Baseball Salaries Dataset

From http://www.amstat.org/publications/jse/jse_data_archive.htm

NAME: Pay for Play: Are Baseball Salaries Based on Performance?
TYPE: Census
SIZE: 337 observations, 18 variables
The article associated with this dataset appears in the Journal of Statistics Education, Volume 6, Number 2 (July 1998). (http://www.amstat.org/publications/jse/v6n2/datasets.watnik.html)

SUBMITTED BY:
Mitchell R. Watnik
Department of Mathematics and Statistics
University of Missouri-Rolla
Rolla, MO 65409-0020

Further notes: http://www.amstat.org/publications/jse/datasets/baseball.txt

  Columns
       1 -  4  Salary (in thousands of dollars)
       6 - 10  Batting average
      12 - 16  On-base percentage (OBP)
      18 - 20  Number of runs
      22 - 24  Number of hits
      26 - 27  Number of doubles
      29 - 30  Number of triples
      32 - 33  Number of home runs
      35 - 37  Number of runs batted in (RBI)
      39 - 41  Number of walks
      43 - 45  Number of strike-outs
      47 - 48  Number of stolen bases
      50 - 51  Number of errors
           53  Indicator of "free agency eligibility"
           55  Indicator of "free agent in 1991/2"
           57  Indicator of "arbitration eligibility"
           59  Indicator of "arbitration in 1991/2"
      61 - 79  Player's name (in quotation marks)

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Pima Indian Diabetes Dataset

http://archive.ics.uci.edu/ml/datasets/Pima+Indians+Diabetes

Abstract: From National Institute of Diabetes and Digestive and Kidney Diseases; Includes cost data (donated by Peter Turney)


Original Owners: 

National Institute of Diabetes and Digestive and Kidney Diseases 

Donor of database: 

Vincent Sigillito (vgs '@' aplcen.apl.jhu.edu) 
Research Center, RMI Group Leader 
Applied Physics Laboratory 
The Johns Hopkins University 
Johns Hopkins Road 
Laurel, MD 20707 
(301) 953-6231


Data Set Information:

Several constraints were placed on the selection of these instances from a larger database. In particular, all patients here are females at least 21 years old of Pima Indian heritage. ADAP is an adaptive learning routine that generates and executes digital analogs of perceptron-like devices. It is a unique algorithm; see the paper for details.


Attribute Information:

1. Number of times pregnant 
2. Plasma glucose concentration a 2 hours in an oral glucose tolerance test 
3. Diastolic blood pressure (mm Hg) 
4. Triceps skin fold thickness (mm) 
5. 2-Hour serum insulin (mu U/ml) 
6. Body mass index (weight in kg/(height in m)^2) 
7. Diabetes pedigree function 
8. Age (years) 
9. Class variable (0 or 1) 

** UPDATE: Until 02/28/2011 this web page indicated that there were no missing values in the dataset. As pointed out by a repository user, this cannot be true: there are zeros in places where they are biologically impossible, such as the blood pressure attribute. It seems very likely that zero values encode missing data. However, since the dataset donors made no such statement we encourage you to use your best judgement and state your assumptions.


Relevant Papers:

Smith, J.W., Everhart, J.E., Dickson, W.C., Knowler, W.C., & Johannes, R.S. (1988). Using the ADAP learning algorithm to forecast the onset of diabetes mellitus. In Proceedings of the Symposium on Computer Applications and Medical Care} (pp. 261--265). IEEE Computer Society Press. 
[Web Link]