[ACFUG Discuss] sorting question

[Tepfer, Seth]

I have a challenge laid out before me. I need to divide the incoming Oxford 
student class into 25 groups of about 16 or 17 students each. However, they 
want the groups to be as balanced as possible, across number, sex, race, and 
geographic origin. Now, I can easily see how to balance based on sex or any 
single characteristic. But how to balance across all three at the same time? My 
head starts spinning when I think about the issues that we won't necessarily 
have equal distribution across any of the characteristics.

I don't need the code, just the concept. I am having a hard time conceiving on 
how to do this if the people were standing in front of me, much less by code. 
Any ideas?


Seth Tepfer 770-784-8487 [EMAIL PROTECTED]
Director of Administrative Computing, Oxford College
Proud Pappa (again): Zyle Caspian, born Thursday, April 17, 2:38 pm. 8 lbs, 
19.5 inches. Baby Pix at: http://www.flickr.com/photos/[EMAIL PROTECTED]/

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Re: [ACFUG Discuss] sorting question

[Dean H. Saxe]

Damn good question.  Here's what I would do...

For each classification, find out how many groups there are and how  
many belong to each group.  For gender, you have 2 groups and they are  
probably split 50/50.  So every addition to each bucket of students  
would be male, then female, etc.  This is, clearly, pretty obvious.   
Geo origin and race would have more buckets with less people per bucket.


I would start assigning students like this:

Bucket 1:  Male, foreign origin (if any), any race
Bucket 2:  Male, foreign origin (if any), any race
... ad nauseum through the first round.  Second round choose women of  
foreign origin of any race.  If you run out of men or women before  
running out of foreign origins, just keep assigning regardless of  
gender.


When you run out of foreign origins, move to race and do the same  
thing through all of the various races you describe.


Finally, you are left with American students, male and female of  
whatever major racial category you have left.  Start assigning them.   
You may further divide them by origin in the US (West Coast, Mountain  
states, midwest, east coast, etc).


This should roughly balance out the groups, but you may choose to do  
some manual tweaking from there.


Hope this helps!

-dhs




Dean H. Saxe, CISSP, CEH
[EMAIL PROTECTED]
"[U]nconstitutional behavior by the authorities is constrained only by  
the peoples' willingness to contest them"

--John Perry Barlow


On Jul 25, 2008, at 5:25 PM, Tepfer, Seth wrote:

I have a challenge laid out before me. I need to divide the incoming  
Oxford student class into 25 groups of about 16 or 17 students each.  
However, they want the groups to be as balanced as possible, across  
number, sex, race, and geographic origin. Now, I can easily see how  
to balance based on sex or any single characteristic. But how to  
balance across all three at the same time? My head starts spinning  
when I think about the issues that we won't necessarily have equal  
distribution across any of the characteristics.


I don't need the code, just the concept. I am having a hard time  
conceiving on how to do this if the people were standing in front of  
me, much less by code. Any ideas?



Seth Tepfer 770-784-8487 [EMAIL PROTECTED]
Director of Administrative Computing, Oxford College
Proud Pappa (again): Zyle Caspian, born Thursday, April 17, 2:38 pm.  
8 lbs, 19.5 inches. Baby Pix at: http://www.flickr.com/photos/[EMAIL PROTECTED]/


This e-mail message (including any attachments) is for the sole use of
the intended recipient(s) and may contain confidential and privileged
information.  If the reader of this message is not the intended
recipient, you are hereby notified that any dissemination,  
distribution

or copying of this message (including any attachments) is strictly
prohibited.

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Re: [ACFUG Discuss] sorting question

[Cameron Childress]

Dean's method is one possibility.  This is actually a very interesting
question and I'm nojt sure how I'd solve it.  I thought about it a bit
during my drive home, and here's the approach I would take...  This is
alot easier if there are only two choices for each statistic
(male|female - american|foreign - white|nonwhite), but it could also
work with multiple choices for each.

First, how to measure the success of the program?  Measure the
percentage of each stat in the group as a whole (I'll call this Big
Ratio), and then measure the percentages in each of the 25 groups
(I'll call this Group Ratio) and see how closely they each match.

Okay, next, how to divide them up into groups?  I'd start by seeding
each group with a random individual.  Then I would take each person
from the pool of potential students and loop over each group, testing
to see if adding that person to that group would make the Group Ratio
for that group closer or farther away from the Big Ratio.  Whichever
Group Ratio moves the farthest toward the Big Ratio would be the group
you add that individual to.  Once a group reaches 17 people, close it
and stop adding people to it.

