[ COVER OF THE WEEK ]
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[ FEATURED COURSE]
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[ FEATURED READ]
People love statistics. Statistics, however, do not always love them back. The Signal and the Noise, Nate Silver’s brilliant and elegant tour of the modern science-slash-art of forecasting, shows what happens when Big Da… more
[ TIPS & TRICKS OF THE WEEK]
Save yourself from zombie apocalypse from unscalable models
One living and breathing zombie in today’s analytical models is the pulsating absence of error bars. Not every model is scalable or holds ground with increasing data. Error bars that is tagged to almost every models should be duly calibrated. As business models rake in more data the error bars keep it sensible and in check. If error bars are not accounted for, we will make our models susceptible to failure leading us to halloween that we never wants to see.
[ DATA SCIENCE Q&A]
Q:What are confounding variables?
A: * Extraneous variable in a statistical model that correlates directly or inversely with both the dependent and the independent variable
* A spurious relationship is a perceived relationship between an independent variable and a dependent variable that has been estimated incorrectly
* The estimate fails to account for the confounding factor
[ VIDEO OF THE WEEK]
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[ QUOTE OF THE WEEK]
It is a capital mistake to theorize before one has data. Insensibly, one begins to twist the facts to suit theories, instead of theories to
[ PODCAST OF THE WEEK]
[ FACT OF THE WEEK]
In the developed economies of Europe, government administrators could save more than 100 billion ($149 billion) in operational efficiency improvements alone by using big data, not including using big data to reduce fraud and errors and boost the collection of tax revenues.