Quarter 10 - Week 6

It's been a reasonably calm week, not much out of the ordinary. The profs continue to remind us about the upcoming projects so that we don't go crazy in the last one week. They're still very optimistic. Their faith in us is troubling... or rather guilt-inducing. Whatever works, right?

Business Data Mining & Decision Models

We continue with labs this week, we've been doing stuff on K-clusters and Decision trees. The funda of the first is simple, take reams of data and let the software (Clementine in this case) work its magic on it to bundle them into clusters. The more clusters you decide to have, the more 'internally aligned' the clusters are supposed to get. So, after a little hulabaloo, you get 4-5 clusters with descriptions like (Male, under 30's, <50000$ income), (Females, over 40s, >30000$ income)... etc etc. The second session had us doing decision trees, where we feed in a bunch of inputs to the software, drag in a model and 'train' it with one part of a data set. We then just apply the trained model to the rest of the dataset and check if it still accurately identifies the type of output we're expecting (based on its understanding of the training data set). Totally takes the fun out of number crunching, but saves us a heck of a lot of time. Yay. And here I thought, the point of number crunching was to identify some human aspects of what were evidently just becoming statistics.

Strategic Thinking and Decision Making

A very creative midterm, if you ask me. The prof tries to compare a Prisoner's Dilemma with a marriage, and asks us what strategies go where. Or he asks us why Apple comes out with an iTunes store, what's the point of it? Was it strategic, or a hint from God? Some questions like that, which required us to think, assume and chew on. Finally when we start discussing the solution, heated debates about what assumptions are right, what weren't. Why one answer is as good as another... sigh, that's probably why some IIMB profs stopped getting creative with their questions. It's difficult to 'hold on' to assumptions...

We were supposed to do a case in the next session, but apparently EVERYONE forgot there was a case, and didnt even realize that the handout wasn't in the book. The perplexed prof has come totally prepared for a heated case discussion, and then realizes to his consternation that the guys in class didn't even realize there was a case (though in our defense, we had a friggin' midterm!). So already tired from the debate, and the futility of it all, the class gets cancelled and for the first time... in our time at IIMB... we were left with a free period. I should be happy! Wonder why it doesn't feel good then.

Quarter 10 - Week 5

It's the usual calm before the storm... midterms are beginning this week, project proposals are also expected to be turned in. The guys working on their final projects are frantically running around trying to give some shape to their mid-term submissions. The profs have now stopped chiding us on the fact that we're not reading the readings, and have not sarcastically taken on to the 'In the reading you SHOULD have read, the saying goes...'. Everything's normal, we're in the midst of the sea and there are no rocks to crash against, yet.

Business Data Mining & Decision Models

We're coming to the more complex data mining modes - we just began with text mining this week. The prof takes examples of how words by themselves are not as important as n-grams. These n-grams are certain combination of words that actually have a sensible meaning. For e.g. 'great' is a good word, but 'not great' implies sometihng else entirely, while 'not great aesthetics' implies yet another meaning. Hence, he goes on about a case where they had to identify trends based on feedback left behind on something. I'd have been more specific, but I'd fallen asleep thinking of n-grams.

The second session was our first practical session on Clementine... which does some pretty cool stuff with data. It's like excel, only that you can do some cool graph-y things with it. Combine data sets, filter stuff out, sort it, sample it... and finally display or extract stuff. And we got to work on a cool data set too! One of login data of students and profs.. probably to check attendance and other such stuff. Good fun...

Strategic Thinking and Decision Making

We continue down the emotion route... further refining our understanding of Game Theory. Apparently, humans are lazy, that's a shocker! They tend to make decisions based on incomplete information and rely a helluva lot on their intuition. Again, such a shocker. The funda appears to be bounded rationality. We tend to look for answers, and will continue looking till we get what we deem to be a satisfying answers, and not the optimal one. We also seem to have some sort of an opinion bias? We are more likely to think our harebrained ideas are the awesomest, while some brilliant ideas from others are downright crappy. Apparently, our intuitive part of the brain is different from the reasoning part of the brain. What makes it worse, is that we can't realize when our intuition is suggesting something downright wrong.