You'll have to find a way of combining the ratios and determining one
big number that represents the combination.  I am sure if I paid more
attention in my statistics class I'd know it had something to do with
standard deviations, but I didn't pay any attention - so that's up to
you to figure out.

Once you are done, look at all the Group Ratios and see how close
their balance measures up to the Big Ratio.

Two suggestions to make this easier on yourself:
1) Start by attempting to balance a smaller number of groups than 25.
2 or 3 maybe.
2) Start with binary choices, then move on to multiple choices after
you have  amethod that is capible of balancing two choices.

Least that's where I would start.  If you are willing, post your
solution (in english or in code) once you're done.  I would be
interested in seeing how you did it.

-Cameron

On Fri, Jul 25, 2008 at 5:25 PM, Tepfer, Seth <[EMAIL PROTECTED]> wrote:
> I have a challenge laid out before me. I need to divide the incoming Oxford 
> student class into 25 groups of about 16 or 17 students each. However, they 
> want the groups to be as balanced as possible, across number, sex, race, and 
> geographic origin. Now, I can easily see how to balance based on sex or any 
> single characteristic. But how to balance across all three at the same time? 
> My head starts spinning when I think about the issues that we won't 
> necessarily have equal distribution across any of the characteristics.
>
> I don't need the code, just the concept. I am having a hard time conceiving 
> on how to do this if the people were standing in front of me, much less by 
> code. Any ideas?


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Re: [ACFUG Discuss] sorting question

[Darin Kohles]

Or, you normalize with eigenvectors. Just determine the McClaurean
equivalent, factor the Jacobian and viola!

Actually, in a take on Dean's suggestion you could try a weighting
function. Simply assign a numeric value for each classification,
"bucketize" the results by sum of the numeric values for all variables
(you might need to groups ranges), then randomly select from the
resulting buckets to fill your groups.

I'd then take Cameron's suggestion and do a comparison with the break
down of the distribution in the resulting groups and possibly tweak.

On Fri, Jul 25, 2008 at 6:44 PM, Cameron Childress <[EMAIL PROTECTED]> wrote:
> Dean's method is one possibility.  This is actually a very interesting
> question and I'm nojt sure how I'd solve it.  I thought about it a bit
> during my drive home, and here's the approach I would take...  This is
> alot easier if there are only two choices for each statistic
> (male|female - american|foreign - white|nonwhite), but it could also
> work with multiple choices for each.
>
> First, how to measure the success of the program?  Measure the
> percentage of each stat in the group as a whole (I'll call this Big
> Ratio), and then measure the percentages in each of the 25 groups
> (I'll call this Group Ratio) and see how closely they each match.
>
> Okay, next, how to divide them up into groups?  I'd start by seeding
> each group with a random individual.  Then I would take each person
> from the pool of potential students and loop over each group, testing
> to see if adding that person to that group would make the Group Ratio
> for that group closer or farther away from the Big Ratio.  Whichever
> Group Ratio moves the farthest toward the Big Ratio would be the group
> you add that individual to.  Once a group reaches 17 people, close it
> and stop adding people to it.
>
> You'll have to find a way of combining the ratios and determining one
> big number that represents the combination.  I am sure if I paid more
> attention in my statistics class I'd know it had something to do with
> standard deviations, but I didn't pay any attention - so that's up to
> you to figure out.
>
> Once you are done, look at all the Group Ratios and see how close
> their balance measures up to the Big Ratio.
>
> Two suggestions to make this easier on yourself:
> 1) Start by attempting to balance a smaller number of groups than 25.
> 2 or 3 maybe.
> 2) Start with binary choices, then move on to multiple choices after
> you have  amethod that is capible of balancing two choices.
>
> Least that's where I would start.  If you are willing, post your
> solution (in english or in code) once you're done.  I would be
> interested in seeing how you did it.
>
> -Cameron
>
> On Fri, Jul 25, 2008 at 5:25 PM, Tepfer, Seth <[EMAIL PROTECTED]> wrote:
>> I have a challenge laid out before me. I need to divide the incoming Oxford 
>> student class into 25 groups of about 16 or 17 students each. However, they 
>> want the groups to be as balanced as possible, across number, sex, race, and 
>> geographic origin. Now, I can easily see how to balance based on sex or any 
>> single characteristic. But how to balance across all three at the same time? 
>> My head starts spinning when I think about the issues that we won't 
>> necessarily have equal distribution across any of the characteristics.
>>
>> I don't need the code, just the concept. I am having a hard time conceiving 
>> on how to do this if the people were standing in front of me, much less by 
>> code. Any ideas?
>
>
> -
> To unsubscribe from this list, manage your profile @
> http://www.acfug.org?fa=login.edituserform
>
> For more info, see http://www.acfug.org/mailinglists
> Archive @ http://www.mail-archive.com/discussion%40acfug.org/
> List hosted by http://www.fusionlink.com
> -
>
>
>
>



-- 
Darin Kohles
RIA Developer


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RE: [ACFUG Discuss] sorting question

[Charlie Stell]

Interesting task!

