure
Back to Marketing Research Homepag