Time use patterns in the last decade

Alexander Fishkov

Alexander Fishkov, Ph.D. student Computer Science

In this post, we will explore the data from the American Time Use Survey and attempt to put the numbers in perspective — using data for the years of 2003-2014 will show us changes in daily activities in the last decade.

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Measuring health levels in the US

Andrey Kamenov

Andrey Kamenov, Ph.D. Probability and Statistics

A question in a survey conducted by the Centers for Disease Control and Prevention asked a respondent to assess his or her own health. Just one in every six people considered their own health “excellent”; most stuck to “very good” or even just “good.” But how do we use this data to visualize the relationship between health levels and other factors?

The problem is, the scale itself is not quantitative. It doesn’t explicitly state how much better “good” is than “fair”.

In order to measure the health levels of specific groups in the general population, we’ll use a quite common procedure. It provides values between 0 percent (meaning all respondents have poor health) and 100 percent (where everyone has excellent health). The exact values of everything in between are based on the (empirical) nationwide percentages.

Let’s see how our health index fares against two of the most obvious factors. The first chart shows the speed of peoples’ self-perceived decline in health with age:

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Are smaller Research and Development businesses more effective?

Andrey Kamenov

Andrey Kamenov, Ph.D. Probability and Statistics

As we saw in an earlier post, one of the industries instrumental to the growth in the professional services sector is research and development. The number of people employed in this sector has grown from 330,000 to almost 480,000. Even more impressive is the fact that it peaked at almost 600,000 in 2006:

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