We're also quite risk averse! If we're getting a chance to look at good things happening, and are confronted with two options, we're more likely to take the less risky one. And if we're getting a chance to look at bad things happening, and are offered two options, we think 'what the hell' and are willing to take much riskier options. So, interestingly, the way a problem is phrased to you ends up with you taking different decisions. Good tip to have, no? It's one of the reasons we stay invested in a market that's obviously going down (because we *think* it will come back up again anyway), or why we don't invest in markets when they're going up (what if it goes down?). Interesting to know how nutty we can get!

Quarter 10 - Week 4

It's about that time of the quarter when people suddenly realize that they're supposed to settle down on a project topic, and then heated debates rise on what to study. The debates essentially come down to convenience vs. interest... 'my topic is easy', 'yes, well, mine is easier!' or the 'Man, let's study social networks!', 'Are you crazy?! Let's do a system that can rival S & P's credit ratings of countries!' to the ever glorious 'The prof doesn't understand your topic, we'll get less marks', 'The prof doesn't understand my topic, we'll get more marks!'

Business Data Mining & Decision Models

This week was supposed to be about pruning/cleaning data. It might come as a shocker to you, but people aren't collecting stats on their companies/divisions/teams so that data analysts can come and do one click with their mice with a magical flourish and charge them a bomb. Everyone wants to make everyone else work, so they deviously collect some data in one form, some related data in the other, jumble the two up and generously offer the analyst some tossed salad. If that weren't enough, they will specifically allow users to half-enter their data (in response to surveys etc.) and submit it, without offering the 'Fill everything, or you dont go further!' clause. Hence, the analyst has the mind-numbing job of having to sift through the data, find out what goes where... neatly order it, find some intellectual way of filling the missing data.... and THEN he clicks the magic button. The prof takes us through multiple examples where given a subset of data, how would one go about gleaning enough to complete the dataset. Appeared to be fun, will know for sure when we start.

Strategic Thinking and Decision Making

We had a quiz worth 20 percent of the overall count, so we justifiably had a reason not to go through the readings for the day. The prof enters the class, and is eagerly getting ready to talk of the Cuban missile crisis, and describe the various mechanics at game theory at work! And he asks 'What do you guys think??'... Pin-drop silence. Even the crickets that typically make an appearance here and answer in an unknown 'crik-crik's were silent, presumably since they were studying for the quiz as well. The prof fumes on how we've got to catch up, this is nothing, the readings are tiny compared to what we'll get later... and I'm guessing he doesn't realize that it is not really a motivating line to begin with.

In any case, we continue discussions around game theory, about how the Cuban missile crisis was an example of how the two most publicly powerful people at the time signalled their intentions to each other and how the world was at the brink of a nuclear war. Then, for the first time there was a little addition of emotion to rationality. The prof makes us play a few games, and then he questions why we don't behave rationally... and then brings in a sense of fair-play etc. to the table. Apparently, if I was offered a 100 bucks, on the condition that I share it with someone... I could come to you and say here's 10 bucks, I'll keep 90 and you're likely to show me the finger, maybe give me two rupees due to my apparently dismal state. What you don't realize is that if you don't accept the 10 bucks, you get nothing anyway. So you have nothing to lose even if I were to give you ONE buck. By choosing to walk away, you show how you bring a sense of fairness to the game. You'd rather take no money than take a pittance or unequal share. And hence, we begin our descent into the nature of the human aspects of the decision making process.

Quarter 10 - Week 3

The IIMB Vistas are coming up, and the buildup is palpable. Some of the final years have finally begun to ponder if now's a good time to take part in the fest, considering it's their last time to do so! The first years are enthusiastic, some with starry eyes... the others with a newbie enthusiasm to make their mark. The second years are busy co-ordinating, from the PGSEM side of things... to ensure that we do our bit. Pretty much like a family when you think of it... the grand-people are thinking if they've done enough to leave their mark in the sands of time, the young want to go out there and rule the world, and the stuck-in-the-middles are busy paying all the bills.

