“…and that indicates heteroscedasticity, which means the variance of the errors is not constant,” Prof. Ed Malthouse, our favorite statistics professor.
Hetero…what? Is that even an English word? This could be a good one for the finals of the National Spelling Bee. What’s this got to do with marketing communications?
Welcome to the Analysis and Insight (AI) track at IMC. The AI track is a set of courses offered at Medill IMC for students excited about using data and analytical techniques intelligently to derive consumer insights, understand consumer behavior and build strategic marketing communications programs. As future marketers, this track trains you to make marketing and brand decisions that are backed by analytics and measurable results. This challenging sub-specialization starts with the foundations in statistics, marketing and consumer insights and moves to advanced courses in database marketing, analytical techniques and business analytics that complement each other well. The amazing AI faculty will encourage you to always look at the big picture and present both theory and practice in exciting ways. This is what sets the IMC program apart from other marketing programs.
I chose the AI track to come out of my comfort zone and add a completely different set of skills to my skill set. You are guaranteed to have an exhilarating experience working with these concepts. Battling with SPSS data will become your new favorite pastime. For those intimidated by data analysis, don’t be. I soon realized that past performance in quantitative courses has no ‘correlation’ with how you will perform in these courses. At times you are pleasantly surprised and at other times you are in state of shock. You will be introduced to cool statistical models, customer profiling techniques, segmentation methods, customer profitability analysis, web analytics and other data-mining methodologies that will ultimately aim to improve the relationship that the marketer has with its customers.
To sum up, all of us in the AI track would swear by :
Y = α + β1 * (x1) + β2 * (x2) 2 + β3 * (x3) + β4 * (x4)
where Criterion variable Y = Analysis & Insight at IMC
and
Predictor variables x1 = Excitement
x2 = Learning
x3 = SPSS
x4 = Ambiguity
……….Srividya Sridharan
