Bob Hayden wrote:
> Tom Moore's original request for data well fit by a cubic tacitly
> implied that it's actually pretty unusual for a cubic (or higher order
> polynomial) to be a good choice. Perhaps Tom even doubted that it
> would EVER be a good choice, and wondered if anyone could provide a
> counterexample!-)
The Alpo dogfood dataset is a possible candidate.
Source: Primary: Alpo dog food bag Secondary: a saved email I found while
scrounging around my hard drive.
**
The recommended serving size for dog food depends on the weight of the dog.
Alpo Data Set
Weight of Dog and amount of food it needs
Weight Amount of Alpo
(lbs) (Cups)
8 1
19 2
36 3
56 4
78 5
103 6
130 7
158 8
190 9
This is more cubic-like if you make Amount of Alpo the explanatory variable
and weight the response variable, rather than the (intended) other way
round.
Probably a better dataset is the Alligator dataset that was in an early
draft document about the AP Stats syllabus.
**
Many wildlife populations are monitored by taking aerial photographs.
Information about the number of animals and their whereabouts is important
to protecting certain species and to ensuring the safety of surrounding
human populations.
In addition, it is sometimes possible to monitor certain characteristics of
the animals. The length of an alligator can be estimated quite accurately
from aerial photographs or from a boat. However, the alligator's weight is
much more difficult to determine. In the example below, data on the length
(in inches) and weight (in pounds) of alligators captured in central
Florida are used to develop a model from which the weight of an alligator
can be predicted from its length.
Length Weight Len^3 Ln(Length) Ln(Weight)
58 28 195112 4.060443 3.33220451
61 44 226981 4.1108739 3.78418963
63 33 250047 4.1431347 3.49650756
68 39 314432 4.2195077 3.66356165
69 36 328509 4.2341065 3.58351894
72 38 373248 4.2766661 3.63758616
72 61 373248 4.2766661 4.11087386
74 54 405224 4.3040651 3.98898405
74 51 405224 4.3040651 3.93182563
76 42 438976 4.3307333 3.73766962
78 57 474552 4.3567088 4.04305127
82 80 551368 4.4067192 4.38202664
85 84 614125 4.4426513 4.4308168
86 83 636056 4.4543473 4.41884061
86 80 636056 4.4543473 4.38202664
86 90 636056 4.4543473 4.49980967
88 70 681472 4.4773368 4.24849524
89 84 704969 4.4886364 4.4308168
90 106 729000 4.4998097 4.66343909
90 102 729000 4.4998097 4.62497281
94 110 830584 4.5432948 4.70048037
94 130 830584 4.5432948 4.86753445
114 197 1481544 4.7361984 5.28320373
128 366 2097152 4.8520303 5.90263333
147 640 3176523 4.9904326 6.46146818
Cheers
Rex
--
Rex Boggs Phone: 0749 230 338
Glenmore SHS Fax: 0749 230 350
P.O. Box 5822, R.M.C. Email: [EMAIL PROTECTED]
Rockhampton QLD 4702
Australia
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http://smard.cqu.edu.au
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http://exploringdata.cqu.edu.au
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