Unless there's some whitepaper out there explaining the "real" right answer,
Cameron's mention of how to test the effectiveness is great.

One way that occurred to me is have a meta table with a column for
attribute-name and a column with the value of importance (would be
sequential, with 1 being least important) - Ill call it tA for this email...

Step 1
ColumnList = [all columns from Ta]
Select #ColumnList#, count()  from student group by #ColumnList#

Take the returning row with the smallest count
memberPool = any member that match all the columns in #ColumnList# into each
group

insert (memberPool/number of groups) members into each group-member

Step 2 - loop over this
ColumnList = [all columns from Ta] with importance > loopcount
Select #ColumnList#, count()  from student join group-member group by
#ColumnList# - 
Take the returning row with the smallest count
memberPool = any member that match all the columns in #ColumnList# and not
in group-member into each group
break loop when all members are assigned

The importance might already be determined arbitrarily (which by that I mean
for some non-data/math reason).
If it weren't, maybe do this:
For each column in ColumnList = [all columns from Ta]
Select '#column#',#column#,count from member group by #column# 
after looping, the column with the highest count
UNION ALL (repeat loop)
Out Of this set, whichever column/value pair has the largest count, use that
for your most important, for your second most important, use the pair with
the next-largest count and not matching the column you just said was most
important... and so forth.

Not sure how any of that would pan out... but my two cents!




-Original Message-
From: [EMAIL PROTECTED] [mailto:[EMAIL PROTECTED] On Behalf Of Cameron
Childress
Sent: Friday, July 25, 2008 18:44
To: discussion@acfug.org
Subject: Re: [ACFUG Discuss] sorting question

Dean's method is one possibility.  This is actually a very interesting
question and I'm nojt sure how I'd solve it.  I thought about it a bit
during my drive home, and here's the approach I would take...  This is
alot easier if there are only two choices for each statistic
(male|female - american|foreign - white|nonwhite), but it could also
work with multiple choices for each.

First, how to measure the success of the program?  Measure the
percentage of each stat in the group as a whole (I'll call this Big
Ratio), and then measure the percentages in each of the 25 groups
(I'll call this Group Ratio) and see how closely they each match.

Okay, next, how to divide them up into groups?  I'd start by seeding
each group with a random individual.  Then I would take each person
from the pool of potential students and loop over each group, testing
to see if adding that person to that group would make the Group Ratio
for that group closer or farther away from the Big Ratio.  Whichever
Group Ratio moves the farthest toward the Big Ratio would be the group
you add that individual to.  Once a group reaches 17 people, close it
and stop adding people to it.

You'll have to find a way of combining the ratios and determining one
big number that represents the combination.  I am sure if I paid more
attention in my statistics class I'd know it had something to do with
standard deviations, but I didn't pay any attention - so that's up to
you to figure out.

Once you are done, look at all the Group Ratios and see how close
their balance measures up to the Big Ratio.

Two suggestions to make this easier on yourself:
1) Start by attempting to balance a smaller number of groups than 25.
2 or 3 maybe.
2) Start with binary choices, then move on to multiple choices after
you have  amethod that is capible of balancing two choices.

Least that's where I would start.  If you are willing, post your
solution (in english or in code) once you're done.  I would be
interested in seeing how you did it.

-Cameron

On Fri, Jul 25, 2008 at 5:25 PM, Tepfer, Seth <[EMAIL PROTECTED]> wrote:
> I have a challenge laid out before me. I need to divide the incoming
Oxford student class into 25 groups of about 16 or 17 students each.
However, they want the groups to be as balanced as possible, across number,
sex, race, and geographic origin. Now, I can easily see how to balance based
on sex or any single characteristic. But how to balance across all three at
the same time? My head starts spinning when I think about the issues that we
won't necessarily have equal distribution across any of the characteristics.
>
> I don't need the code, just the concept. I am having a hard time
conceiving on how to do this if the people were standing in front of me,
much less by code. Any ideas?


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Re: [ACFUG Discuss] sorting question

[Douglas Knudsen]

ha.  yeah, I'd prolly just randomize the table as is for S+Gs to see if just
randomly distributes even enough for the suits.  Or, seeing as how you are
on a edu there, I suggest taking a jaunt over to the Prob and stats dept, or
Math dept if no separate prob+stats, and have some grad student play with
it.