Business Data Mining & Decision Models

This course name is still such a mouthful, I have to check the previous blog posts to know what the name really is. This week we move along with more means of analysis, and we cover Artifical Neural Networks and Logistic Regression. The funda from the Neural Networks is pretty simple. Assume you have a black box, and you know that there are some inputs going in one end, and some output coming out the other. You take a sample, look at the values and arrive at what weights are to be associated with them in order to get the result. Then you take the next sample, and by applying a set of simple formulae, you find out how wrong the previous weights were and correct the weights based on the current inputs to get the output. And the cycle goes on and on, till hopefully you have such a confused set of weights that begins to predict what the output should be given a set of input values. The prof covers the funda with a case where he used such a thing, and then we marvel at how accurate something can be, and give a contemptuous smirk at all the previous methods we learnt over the last two weeks. Artificial Intelligence rules!!

The next session when we read about Logistic Regression, we find out about how this uses an exponential function to find out what the effect of the input variables can be. While explaining all of it, the prof decides to show us another case study where he applied this and how it gave all awesome results, and we smirk again at the uselessness of the other methods in this study. Funnily enough, this time the Neural Networks method was pretty bad. So, the question then arises that if all the models have an insanely unpredictable error rate, how do you identify the best one for use on incoming data, when it cant even predict past data as accurately. To which the prof sagely responds - It depends on the input format. If you use continuous variables in these two, and bins in those two, then this method is better else that method is better. That's just convenient if you ask me - Tomato / Tomaahto! A value is a value, how does it being continuous affect the model to be used is beyond me, but I didn't do the PhD or run the painstaking tests and examples, so I'll leave it to the wizened old goats and trust their statements as I've done for the last 2.5 years.

P.S. Yet another difference between the PGP and the PGSEM came forth this week - We seem to have a PGP-er attending the class alongwith us, and the chap is definitely the most inspired by this prof. How would I know? Because while his eyes are focussed on the prof like the latter's a wonder of the world, and the prof's simplest joke or statement is met with a wide grin or a vigorous nod or scribble, some of the PGSEMers are more interested in his reactions than the prof. Analytics must really be their holy grail, if they are dive this deep in a lecture. I'm guessing the prof realized he's losing our attention, because he now cracks fewer jokes. Therefore, to be mesmerized 150% or not to be, that's the difference between the young and the 'experienced'. (Bows to a rumbling applause, and a few delirious fainting acts for the earth-shattering gyaan)

Strategic Thinking and Decision Making

'Tis a game this week, and one where a number of PGSEM team look forward to tearing the guts out of one another to be the top boss! Our prof thought now'd be a good time to let us try out rules of game theory, and so asks us to be ready with a strategy to take on the other teams. And so we prepare over the week and come to class, only to realize that the rest of the class is just as nuts as we are! To put it simply, the game was five round of bidding for business and at the very first round, one of the team lands a shocker by going so deep that the rest of the people go blank for a second. From then on, we ran around trying to figure what the other crazy people might do to get the order, and we went into mutual demolition. The price of the winning tender kept going lower and lower... till finally we look at the numbers and realize exactly why this happens in the real world as well.

We then move into some theory, to understand how people can resolve the prisoner's dilemma. After hearing them, I just wonder why we need to learn strategy when obviously the answers lie in the good ol' religious tomes. Be good, care for others, don't fight, forgive people etc. are the way to go in long term relationships. It's not put as lightly as I just did... there's obviously tons of backing, because hey, it's strategy and its based on inter-entity behaviour. The prof ends with a reminder of the quiz next week, and as usual threatens us enough about reading the soporific chapters early on, if we are to do well.

Not much else on campus, other than a guest lecture on Open Innovation. The preps seem to be in full swing for the Vistas, the students seem concerned about the type of projects to choose, it's a normal week.

Quarter 10 - Week 2

The weather's been surprisingly accommodating thus far, rains when we're in class, stops when we're out of class. My fellow students seem reasonably chirpy too... you'd think that after nine quarters they'd know these are short-lived moments of joy, but they seem to like living life in the moment. I'm a lot more chilled out so far, you wouldn't believe how relaxing it is to take just two subjects instead of the standard three... phew!

