Three functions are available for sampling.

Random Samples

The first function

samp_rand(prop)

allows for simple random sampling. Each case is selected with a probability equal to prop.

For example, for a random sample of one tenth of a data set, use:

where samp_rand(.1)

Random Samples of Fixed Size

The second function

samp_fixed(sample_size,total_observations)

allows a random sample of fixed size to be drawn. When using this function, the first case is drawn with a probability of sample_size/total_observations, and the succeeding i'th case is drawn with a probability of (sample_size - hits) / (total_observations - i).

For example, if you had a data set of 1000 cases and wished for a random sample of 25 cases, you would specify:

where samp_fixed(25,1000)

Systematic Random Samples

Finally, a third function

samp_syst(interval)

performs a systematic sample of every n'th case after a random start. For instance, to take every 6'th case, use:

where samp_syst(6)

Sampling Subsets of the Input Data

Expressions are evaluated from left to right. You can thus sample from a subset of your cases by subsetting them first and then sampling.

For example, to take a random half of high school graduates, use:

where schooling >= 12 & samp_rand(.5)

Sampling Seed and Reproducible Samples

The random number generator that provides the basis of these sampling routines is 'rand_port()' in Jerry Dwyer, "Quick and Portable Random Number Generators." C Users Journal, June, 1995, pp. 33-44. By default, it is seeded using a permutation of the time of day, and will yield a different sample on each run.

If you need a reproducible sample, you can generate it by using the same seed each time. The seed is entered in the General Options section of the Options dialog box and should be a positive integer in the range of one through 2,147,483,646.