Previous: , Up: Selecting data for analysis   [Contents][Index]


13.7 WEIGHT

WEIGHT BY var_name.
WEIGHT OFF.

WEIGHT assigns cases varying weights, changing the frequency distribution of the active dataset. Execution of WEIGHT is delayed until data have been read.

If a variable name is specified, WEIGHT causes the values of that variable to be used as weighting factors for subsequent statistical procedures. Use of keyword BY is optional but recommended. Weighting variables must be numeric. Scratch variables may not be used for weighting (see Scratch Variables).

When OFF is specified, subsequent statistical procedures weight all cases equally.

A positive integer weighting factor w on a case yields the same statistical output as would replicating the case w times. A weighting factor of 0 is treated for statistical purposes as if the case did not exist in the input. Weighting values need not be integers, but negative and system-missing values for the weighting variable are interpreted as weighting factors of 0. User-missing values are not treated specially.

When WEIGHT is specified after TEMPORARY, it affects only the next procedure (see TEMPORARY).

WEIGHT does not cause cases in the active dataset to be replicated in memory.

13.7.1 Example Weights

One could define a dataset containing an inventory of stock items. It would be reasonable to use a string variable for a description of the item, and a numeric variable for the number in stock, like in Example 13.5.

data list notable list /item (a16) quantity (f8.0).
begin   data
nuts    345
screws  10034
washers 32012
bolts   876
end data.

echo 'Unweighted frequency table'.
frequencies /variables = item /format=dfreq.

weight by quantity.

echo 'Weighted frequency table'.
frequencies /variables = item /format=dfreq.

Example 13.5: Setting the weight on the variable quantity

One analysis which most surely would be of interest is the relative amounts or each item in stock. However without setting a weight variable, FREQUENCIES (see FREQUENCIES) does not tell us what we want to know, since there is only one case for each stock item. Example 13.6 shows the difference between the weighted and unweighted frequency tables.

Unweighted frequency table

item
Frequency Percent Valid Percent Cumulative Percent
Valid bolts 1 25.0% 25.0% 25.0%
nuts 1 25.0% 25.0% 50.0%
screws 1 25.0% 25.0% 75.0%
washers 1 25.0% 25.0% 100.0%
Total 4 100.0%

Weighted frequency table

item
Frequency Percent Valid Percent Cumulative Percent
Valid washers 32012 74.0% 74.0% 74.0%
screws 10034 23.2% 23.2% 97.2%
bolts 876 2.0% 2.0% 99.2%
nuts 345 .8% .8% 100.0%
Total 43267 100.0%

Example 13.6: Weighted and unweighted frequency tables of items


Previous: TEMPORARY, Up: Selecting data for analysis   [Contents][Index]