Summary Measures in Business Analytics

Summary Measures in Business Analytics: location measures, measures of dispersion, shape, and association; boxplots and z scores.

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Ways to Speed Up R

Speeding up R computation for simulation or package purposes.

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The year changed Tech dramatically 2007

Several big innovations that benefit you most

When you talk about the new Netflix series “House of Cards” on your iPhone 7 plus in you left hand, you may find more and more people on the street are using fancy Android mobile phone which makes you worry about whether the next generation of iPhone is worth to buy. Likewise, some easily missed technologies that benefit you a lot such as AWS, Prime Video also initiated in the same year, 2007. You may get used to them today and think that they are necessary parts of your daily life. But before 2007, they all are bound by network infrastructure.

Things are changed due to the network upgrade and launch of the App Store.

It’s intuitive to think that the expansion of statistical learning algorithms and computational power will promote the next upheaval in human society. The popularity of AI is based on mathematics, statistical methods but not limited to those narrow nature sciences which we know for centuries. Without the healthy development of these “next-generation infrastructure”, just think of it as a body but no sapiential “brain”. Without the “brain”, the AI, VR, Google Brain, Smart City wouldn’t come true.

All human knowledge as a whole will be evolved to break the boundaries that we think they are, no matter good or bad. Nature selection over the past billions of years was only led by a randomly utilizing process that optimal the number of species or just live or die. The development of AI will dwarf this complicated but not sole evolution path. The rule and the destination are rooted in the whole design of the fate of AI. The evil idea leads to releasing of demons, whereas optimizing human knowledge could lead to a world with sophisticated but elegant knowledge object.


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The Sample Selection Model

Sample selction is also called as incidental truncation. Simply say, it means the sample was not randomly selected from the total population. Some specific sample are neglect when research is collecting samples.