You could play with Excel evenmaybe todays GOTD would help
http://www.giveawayoftheday.com/statfi/

DK

On Fri, Jul 25, 2008 at 7:32 PM, Darin Kohles <[EMAIL PROTECTED]> wrote:

> Or, you normalize with eigenvectors. Just determine the McClaurean
> equivalent, factor the Jacobian and viola!
>
> Actually, in a take on Dean's suggestion you could try a weighting
> function. Simply assign a numeric value for each classification,
> "bucketize" the results by sum of the numeric values for all variables
> (you might need to groups ranges), then randomly select from the
> resulting buckets to fill your groups.
>
> I'd then take Cameron's suggestion and do a comparison with the break
> down of the distribution in the resulting groups and possibly tweak.
>
> On Fri, Jul 25, 2008 at 6:44 PM, Cameron Childress <[EMAIL PROTECTED]>
> wrote:
> > Dean's method is one possibility.  This is actually a very interesting
> > question and I'm nojt sure how I'd solve it.  I thought about it a bit
> > during my drive home, and here's the approach I would take...  This is
> > alot easier if there are only two choices for each statistic
> > (male|female - american|foreign - white|nonwhite), but it could also
> > work with multiple choices for each.
> >
> > First, how to measure the success of the program?  Measure the
> > percentage of each stat in the group as a whole (I'll call this Big
> > Ratio), and then measure the percentages in each of the 25 groups
> > (I'll call this Group Ratio) and see how closely they each match.
> >
> > Okay, next, how to divide them up into groups?  I'd start by seeding
> > each group with a random individual.  Then I would take each person
> > from the pool of potential students and loop over each group, testing
> > to see if adding that person to that group would make the Group Ratio
> > for that group closer or farther away from the Big Ratio.  Whichever
> > Group Ratio moves the farthest toward the Big Ratio would be the group
> > you add that individual to.  Once a group reaches 17 people, close it
> > and stop adding people to it.
> >
> > You'll have to find a way of combining the ratios and determining one
> > big number that represents the combination.  I am sure if I paid more
> > attention in my statistics class I'd know it had something to do with
> > standard deviations, but I didn't pay any attention - so that's up to
> > you to figure out.
> >
> > Once you are done, look at all the Group Ratios and see how close
> > their balance measures up to the Big Ratio.
> >
> > Two suggestions to make this easier on yourself:
> > 1) Start by attempting to balance a smaller number of groups than 25.
> > 2 or 3 maybe.
> > 2) Start with binary choices, then move on to multiple choices after
> > you have  amethod that is capible of balancing two choices.
> >
> > Least that's where I would start.  If you are willing, post your
> > solution (in english or in code) once you're done.  I would be
> > interested in seeing how you did it.
> >
> > -Cameron
> >
> > On Fri, Jul 25, 2008 at 5:25 PM, Tepfer, Seth <[EMAIL PROTECTED]> wrote:
> >> I have a challenge laid out before me. I need to divide the incoming
> Oxford student class into 25 groups of about 16 or 17 students each.
> However, they want the groups to be as balanced as possible, across number,
> sex, race, and geographic origin. Now, I can easily see how to balance based
> on sex or any single characteristic. But how to balance across all three at
> the same time? My head starts spinning when I think about the issues that we
> won't necessarily have equal distribution across any of the characteristics.
> >>
> >> I don't need the code, just the concept. I am having a hard time
> conceiving on how to do this if the people were standing in front of me,
> much less by code. Any ideas?
> >
> >
> > -
> > To unsubscribe from this list, manage your profile @
> > http://www.acfug.org?fa=login.edituserform
> >
> > For more info, see http://www.acfug.org/mailinglists
> > Archive @ http://www.mail-archive.com/discussion%40acfug.org/
> > List hosted by http://www.fusionlink.com
> > -
> >
> >
> >
> >
>
>
>
> --
> Darin Kohles
> RIA Developer
>
>
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Re: [ACFUG Discuss] sorting question

[Jeremy Allen]

The nice thing is you can test the distribution when you are done to
determine, statistically, if everything is distributed evenly. So a test in
this case is really important. I would develop your testing algorithm (as
suggested earlier first) and then work on the actual distribution
algorithm.  Now then. Once we have a test here is what you do. This is a
sure fire method and is at least one correct solution.

Assumption 1: You have, basically, an infinite amount of time per
distribution.
Assumption 2: You can find an infinite supply of monkeys and keyboards.

Set the infinite monkeys jumping on keyboards and sample the output they
generate until it fits a perfect distribution per group.

