Andrew B. Collier / @datawookie

In the previous installment we derived two categorical variables. This time we will extract descriptive statistics.

In the previous installment we sucked some data from the National Health and Nutrition Examination Survey into R and did some preliminary work. Now we are going to play with some categorical data.

I have just started preparing a series of talks aimed at introducing the use of R to a rather broad audience consisting of physicists, chemists, statisticians, biologists and computer scientists (plus a few other disciplines thrown in for good measure). I want to use a single consistent set of data throughout the talks. Finding something that would resonate with such a disparate set of people was quite a challenge. After playing around with a couple of options, I settled on using data for age, height and mass. These are things that we can all identify with. The next challenge was to actually find a suitable data set, which was surprisingly difficult. Eventually I stumbled upon the data from the National Health and Nutrition Examination Survey (NHANES), The data from the survey are available here. These data have been divided into a number of sets, each of which has been excellently curated and has a detailed codebook.

I was recently browsing through the variety of MetaTrader indicators for support and resistance levels. None of them ticked all of my boxes. Either they were not aesthetically pleasing (making a mess of my pristine charts) or they failed to produce what I consider to be reasonable levels. Embracing my pioneering spirit, I set out to fashion my own indicator, one which will ultimately tick all of my boxes.

Sample output from v1.2 of my support-resistance indicator is shown below for the weekly chart of GBPUSD.

A year or so ago I went to a talk which included a diagram showing the locations of Earth’s fleet of geosynchronous satellites. According to the speaker, the information in this diagram was already quite dated: the satellites and their locations had changed.