I have enrolled in a MOOC on Coursera, Duke University’s Data Analysis and Statistical Inference. I’m having to learn a new (to me) programming language, R, that is frequently used in data analysis. I had forgotten what learning a coding language was like. It’s fun and is allowing me to build some new synapses, of which I am in dire need 🙂
I clicked once too many times and did it: I linked myself to “gangsta” and I don’t know how to unlink. It all started innocently enough; I was reading my Twitter feed when I noticed one of my friends made an interesting tweet about the Sherman (think Seattle Seahawks v 49ers last Sunday) flap. The tweet pointed out that Sherman was not a stereotypical “dumb” football player; rather he was very intelligent, having graduated from Stanford, which is no slouch of a college. She said he was articulate and could speak “gangsta” as well as “Stanford.” For some reason, that got me thinking about the current sagging pants style adopted by many teens and young men.
I knew there was a name for that style, but I couldn’t place it and wondered if “gangsta” would mean a new, less sagging style would be adopted. So I did my normal Google search for “gangsta” & “belts” (mistake 1 – not setting Google privacy properly) and a link to Amazon popped up top. Before my brain could be engaged, I clicked on the Amazon link and found myself looking at a “Gangsta-style” belt. Then it dawned 🙂 on me that Amazon had opened my account given that “Hello Dawn” was there on the screen. So now I expect to be showered with “gangsta” ads where ever I go on the web. Does anyone know how to scrub my digital footprint? 🙁
I found an article this morning that informed me that Amazon was granted a patent (in December) for a process called “Anticipatory Shipping.” My immediate suspicion was that this was more of Amazon’s extensive use of Big Data and I was right. They (Amazon) have gathered so much data on shopping habits that they can predict with great accuracy just when you will succumb to their tailored advertising and order from them. So much so that they will probably shortly be implementing the new process in their logistic system. No longer will they wait until your credit card has cleared to initiate shipping of the product you just bought. Instead, at some predetermined interval, Amazon will ship the goods from their central hubs to a location much nearer your address, if not all the way to your local UPS facility. I knew this was coming. I have seen the embryonic form of it at the Kindle store. They know my reading habits so well they tantalize me with new books just as I’m finishing my current one. They know when I’m close to the finish and hit me when I’m vulnerable. All I have to do is make “one click” and my new read is on its way. Its only a matter of time ’til they close that loop without me. http://t.co/HFALzag5NY
I teach graduate and undergraduate statistics (quantitative analysis) and I am often asked by business students struggling with the numbers “what am I really going to use this for in real life?” True it may be difficult at first to understand the relevance of pure number crunching using the binomial distribution or chi square. So I have been introducing my students to Big Data as a way to help them see the power of quantitative methods to make significant contributions in almost any field of work. We recently discussed the use of the scientific method in business and many students brought up marketing examples. I ran across this company, eMarketer, and watched a short video on their method of doing market research. I think it does a fairly good job of describing the difference between traditional market research and that now possible using Big Data. Enjoy: http://vimeo.com/81520554
I’ve been on Facebook since 2007 but have not been addicted to it until recently. That may be do to an “aging” effect that I intend to research. But I have been active enough to notice that my friends seem to have more friends that I do. And that my friends seem to do more fun and creative things than I do. I thought I was just imagining this but it seems that statisticians have been researching the phenomenon. It turns out it is not a new idea. Research into social networks first identified the trend in 1991. But current research has found some interesting things using data from a number of networks. More Big Data? http://www.technologyreview.com/view/523566/how-the-friendship-paradox-makes-your-friends-better-than-you-are/