Tutoring math, you get asked about statistics.  The tutor offers an interpretation of mean and standard deviation.

Back when I was in university, there was a 2nd-year statistics course. It was the introductory stats course and was required for many degrees. Of course, being in math, I had to take it. However, I recall that business students, as well as social science students, commonly took it as well. I rarely had those people in my classes; that stats course was the exception.

I was told that the class had a 50 percent failure/dropout rate – the highest of all the courses at the university. It was even higher than calculus, which had a 40 percent non-completion rate. However, the stats course did have the enrollment of many students who weren’t math-oriented.

A common sentiment expressed by statistics students is that it’s hard to apply the ideas to everyday life. In a way, the feeling is ironic, since the first couple of courses in statistics – much more than most math courses – focus on everyday applications.

Introductory statistics focuses closely on the mean and the standard deviation of a population. The mean is another name for the average; most people understand it as the “expected” value. Consider mean height, for instance. If you imagine a person you can’t see, but want to guess their height, your best guess is the mean height of the population.

Standard deviation is harder to understand for most people. It’s the measure of how far apart the population’s values are – how spread out they are. Thinking of heights again: in a population with low standard deviation, people’s heights would mainly be close to the same. In a population with high standard deviation, the heights would likely be quite different from person to person.

I’ll be discussing more technical aspects of mean and standard deviation in coming posts. This, I hope, might be a good first step:)

Jack of Oracle Tutoring by Jack and Diane, Campbell River, BC.