This practice is designed to permit users of sample survey data to judge the trustworthiness of results from such surveys. Section 5 gives extended definitions of the concepts basic to survey sampling and the user should verify that such concepts were indeed used and understood by those who conducted the survey. What was the frame? How large (exactly) was the quantity N? How was the parameter θ estimated and its standard error calculated? If replicate subsamples were not used, why not?

Adequate answers should be given for all questions. There are many acceptable answers to the last question. If the sample design was relatively simple, such as simple random or stratified, then good estimates of sampling variance are easily available. If a more complex design was used then methods such as discussed in [1] may be acceptable. Replicate subsamples is the most straightforward way to estimate sampling variances when the survey design is complex.

Once the survey procedures that were used satisfy Section 5, consult Section 4 to see if any increase in sample size is needed. The calculations for making it are objectively described in Section 4.

Refer to Section 6 to guide in the interpretation of the uncertainty in the reported value of the parameter estimate, θ, i.e. the value of its standard error, se(θ). The quantity se(θ) should be reviewed to verify that the risks it entails are commensurate with the size of the sample.

1.1 This practice presents rules for accepting or rejecting evidence based on a sample. Statistical evidence for this practice is in the form of an estimate of a proportion, an average, a total, or other numerical characteristic of a finite population or lot. It is an estimate of the result which would have been obtained by investigating the entire lot or population under the same rules and with the same care as was used for the sample.

1.2 One purpose of this practice is to describe straightforward sample selection and data calculation procedures so that courts, commissions, etc. will be able to verify whether such procedures have been applied. The methods may not give least uncertainty at least cost, they should however furnish a reasonable estimate with calculable uncertainty.

1.3 This practice is primarily intended for one-of-a-kind studies. Repetitive surveys allow estimates of sampling uncertainties to be pooled; the emphasis of this practice is on estimation of sampling uncertainty from the sample itself. The parameter of interest for this practice is effectively a constant. Thus, the principal inference is a simple point estimate to be used as if it were the unknown constant, rather than, for example, a forecast or prediction interval or distribution devised to match a random quantity of interest.

This standard does not purport to address all of the safety concerns, if any, associated with its use. It is the responsibility of the user of this standard to establish appropriate safety and health practices and determine the applicability of regulatory limitations prior to use.