From: maufd@csv.warwick.ac.uk (Mr J S Graley)
Newsgroups: soc.women,alt.feminism,soc.men
Subject: Re: Entry level salaries (was: Re: Elle MacPherson causes rape?)
Date: 9 Nov 92 18:11:32 GMT
Organization: Computing Services, University of Warwick, UK
NNTP-Posting-Host: oregano.csv.warwick.ac.uk

In article <MUFFY.92Nov9082355@remarque.berkeley.edu> muffy@remarque.berkeley.edu (Muffy Barkocy) writes:
>In article <9NOV199210165558@mary.fordham.edu> nissim@mary.fordham.edu (Leonard J. Nissim) writes:
>>In article <1992Nov7.213707.15211@fid.morgan.com>, 
>>sethb@fid.morgan.com (Seth Breidbart) writes...
>>[stuff about MacPherson calendars deleted]
>>> 
>>>More recently, I've seen statistics that when men and women have the
>>>same level of education and experience, they earn about the same.  The
>>>only reference I have is that in the most recent salary survey taken
>>>by the MAA that I've seen (probably a year or two old), women with new
>>>PhD's in math earned more, on average, than men with new PhD's in math.
>
>>Here are the *new* statistics (from the November 1992 issue of "Notices of 
>>the American Mathematical Society"):
>>9-month academic salaries of people with new Ph.D.'s in mathematics:
>>(`new' means granted during the 1991/92 academic year) 
>>Median salary for men----$34,000  (interquartile range--31,000 to 36,000)
>>Median salary for women--$34,900  (interquartile range--33,000 to 37,100)
>>Note that women earn over $1.02 for each $1 earned per man.  
>
>Well, if you're reading stuff from the American Mathematical Society, I
>would think you would know that the "median" is the number which falls
>in the middle of a sorted list of numbers.  This is not the same as the
>"mean" or average.  For example, suppose that the salaries in question
>are:
>
>women: 33,000 33,000 33,000 33,000 34,900 34,900 34,900 34,900 37,100
>men:   31,000 34,000 34,000 34,000 34,000 36,000 36,000 36,000 36,000
>
>In this example, the *medians* are as given above.  The *mean*, however,
>is:
>
>women: 34,300
>men: 34,555
>
>So, as the median is just one salary figure, all you can say is that
>that particular woman makes more than that particular man.  To come up
>with the "women make X for each $1 earned *per* man," you have to use
>the mean, which is the average salary *per* man or woman.  How about
>running back to those figures and posting the mean?  And the number of
>people in each group?
>
>Thanks...
>
>Muffy
>--
>

Just some thoughts on the subject of statistics:

If you assume that income has a normal distribution (ie the same curve as
height, IQ distributions etc) then the mean would equal the median.
In fact, though, income is not normally distributed. There is a large 
number of people with fairly low earnings, and a small number with extremlely
high earnings. If you treat the average income as the income you can
reasonably expect when you get a job, then the mean, which is affected
disproportionately by the very high earners, is probably not the best value
to use.

You see, a person's income is exponentially related to their potential
earning capability, if you define this capability as having a normal curve.
So if a person with capability 100 (arbitary units) earns $35,000 then a
person with capability 99 might earn $17,500 (half as much) and a person
with capability 101 might earn $70,000 (twice as much).
This explains the distribution of many low earners with a few very high; by 
exponentialising the normal curve we go from
   |     ___                         |  __
   |    /   \                        | /  \__
   |___/     \___         to         |_|     \__
   +--------------                   +-----------      in broad terms.
This is explainable too - employers have to place a value on positions in
order to compete for applicants, and to improve the offer a certain amount,
while $1000 might suffice as an addition to a $20,000 wage, more like $10,000
would have to be added to $200,000 to yield the same improvement in lifestyle.
Thus we _multiply_ rather than add, leading to the exponential potential ->
income relationship.

It follows that a mean wage is not the mean quality of life. In
particular, pertaining to the male/female comparison, we note that males
have a greater variability in their genetic makeup to women, which can be
seen clearly in the increased proportion of men in both very high flyer
jobs, and in the shite street-cleaner type jobs. 

However, the mean of the exponents of a wider distribution is higher. In 
other words, the bad jobs have a far smaller affect than the good ones, 
because of the unrepresentative diffeence between the linear distance from
the mean of a typical bad and typical good job. 

For instance:
Suppose three women earn $35,000. Mean = $35,000
Suppose three men earn $17,500, $35,000 and $70,000. Mean $40,833
BUT the percieved potential, and the quality of life, for the women is the
same as for the men.

The median is not a perfect measure either. 

Now the difference in practise will be small, but nonetheless potentially
able to outweigh the even smaller differences shown between male and female
averages above.

I hope this goes some way to demonstrating the dangers involved in 'bandying
about' with statistics as though they were subjective viewpoints.

--Morley