Business Data Mining & Decision Models

Ok, so I might be a little TOO relaxed. I fell asleep in the first session... I dont even know why! I'm getting enough sleep nowadays, for God's sakes! I remember some fundas about how you shouldn't overcook your analysis. Apparently, when you have your data set, you randomly select 70% of the values and run your magic on it. Fry, Flip and once your gyaan is condensed, you apply your analysis on a randomly selected 30% data from your set. If the values are very close and matching, then you know its not overcooked. He obviously said a lot more, but hey... if you don't fall asleep in a class, you don' give a chance for subliminal learning (You know, let your subconscious do some work), and therefore you're not really learning anything...

The second session was a lot of practical examples that made use of the learning from the first class. The prof takes an example of how they studied sericulture (silkworms stuff) and how they helped add some method-of-madness to the quality grading procedure. Apparently they ran some tests on a sample of 100 silkworm cocoons on various parameters of quality, and where able to find a condensed and quick mean for farmers to get their produced judged and paid for. I'm reasonably sure that I've learnt everything I missed on the previous session, this can be confirmed only during our midterm in a few weeks.

Strategic Thinking and Decision Making

Today's class easily makes it into my top-5 list of most active sessions. The criteria for judging is simple. The number of open eyes and fishmarket noise when the teacher is present, but where everything is directed at one destination(the prof) and everyone's vehemently arguing about points that they think is right. The prof knows how to make his examples - he actually 'localized' the examples from the textbook and added a few more examples of his own. Kept the class active for most of the two sessions (except for the last half hour in the second session, where he left us looking at twirling stars).

During the course of the classes, he managed to convince me that icecreams are a very diabolical device meant to force strategic thinking in innocent young minds - especially siblings. Most parents have a very simple formula for icecream sharing - Get one to cut, and the other to choose his half. This prof applies strategy. And because he knows it will be too easy, he forces us to consider that the icecream can melt. Therefore, there's a money value of time (Ahaah! No you finance chaps, I'm NOT talking time value of money, I really AM talking money value of time!). Did you know that if the icecream melts with an even number of negotiation rounds, people share 50:50, but if it melts with an odd number, people take an advantage of n/(2n+1):n+1/(2n+1). Get in touch with me, I'll explain why! Oh, charges of Rs. 3000 apply.

If that wasn't enough, he gives examples of husbands and wives who want to spend time together, but one likes sports and the other likes movies. So who wins? Again, ask any normal person, and he'll say 'Listen to the wife. Long-term happiness over short-term gain'. But the prof made a 2 by 2! And via this he actually explained a Nash equilibrium, a dominated and a dominant strategy! Therefore, if you've been wondering how your parent/spouse is constantly getting the better of you, and if they have an MBA, you should know... it's not their fault. There's an even bigger sinister plot running in front of you!

While the class was definitely a lot of fun, and informative... the principles of game theory acknowledge one major shortcoming, the choices made are completely rational and thought of as the gains to the individual not as gains or harms to the opponent. It will be a while before we attempt to solve what happens if the opponent is in real life (thereby allowing emotional variables) or if the opponent is just plain dumb (Good luck trying to play the Nash game with a real dumass partner). The quiz for this is dawning up quite fast, so we've got some heavy reading to do... and a game to be ready for next week. Quite entertaining, thus far!

In the meantime, there's a ton of activity around the upcoming Vista fest at IIMB. We have a few corporate events too, hence external invitation is really welcomed! If you're interested, check out the site: http://www.iimb-vista.com and register for it! As a corp junkie, here's your chance to experience college life again! :)

Quarter 10 - Week 1

Snifffffff..... do you smell that? Of course you don't, unless you're from my batch! It's the smell of vacant weekends and jobless evenings in the near future. Many of our classmates have taken on a radiant glow, and I'm guessing it has nothing to do with better face wash products.

Just because I am going to be here till next quarter because there's a couple of awesome subjects I want to take, I've taken the phenomenal decision of doing only two courses this quarter! Yes, two! I'm expecting that it will result in increased concentration in these subjects, to an extent of an extra 50%! I have not factored in the 'Going-to-leave-shortly' aspect, but the dampening factor of the same can be calculated at the end of the quarter based on the deviation from the mean... BUTTT I DIGRESS!

Business Data Mining & Decision Models (BDMDM)

I took the course just because it has such a big name, and the abbreviation sounds like thunder. Actually no, but I wouldn't put it beyond me. The name is so obviously suggesting the amount of trouble it can cause, it would be a crime not to undergo the pain of it! We don't really come to study to have a fun life now, do we...

