Updates on Session 9

Hi all,

Session 9 is done. One more to go.

1. Notes from Today's session:

We covered a lot in this rather eclectic session - from Hypothesis formulation to Social network analysis (SNA). A few quick notes on the same:

i. Hypothesis formulation and testing fits neatly into the Causal research (Experimentation) topic that we did in Session 7. After all, logical, measurable hypotheses underlie the experimental method.

ii. The two types of tests we did - Association (chi-square) and Differences (t-tests) cover the majority of situations you are likely to face. However, even for other, more esoteric testing requirements R is handy and available.

iii. Regression modeling borrows much from your Stats core. However, even if repetitive, I couldn't risk leaving it out as IMO, basic regression modeling forms a critical part of tomorrow's Mktg manager's repertoire.

iv. The 3 basic regression variants we covered viz., quadratic terms (for ideal points estimation), log-log models (for elasticities) and interaction effects open up a lot of space for managers to maneuver and test conjectures in.

v. The SNA portion was new to me too, in a sense. I'd done my network theory basics way back in grad study but getting back in touch felt good. SNA going forward will gain in importance and applicability. Already we saw the kind of Qs it is able to provide guidance and answers for.

vi. We've only scratched the surface where SNA is concerned. R's capabilities extend further but let me quickly admit that I have myself not explored very far in this area. A big limitation on SNA is how much data we can collect from Twitter, FB etc when their connection APIs set rather small automated limits for downloading data.

vii. The R code and data for today's classwork is up on LMS. Pls try to replicate at home, interested folks can generally play around with the code and see.

2. Regarding SNA data:

Folks, normally I would remove identifying information about students from the data but in this case (and in the JSM homework case which called for individual level plots), that was not possible. so the identifying information remains.

Pls remember: Since only 6 friends could be listed, its not possible for people to list all their friends. Hence some names might be missing in the SNA dataset of Co2014. Pls take that in the right spirit rather than blame anybody for non-reciprocity.

Bottomline: I don't want MKTR to be remembered for any negative reasons whatsoever.

3. Some Announcements:

a. Those who have missed filling up a survey can also take up the 2-page write-up assignment I'd given earlier to folks who'd missed pre-read quizzes, here, at this link. Deadline is Thursday.

b. There will be 5 pre-read quizzes in all (including the session 10 one). I'll consider your top 4 scores for grading. So if you performed really badly on one, you can let it go.

c. Update: I have decided to drop this reading from your pre-read list for session 10.You have two pre-reads for session 10. One is this McKinsey article: Capturing Business Value with Social Technologies. Scan it quickly, doesn't require a very in depth read, IMHO. But the general ideas should be clear.

d. Your other pre-read for session 10 is a famous Wired article from 2004 which went on to become a major 2007 book on the subject: The Long Tail, by Chris Anderson. Its an excellent article on a new economic paradigm enabled by technology.

e. The practice exam is up on LMS. Its solution is up too. But only those Qs which have one clear answer have been solved. More open-ended Qs have been left blank. The practice exam is a good template for what you can expect to see in the end-term. Most pre-reads per se will not come unless explicitly covered in the slides, as you can see in the practice exam.

f. I solved Session 8 HW again. The findAssoc() function seems to do OK for Qs 1-9. So keep it as is. FindAssocs() is not needed for the Amazon reviews analysis anyway.

Well, that's it from me for now. See you on Thursday.

Sudhir