Universities should strive for gender balance between male and female students in every subject

universities should accept numbers of male and female students in every subject
to what extent do you agree or disagree

Wow, I don't think you even managed to copy the prompt correctly. Presumably it should be "universities should strive for perfect gender balance between male and female students in every subject. To what extent do you agree or disagree." That is an excellent prompt to write an essay on. Good luck coming up with a draft. Once you have one, feel free to post it here for more feedback.

If you need help getting started, try thinking of the causes of gender imbalance in some subjects, as well as some of the problems that could arise if every class had to have a 50/50 split between the sexes.

After brainstorming, make up an outline. If you'd like feedback on your outline before writing your first draft, feel free to post that here too.

Do you mean equal numbers of males and females?

If so, I would say no. My basic argument would be that individuals should be allowed to choose their own courses and majors. If it turns out this freedom leads to unequal numbers of men and women in certain courses, so be it. We should not force individuals to change courses and majors just because there's an unequal sex ratio. We also shouldn't expect males and females to have the same preferences for courses, so it's probably optimal that there's unequal sex ratios. For example, if more women than men find sociology a fascinating and personally relevant discipline, we should expect that over half the Soc 101 class (and Soc major) will be female.

That would be the easiest case to argue, certainly. One might reference Simpson's Paradox as it applied to the 1973 Berkeley law suit when taking that approach. If you go with this argument, though, don't forget to brainstorm possible counter-arguments and to respond to them in your essay to make it as strong as possible.

Are you implying that the number of males vs. females in a class is not a result of them being interested in different subjects?

No. I was actually agreeing with you. However, the author of the essay should think of possible counter-arguments when writing the essay, because authors of argumentative essays should always consider the opposing point of view. In this case, one might look at why males and females are interested in different subjects, whether this is the result of social forces that perpetuate inequality, and whether these social forces should be fought against.

Oh, I guess I don't understand Simpson's Paradox. Just out of curiosity, can you briefly explain what you meant.

You can look it up in Wikipedia for a full explanation, including the Berkeley example I mentioned. Essentially, in 1973, the University of Berkeley was sued for discriminating against women, because it admitted a higher percentage of male than female applicants. The university defended itself by pointing out that, on a department by department basis, the trend was a bias against male applicants in favor of female applicants. However, due to the unequal number of applicants to the various departments, and the difference in the number of students overall each department had room to accept, this trend was reversed in the aggregate.

And that's Simpson's Paradox -- the idea that the direction of an aggregate trend can be the opposite to the trends that make it up. So, for instance, Baseball Player A could have a higher batting average that Baseball Player B for 1998 and for 1999, yet Baseball Player B could have the better average over both years. A real life example, again paraphrased from Wikipedia, involves Derek Jeter and David Justice. In 1995, Jeter had a batting average of 0.250, and Justice one of 0.253. In 1996, Jeter had a batting average of .314, while Justice had an average of .321. Justice was therefore, on a year-by-year average, the better batter. But, if you compare their average for both years combined, Jeter's average is .310, while Justice's average is only .270. So, over the entire two year period, Jeter has the higher average.

Thanks Sean, that's fascinating.

Apparently its something students learn in first year statistics. Of course, not many people take first year statistics, which is unfortunate. The public is woefully innumerate. In fact, the public tends to lack a background in the basic sciences. I forget how many people agreed that dihydrogen monoxide should be banned, after a petition circulated warning that scientists had found that it was present in large quantities in most of our lakes and rivers. Enough to show that public opinion on environmental matters should often be ignored, at any rate.

Too true. And a challenge for essay writers, in two ways: (1) We must ensure that we use statistics accurately and non-deceptively, which it can be difficult to do if we don't understand them ourselves; and (2) we must explain the numbers that we do use, keeping the likely numeracy (or lack thereof) of our target audience in mind.

Quite right. Though, to be fair, I don't think that most essay writers set out to use statistics inaccurately or deceptively -- they just don't really think through the research that they do that supports their position. If an essay writer is very strongly pro-gun control, for instance, and she reads an article that states that, in State X, violent crime has declined by 5% since gun control measures were implemented, she is likely to incorporate that number into her work without really questioning it, because it makes intuitive sense to her.

I wish that schools worldwide would make the collective works of John Allen Paulos required reading. That's where I first encountered Simpson's Paradox. The books are wonderfully written, and show just why statistics are so often grouped with lies and damn lies.

I think it's also that most writers don't really understand empirical research. For example, showing that violent crime declined by 5% since gun control measures were taken doesn't really show much of anything. A statistician would not find that fact convincing in and of itself, as one needs to use regression analyses or other measures to control for the relevant variables. In my experience, most writers don't quite understand these things, so these use simple statistics and facts to support their view point.

And an awful lot of people mix up correlation and causation, too. Gun control measures in many states might coincide with a decline in violent crime, for instance, but this wouldn't mean much if the crime rates in those states had been declining for years before the measures were enacted as well.

Even highly educated people mix up the basics such as the difference between mean, mode, and median. I recently spent I-don't-know-how-long convincing a tenured full professor in English not to claim that half of all cases necessarily fall below the average. Even after I gave examples and explained outliers, the sentence interpreting "average" as if it meant "median" was still in her text. I finally had to just say, "You cannot say that. It just isn't true."

The confusion probably arises owing to the fact that, in normal distributions, half of all cases that are not actually at the average do fall below the average, just as half fall above it. An awful lot of phenomena have normal distributions, or close enough to it that textbooks even it out to get a nice bell curve. Probably, the high instance of this is the reason that such distributions are termed "normal." So, for instance, one is not speaking foolishly when one says that half the population (excluding those who are exactly average) have a below average IQ. IQ tests are actually designed to to ensure that result -- i.e., they are set up to yield a normal distribution of scores. So, if one is talking about variables that manifest a normal distribution, then half of all cases do necessarily fall below the mean.

So, if the person you were talking to was referring to such a variable, she was in fact using the term correctly. I assume she was, even if she didn't articulate it, as it is very easy to come up with examples of non-normal distributions that prove your point (4, 98, 99, 99, for instance, have an average of 75, in which three of the cases are above the average and only one below it). I hope this helps you next time the two of you discuss the issue.