The first week was reasonably intriguing. The prof knows his stuff, and has a way of describing the problems in a imaginative manner. If he fails to help you picturize the complexity in your head, he'll have it drawn up on the presentation so you have no doubt about the fact that you're confused. He also spoke about how business data mining has evolved, from just simple metrics collection to metrics analysis. While making it absolutely clear that we are going to suffer under the load of the project, he has also managed to convince me on the value of doing this course. This week, we looked at cluster analysis and how this differs from cluster sampling (diametrically opposite in fact! These mathematicians have no sense on how to name things, thats for sure!) and we then went on to discuss how clustering can be done from the many different angles. Looks set to be an interesting course, especially since there's only one textbook which, in all probability, we wont read, and sets of slides that will be shared!

Strategic Thinking & Decision Making (STDM)

Fortunately not as dangerous sounding, this course attempts to explain the thought process behind decision making by people. I'd have put this down as an OB course, given the chance. This prof is very engaging, but the catch is that you need to get on his boat right at the start! If you happen to disengage in the middle of class over a game of Angry Birds, and then suddenly pay attention... you get completely flustered at the jargon being thrown your way! Therefore, the important lesson would be to avoid the Angry Bird. Or don't play the game.

For the first week, after the standard 'study-your-ass-out-or-else' sermon to a set of bored-looking 'Been there, heard that' students... the prof gets down to some practical examples. Takes up a mini case and asks us our thoughts on whether the decision taken was right or not. After a bunch of suggestions from the class, he breaks down what seems like a 'poor-chap' case into a set of discrete 'if-then' and 'cause-effect' scenarios. Talks of what would happen if you do this, or do that... about what the other person has in his mind, and why he should cede to your point-of-view. That seemed enough to get the class hooked, as he went on to explain in light sciency terms about why people make the decisions they do, and how it turns out. Something tells me that some of the students didn't realize what the course entailed, as after the break there was approximate 3/4 of the class around. The rest, having realized this has more to do with the fundas behind decision-making and not with actual strategic frameworks, had strategically decided to bolt out the door!

We then also spent some time discussing Game Theory, and it pretty shortly came about that the underlying principle is that every man's for himself. This intensely individualistic appeal also came about to explain how people look at the immediate short term, under the rules of Game Theory, than the collective long term perspective. Therefore, my takeaway was that Game Theory needs an infusion of collective thinking if it should take into account long-term prospects. Having said that, it's not the Game Theory itself that needs fixing... it's the inherent programming of the individual, who's being told to look out only for himself. A tall prospect, which probably explains why not much has happened to influence this theory in quite a while.

All in all, it sounds like it will be a fun quarter... I haven't done many quant subjects since my first year, and BDMDM seems to pose a good enough challenge. Similarly, strategy not being my weapon of choice, gets SOME makeover with STDM. Hopefully, I'll learn more consumer behaviour from this, and 'enhance' my Marketing knowhow!

Quarter 9 - Week of Exams

The halls seem a lot quieter, and you wonder if it's because we are going to have fewer people in our classes now that a few of our classmates are done. And then you realize it's because you are one of the few miserable students who's exams are starting at 8 when everyone else gets to start at 11 AM!

The mood had its mix, the outgoing students had their share of nostalgia and relief, more of the latter. They couldn't wait to snatch their weekends back... and their gleeful statements makes everyone else switch from a state of wistfulness of losing time with fellow comrades, to a state of vengeful fury. But that still didn't stand in the way of a horde of our batch waiting till the end of Friday so that we could snap some pics with the first set of pass-outs! :)

Consumer Behaviour

Knowing our prof, it wasn't surprising that we spent 10 minutes gazing at the paper going 'What the %#$%#', following it with thumbing (or rather frantically rustling) through the pages going 'Where the ^%$^$', with an 'I'm ^#$%@&-ed' with half an hour to spare for the end of the exam. Apparently, it wasn't that bad for everyone, a few of the students actually knew what the paper was about, so they went ahead and analysed it this way and that. I'm just glad that the exam's all done.

I didn't have any other exams this week, so all that's left is an assignment that needs to be submitted by Saturday. Once that's done, Q10 is just a week away.