Requires Microsoft Excel 2.2 or an application capable of reading and utilizing Excel Worksheets. Requires at least 20 observations (scores) to properly compute all statistics.
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DataDef
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defines, characterizes and classifies score distributions with two purposes in mind:
1) Selecting appropriate statistics and
2) Identifying distributional characteristics that should
be considered in interpretation.
DataDef will estimate distribution characteristics for data sets of any size having up to 100 sample points. Twenty seven statistics (see enclosed documentation for detail) are computed and used to classify distributions into one of 24 cells of Tail Weight and Symmetry/Asymmetry as defined in Micceri (1989). Operating on the assumption that the nature of score distributions influences both statistical findings and the interpretations allowable for different data sets, this program was written to enable comprehensive description of data sets and their classification into categories that allow one to estimate how robust various statistics will be when applied to said data.
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DataDef is SHAREWARE
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Please pass it on. If you like it, use it for more than one month, or want updates and revisions, please send between $5 and $15 to the starving author and his big, voracious family:
Theodore Micceri
527 Lantern Circle
Temple Terrace, FL 33617
(813) 988-0056
FAX (813) 974-3493
CIS 70303,1275
Also, please send comments or any improvements you make. Note that I avoided Macros and other simplifying techniques to allow easier transfer across platforms.
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QUICK START
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DataDef may be used alone or in combination with the two other link spreadsheets that are enclosed. Those are designed to simplify data entry and/or to create a data base of the distributions with which you work.
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USE ALONE
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Spawn a copy before making changes in DataDef. A distribution's Skewness and Tail-Weight categories are shown in Cells B4 & B5 using the following groupings. Details on the limits of categories can be found in Micceri, 1989.
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SKEWNESS TAIL WEIGHT
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1 Relatively Symmetric Uniform
2 Moderate Asymmetry Lighter than Gaussian
3 Extreme Asymmetry About Gaussian
4 Exponential or Greater Moderately Heavy Tailed
5 Extremely Heavy Tailed
6 Double Exponential or Greater
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Descriptive statistics are provided in cells B8 to B25 and D8 to D16 (Percentiles). Note that percentiles are computed within class intervals, assuming discrete rather than continuous data. No other readily available packaged statistical application of which I am aware computes percentiles in this way, although it is the only appropriate one. Please write if you desire a paper describing the rationale and method.
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TO EVALUATE A DISTRIBUTION:
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1) - first define the distance between two of your measure's scale points in column B2. If not specifically identified, DataDef assumes the width of each point to be 1.0.
2) - enter or paste a distributions scores and frequencies in column A48 to A148 and B48 to B148
3) - Select "CALCULATE NOW" from the OPTIONS menu and all statistics and categories will be computed.
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OR IN COMBINATION
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Three linked spreadsheets are provided to simplify data entry or to assist in creating a data base of distribution characteristics. Follow these steps in order.
1) Open Frequncy - This spreadsheet is linked to DataDef. Enter a title for the data set in cell B1, and identification number in cell B2, the width of each scale point in cell B3 (if none, 1.0 is assumed) and the number of cases (this will be used to compare with the number entered in a frequency distribution) into cell B4. Then either enter or paste the Scores and their frequencies into cells A7 to A107 and B7 to B107.
2) DataDef - Open DataDef, update from other documents and select CALCULATE NOW from the OPTIONS menu.
3) DataBase - Open Data.Base and update from other documents. The values in row 2 are from your most recently entered data sets. These will be replaced any time the data are updated, therefore, if you wish to create an historical data base, copy this row to the bottom and save this worksheet. It is not necessary to save any other worksheets unless you wish to retain data from a specific distribution.
REFERENCES:
Micceri, T. (1989). The Unicorn, The Normal Curve, and Other Improbable Creatures. The Psychological Bulletin, 105:1, p. 156-166,
