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Archive for November 2013

Is Job designation an intelligence Pill (a placebo)

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A year back while wasting time on Netflix, I discovered  “It’s Always Sunny in Philadelphia’. I watched couple of episodes, and was hooked on it. Though, I kept thinking that this show has low-class humor, and I wondered why did I like it?

I recommended the show to my friends. Without fail I pointed out to them that it has low-class jokes, and I don’t like the fact that I like it so much. After a week or two, I ended up reading about the show in Wikipedia, and discovered it was getting compared to Seinfeld. I liked Seinfeld, the moment I laid my eyes on it, and I liked the fact that I liked it. After all, it was a show about nothing! I thought again about “It’s Always Sunny in Philadelphia”, and collected feedback from friends about it, and decided that it’s a good show, and I don’t have to dislike myself for liking it.

So, now the 9th season is on, and there is an episode, “Flowers for Charlie“. In that episode two scientist who had developed an intelligence pill, selects Charlie as a lab rat considering the fact that he has intelligence of a rat. After taking intelligence pill, Charlie starts reading Tolstoy and Shakespeare and Hawking, denies doing any menial work in the pub, and realizes his friends are utterly stupid.  He was able to look at the real waitress too. An inane and crackpot girl, who he can’t understand why thought as love of his life for last eight seasons.

After taking all those intelligence pills, Charlie  presents the research that he claims is going to revolutionize the human society; everyone in the room is dumbfounded.

As an explanation of his stupid, Charlie-like research, the two scientists unravel that Charlie was getting placebo not the intelligence pill.

While explaining their findings both scientists show below chart. I am wondering, does that apply to corporate world?

Notice, how his arrogance increases even without increase in intelligence or knowledge.

Charlie's Arrogance

Since, now it’s a widely accepted fact that ‘It’s always Sunny in Philadelphia’ is like Seinfeld – a show about nothing, we can extract any intelligent insight we want to get out of it. I wonder whether designations or promotions in corporate world, in reality,  turns out to be placebo of  intelligence pill for most of the folks.

Of course, not everyone follows the path shown in the chart. In fact, like what analytic professionals are  striving to  apply in all walks of business, every individual might have different path. One chart like below exists for everyone at every moment of one’s professional life. Please notice the line item for ‘political awareness’ also, it means that ‘real’ knowledge might not increase significantly as we go in hierarchy, but ‘political  awareness’ certainly increases. Sometime we confound it with ‘real’ knowledge. Keeping Orwell’s ‘Animal Farm’ in context, ‘political awareness’ is what elite class flaunts as a sword over proletariat class, and proletariat class never realizes that the sword is made of  foam  that has color of iron throne.

Though, in general, lets also not discount that generally average intelligence increases as we go up the ladder. ‘A man rises up to the level of his incompetence’ is a nugget of wisdom I got from CEO of last company I worked for, and rings true to my ear the more I think about it.

Nonetheless, we have to agree that, some of us , some of the time ,are like Charlie.

its sunny 3

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Written by SK

November 20, 2013 at 5:10 am

Posted in Uncategorized

History of Statistics

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Couple of months back I did a course on Bayesian Statistics organized by SF chapter of ASA and eBay-Google . The course was really great, and I wish I were more disciplined and grasped more from the course.

The instructor, David Draper, is really great. In addition to teaching us Bayesian Statistics, he talked about the history of statistical methods. When he talked about hypothesis testing and Neyman, he talked about the tools that we had in 1930’s with us.  To me, it was like, you teleport yourself to 30’s, and forget all the learning and tools (computers) we had so far in 100 years, and make yourself aware of the challenges and prejudices faced by scientific community of that time, and try to come up withsomething – that future generation would know as hypothesis testing.

Not just that when David Draper talked about Jerzy Neyman  he talked about Roland Fisher, when he talked about Fisher, he talked about Karl Pearson. He mentioned a book on history of statistics. As far as I recall, it was a book by Stephen M. Stigler, Statistics on the table. Though I am not sure, and I have to ask him again.

But, in any case, I ended up buying two books on history of Statistics and statistical methods, that I received last night . The book ‘Statistics on the Table’ and ‘The Lady Tasting Tea’. Since The Lady Tasting Tea talks about Statistics of the twentieth century, I am going to start with this. Or, pondering over my choice for a while,I think, I might be starting with this one because the book cover is more interesting – a cup of tea with a piece of lemon tucked on it, resting over chess-board styled tiled floor, and a lady with a hat on, not facing the cup, but  looking at the horizon where the sun is taking shelter for the night.

I just hope this book makes me smarter enough to design an experiment to find out the underlying reason of my choice – even with a sample size of one, as in my case.

Written by SK

November 13, 2013 at 4:44 pm

Posted in Uncategorized

YouTube Recommendation Engine

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While watching a YouTube video I was pleasantly surprised to see a video recommendation. I was watching a Hindi song, and got recommendation of an interview of P!nk on a topic that was highly relevant to the theme of the song. If you have seen the movie Abhiman, you are certainly going to be impressed with the recommendation!

recommendation Engine

Have YouTube statistical modelers  made their recommendation engine advance enough to recommend us videos based on our mood/sentiment?  I doubt that.

To understand, lets just think of the data YouTube collected from my activities. I watched couple of P!nk video. I am not sure whether I listened to any Hindi songs in the last couple of weeks, but that’s not of enough relevance here.  Now the possible hypothesis could be:

a:) YouTube knows I watch P!nk videos along with many more videos. Quite possible that randomly, just by sheer chance, it recommended me to watch one of the P1nk video.   Relevance of sentiment was just a fluke.  Well, this is always a possibility, and in fact, number of times chance and randomness are answers to so many puzzles we bump our head to. But, I am positive, recommendation engine is smarter than this.

b:) It’s quite possible, YouTube might have bucketed all the videos in their database based on ‘sentiments’. The video from Abhiman might have been bucketed under the same ‘sentiment’ as the interview of P1nk. Hence, the moment I watch the Abhiman video, YouTube recommended me a video  with the same sentiment, and of someone I watch.  I would guess YouTube might have started using this approach for number of recommendation, but I have some reservation around how well they might be using the approach. It’s difficult as you have to bucket a video in millions of group across multiple dimension. Sometime user generated ‘sentiment group’ is the answer, but getting as much data as you really want is a challenge.

c:) The third possibility could be the  approach that was, and it still is, the core of most of recommendation engines. There might be someone who would have watched the Abhiman video, and the same guy might have watched the P1nk video as well. Millions would have watched Abhiman, and most of them won’t have watched P!nk video subsequently. So, the recommendation rule tagged me along with a guy who watched P1nk video, as I too like P!nk video.

If you think about it, the real business rule could be a combination of any of the three hypothesis, including the one based on randomness. But, in any case, it was nice to  get the recommendation as I really ended up watching it.

Written by SK

November 6, 2013 at 7:04 am

Posted in Uncategorized

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