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Re: st: are there any statistics rules that I can apply to separate numbers into groups?


From   "Kyle K. Hood" <kyle.hood@yale.edu>
To   statalist@hsphsun2.harvard.edu
Subject   Re: st: are there any statistics rules that I can apply to separate numbers into groups?
Date   Wed, 11 Mar 2009 00:11:38 -0700

In mapping, univariate classification schemes are used to group features together. An example is Jenks' natural breaks, which simply defines k-1 cutoffs to minimize within-group sums of square deviations from group means. Unfortunately,

. findit jenks

produces nothing. However, there is information on the web regarding how to compute these cutoffs (just google it). I'm not sure how closely this method relates to cluster analysis and finite mixture models.

Kyle

Partha Deb wrote:
Although one can never be sure what's in someone else's mind, I suspect you are looking for cluster analysis. -help cluster- . Finite mixture models may also be of interest. -findit fmm- . See http://users.ox.ac.uk/~polf0050/ISS%20Lecture%208.pdf for a set of slides by Stephen Fisher that has an introduction to Cluster analysis and finite mixture models.

Best.

Partha


Ada Ma wrote:
Hi Statalisters,

I am looking for a solution to a problem but I have no idea where to start.

Let's say I have 50 packets of crisps of various weights and I would
like to separate these 50 packets of crisps into five groups based on
their weights in grams, as follows:

108.9702
111.1337
112.5217
112.6697
112.9962
114.0323
114.6699
116.8646
119.0719
124.5645
124.691
126.4943
126.5528
133.5675
134.9519
140.7979
144.228
102.8566
103.9373
104.7436
107.5397
109.4443
109.7089
110.395
112.1248
113.6032
115.6405
117.1919
120.0395
121.0714
121.7119
110.1116
112.0128
117.6563
118.2418
126.0027
127.8855
92.21352
92.45715
92.953
93.01508
94.05335
94.27259
94.38242
94.72507
94.83315
95.25914
95.37813
95.52933

I don't want to separate them into five equally sized groups.  I want
to separate the packets into groups so that the group members are most
similar to one another.  I am looking for a method (or methods?) to
achieve this end but I don't know where to start.  If you can think of
any suggestion please fire away and I'd be most grateful!

Regards,
Ada




--
Kyle Hood
Department of Economics
Yale University
New Haven, CT
website: http://www.econ.yale.edu/~kkh25

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