360° Coverage : Don't Underestimate Big Data

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Don't Underestimate Big Data

Apr 15 2014, 9:03pm CDT | by

The techniques of big data have been criticized recently in a post by Tim Harford among others. It’s quite easy to imagine the potential here has been exaggerated, and a core point about the...

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15 weeks ago

Don't Underestimate Big Data

Apr 15 2014, 9:03pm CDT | by

The techniques of big data have been criticized recently in a post by Tim Harford among others. It’s quite easy to imagine the potential here has been exaggerated, and a core point about the importance of theory in a lot of empiricism is undeniable. But I think there is some overreach in the criticisms, and in particular one of the failure examples Tim gives shows the opposite of what he claims. He points to a flu forecast by google that failed:

Four years after the original Nature paper was published, Nature News had sad tidings to convey: the latest flu outbreak had claimed an unexpected victim: Google Flu Trends. After reliably providing a swift and accurate account of flu outbreaks for several winters, the theory-free, data-rich model had lost its nose for where flu was going. Google’s model pointed to a severe outbreak but when the slow-and-steady data from the CDC arrived, they showed that Google’s estimates of the spread of flu-like illnesses were overstated by almost a factor of two.

What happened here is in fact one of the advantages of big data: the ability to reject models due to frequently updating data. Google provided a forecast and the forecast and the model underlying it was unequivocably debunked. What a novelty for the social sciences! Of course big data isn’t alone in having constantly updating forecasts that can be tested against reality, but the focus on forecasting and constantly updating data is one of the advantages it has over many other areas of the social sciences. Yes, google made a model and it was falsified. But keep in mind the famous claim John Ioniaddes that most published research findings are false. Maybe it is most, or maybe it’s only half or a quarter. But with big data if a large percent of your findings are false you find out sooner rather than later.

Indeed it is the forecast driven nature of machine learning that makes it so appealing as a branch of empiricism. Maybe this is something you can’t appreciate if you haven’t actually spent time with a big dataset with lots of variables and seen how potentially easy it is to pick the wrong model, or if you haven’t taken a look at the statistical guts of disagreeing research papers. But this focus on the right model being the one that makes the best out of sample predictions, and the ability to be constantly running out-of-sample predictions just seems so much more tied to reality than most research has to be.

Another thing that I think people miss is there is too much focus on what a really long dataset does to, for example, the probability of spurious correlations. What makes machine learning interesting isn’t just dealing with long dataset, but really wide datasets. Consider the data that Netflix has on it’s customers. This isn’t remarkable because of how many people are in the dataset, but how much you know about them. Yes it’s true what they say about spurious correlations, but if you do an out-of-sample prediction with a spurious correlation the relationship will be falsified quickly no matter what your p-value.

In 2001, the statisticisn Leo Breiman wrote a paper titled “Statistical Modeling: The Two Cultures” where he contrasted the data modeling culture and the algorithmic modeling cultures that compete among statisticians. The data modeling culture used goodness-of-fit tests and residual examination to validate models, while the algorithmic modeling culture focused on out-of-sample predictions. He estimated that 98% of all statisticians fell into the former camp, and only 2% fell into the latter. I’m not sure what the numbers are today, and surely many fall into both camps, but the percent of statisticians who are algorithmic folks and the percent of important problems they are working on has gone up sharply from 2%.

It’s true that misleading p-values are a consequence of a lot of data, but this is a data modeling culture problem, not an algorithmic modeling culture problem.

Now don’t get me wrong, I am for the most part a p-value checking, residual examining, data modeling culture economist. But machine learning and big data are going to get more important not less, and I think social scientists who don’t learn to at least think like the other culture are going to be left behind.

 
Update
10

7 weeks ago

RM47mil KWSG contributions still unclaimed

Jun 9 2014 7:54am CDT | Source: Business Times Malaysia

KUALA LUMPUR: About RM47 million of contributions in the Teachers Provident Fund (KWSG) still remain unclaimed, the ...
Source: Business Times Malaysia   Full article at: Business Times Malaysia
 

 
Update
9

7 weeks ago

Gold shop lost almost RM1mil

Jun 9 2014 3:50am CDT | Source: Business Times Malaysia

KANGAR: A gold shop owner lost almost RM1 million after after the safe on in his shop was brok ...
Source: Business Times Malaysia   Full article at: Business Times Malaysia
 

 
Update
8

7 weeks ago

Motion to debate MAS losses in Dewan Rakyat rejected

Jun 9 2014 3:39am CDT | Source: Business Times Malaysia

KUALA LUMPUR: AN emergency motion to debate the losses incurred by Malaysia Airlines last year, amounting to RM1.2 billion was rej ...
Source: Business Times Malaysia   Full article at: Business Times Malaysia
 

 
Update
7

7 weeks ago

MH370 Tragedy: Hisham: RM27.6 mil spent on 1st phase of SAR

Jun 9 2014 2:11am CDT | Source: Business Times Malaysia

KUALA LUMPUR: Malaysia spent some RM27.6 million in its first phase of the search operations for missing Malaysia Airline flight MH370, said Acting Transport Min ...
Source: Business Times Malaysia   Full article at: Business Times Malaysia
 

 
Update
6

7 weeks ago

9.1m litres of diesel seized in a month

Jun 8 2014 1:11am CDT | Source: Business Times Malaysia

PUTRAJAYA: The Domestic Trade, Cooperatives, and Consumerism ministry has seized some 9.1 million litres of diesel and property worth RM58 million since mounting ‘Operasi Diesel Selatan’ in the southe ...
Source: Business Times Malaysia   Full article at: Business Times Malaysia
 

 
Update
5

8 weeks ago

Girl, 9, awarded RM2.78m compensation for medical negligence

Jun 6 2014 4:56am CDT | Source: Business Times Malaysia

KUALA LUMPUR: A nine-year-old girl who suffered brain damage during her birth at a government hospital was awarded over RM2.78 millio ...
Source: Business Times Malaysia   Full article at: Business Times Malaysia
 

 
Update
4

8 weeks ago

Malaysia's total trade in April up 12pc

Jun 5 2014 11:52pm CDT | Source: Business Times Malaysia

KUALA LUMPUR: Malaysia's total trade in April 2014 rose by 12 per cent from a year ago to RM123.86 billion due to growing trading activities, International Trade and Industry Minister Datuk Seri Musta ...
Source: Business Times Malaysia   Full article at: Business Times Malaysia
 

 
Update
3

8 weeks ago

Works Ministry to spend RM20m for upgrading works at 50 accident black spots

Jun 4 2014 11:35pm CDT | Source: Business Times Malaysia

JOHOR BARU: The Works Ministry will implement upgrading works at 50 accident prone locations in the country that have been identified this year invol ...
Source: Business Times Malaysia   Full article at: Business Times Malaysia
 

 
Update
2

8 weeks ago

Najib launches loan scheme for Ramadan traders

Jun 4 2014 10:24pm CDT | Source: Business Times Malaysia

PUTRAJAYA: Prime Minister Datuk Seri Najib Razak today launches RM45 million Ramadan Bazaar Sch ...
Source: Business Times Malaysia   Full article at: Business Times Malaysia
 

 
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1

8 weeks ago

Residents bring up objection against Kidex to Suhakam

Jun 4 2014 4:49am CDT | Source: Business Times Malaysia

PETALING JAYA: A group of 20 Petaling Jaya residents held a meeting with the Human Rights Commission of Malaysia (Suhakam) over their objection against the proposed RM2.2 billion Kinr ...
Source: Business Times Malaysia   Full article at: Business Times Malaysia
 

 

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