Voila.

Thanks,

Jeremy

On Fri, Jul 25, 2008 at 5:25 PM, Tepfer, Seth <[EMAIL PROTECTED]> wrote:

> I have a challenge laid out before me. I need to divide the incoming Oxford
> student class into 25 groups of about 16 or 17 students each. However, they
> want the groups to be as balanced as possible, across number, sex, race, and
> geographic origin. Now, I can easily see how to balance based on sex or any
> single characteristic. But how to balance across all three at the same time?
> My head starts spinning when I think about the issues that we won't
> necessarily have equal distribution across any of the characteristics.
>
> I don't need the code, just the concept. I am having a hard time conceiving
> on how to do this if the people were standing in front of me, much less by
> code. Any ideas?
>
>
> Seth Tepfer 770-784-8487 [EMAIL PROTECTED]
> Director of Administrative Computing, Oxford College
> Proud Pappa (again): Zyle Caspian, born Thursday, April 17, 2:38 pm. 8 lbs,
> 19.5 inches. Baby Pix at: http://www.flickr.com/photos/[EMAIL PROTECTED]/
>
> This e-mail message (including any attachments) is for the sole use of
> the intended recipient(s) and may contain confidential and privileged
> information.  If the reader of this message is not the intended
> recipient, you are hereby notified that any dissemination, distribution
> or copying of this message (including any attachments) is strictly
> prohibited.
>
> If you have received this message in error, please contact
> the sender by reply e-mail message and destroy all copies of the
> original message (including attachments).
>
>
> -
> To unsubscribe from this list, manage your profile @
> http://www.acfug.org?falogin.edituserform
>
> For more info, see http://www.acfug.org/mailinglists
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> List hosted by http://www.fusionlink.com
> -
>
>
>
>



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re[2]: [ACFUG Discuss] sorting question

[Mischa Uppelschoten ext 10]

As a variation on Charlie's suggestion, I'd like to propose assigning points to 
individual students for having a certain value for a characteristic:

points = total population / group size

Assume 400 students: 200 Europeans, 100 Asians, 50 Africans, 50 Oceanians.

Europeans: 400/200: 2 points each.
Asians: 400/100: 4 points
etc.

Repeat this for every characteristic. In the end, every student will have 
accumulated points for uniqueness. You want to assign the high point students 
to their own group first because they are very valueable from a uniqueness 
standpoint.

So distribute the top 25 unique students over 25 groups first, then randomly 
distribute the next 25 students over the groups etc.

I realize that you are giving more total points to characteristics with more 
possible values but I think that still achieves the goal of making each group 
as diverse as possible. The benefit is that the above method is fairly easy to 
program and with two tables and a bit of sql and some CF loops the overall goal 
can be achieved.

I'm curious about how you end up doing it!
Good luck!
Mischa.



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re[4]: [ACFUG Discuss] sorting question

[Mischa Uppelschoten ext 10]

Hey, why take the easy
 way when it's possible to overengineer it!
 
: #1 Get a pencil /
 paper : #2 divide them up: ;
 ): how i would do it.



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Re: re[2]: [ACFUG Discuss] sorting question

[Steven Ross]

#1 Get a pencil / paper
#2 divide them up

; )

how i would do it.



On Mon, Jul 28, 2008 at 10:45 AM, Mischa Uppelschoten ext 10 <
[EMAIL PROTECTED]> wrote:

> As a variation on Charlie's suggestion, I'd like to propose assigning
> points to individual students for having a certain value for a
> characteristic:
>
> points = total population / group size
>
> Assume 400 students: 200 Europeans, 100 Asians, 50 Africans, 50 Oceanians.
>
> Europeans: 400/200: 2 points each.
> Asians: 400/100: 4 points
> etc.
>
> Repeat this for every characteristic. In the end, every student will have
> accumulated points for uniqueness. You want to assign the high point
> students to their own group first because they are very valueable from a
> uniqueness standpoint.
>
> So distribute the top 25 unique students over 25 groups first, then
> randomly distribute the next 25 students over the groups etc.
>
> I realize that you are giving more total points to characteristics with
> more possible values but I think that still achieves the goal of making each
> group as diverse as possible. The benefit is that the above method is fairly
> easy to program and with two tables and a bit of sql and some CF loops the
> overall goal can be achieved.
>
> I'm curious about how you end up doing it!
> Good luck!
> Mischa.
>
>
>
> -
> To unsubscribe from this list, manage your profile @
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Steve Ross
web application & interface developer
http://blog.stevensross.com
[mobile] 404-488-4364 [fax] (404) 592-6885
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