I remembered a another Anecdote.

Most of you may be familiar with grading on a curve that leads to grade inflation. How many of you have been in classes where the professor Lowers grades on a curve??!!

I have been in such classes particularly in the engineering field. In otherwords, let us say there is an exam and the average score is a 91%. The professor then makes 91% a C and redetermines the rest of the grades to fit into a stanard bell curve distribution.

So you look on your test and see “89.5%” and think “Well, good, I’m doing quite OK!”.

But then you see the board and is says something like this:

100-96 = A
96-94 = B
94-91 = C
91-80 = D
79-0 = E

I hated being in those classes especailly discovering that half the class is using the exams from the past five years to prepare for the exam because the professor never makes new problems [do each problem enough times and you can do it from memory; program each problem into your calculator as text and you can take it straight off the calculator!] and because everybody [THE AVERAGE] does so well on the exams, the professor thinks his lectures are really really hot stuff and thinks even that the students are really understanding the material.

And becasue this professor is adament abotu fighitng “grade inflation,” he is purposely holding the class to a standard preset idea that every class taught right fits a predefined bellcurve average.

Meanwhile, none of these conclusions really addresses the case.

It’s really quite frustrating!!!

Technolib, if they grade on a curve, the average is still ~70% but they are given handicap points; so when you grade on a curve, a whole lot more people think they’re smarter when in truth they’re still just as Dumb as the Average Brick or worse.

Now if we have a populaiton of 250 million, then 125 million are between average and below average intelligence. Unemployment is high, but it is not 125 million, and given the number of people who have said Library school was hard and earnestly meant it, I would suggest these people are indeed gainfully employed everywhere but most particularly in Libraries. How else do we explain such low salaries and a reverancy for the job that suggests we would even PAY to work in this field since it is so good to us?

This discussion has been too much fun…

The reason the definition works is because we are dealing with the population of the US, which is about 300 million. The outliers on the low end are balanced out by the outliers on the high end. Hence we are dealing with a standard distribution about a bell curve.

Now if you spend some time with this you will find that the Median for such a dataset very near equals the Mean – your middle value very near approximates the Average. But Our statement calls for the Average [By definition, half of the US population is below AVERAGE intelligence], so MEAN is the correct term.