haphazard sampling

hap·haz·ard sam·pling

the assembly of data in an unprescribed and undefined fashion that allows no sound scientific inferences other than establishing the existence of types. (Finding even one unicorn in such a set would establish that unicorns can exist, but no inference about their prevalence could be made from it.) Compare: random sample.
References in periodicals archive ?
0 Opportunistic or haphazard sampling, including voluntary observer programs, to support bycatch or total catch estimation.
Haphazard sampling, e.g., taking a few from the top, middle, and bottom of a list, is another form of judgment sampling, as is convenience sampling, where the sample consists of available cases, as when magazines ask readers to fill out a questionnaire.
2), rather than reflecting the haphazard sampling expected from a limited surface survey without benefit of even exploratory excavations (Garanger 1971:58, 1972:32).
In the case of haphazard sampling, the selection process is intended to emulate equal probability sampling, with the effect that all population elements have the same chance of selection.
The tendency of haphazard sampling to yield biased selections appears to result from subconscious human behavior in the areas of 1) visual perception and 2) the performance of tasks requiring physical effort.
In haphazard sampling, an auditor attempts to select sample items as randomly as possible.
In this article, we refer to data collection without a probability sampling design as "haphazard sampling." The use of haphazardly collected data for estimating abundance is undesirable because they cannot be evaluated by the theorems of probability theory (Krebs, 1989).
The survey data were collected during the six-year survey under three different survey designs, none of which were strictly randomized, but each involved some degree of haphazard sampling due to weather, sediment structure, and other logistical restrictions for beam trawling in small bays off the Gulf of Alaska (Norcross et al.
The most common method of sample selection is haphazard sampling at 74 percent of all applications, followed by dollar-unit sampling at 12 percent of all applications.
The effectiveness of increasing sample size to mitigate the influence of population characteristics in haphazard sampling. Auditing: A Journal of Practice & Theory (March): 169-185.
A recent survey of auditors found that the majority of audit samples are selected using haphazard sampling, i.e., selecting items using professional judgment.
Given these findings, audit practitioners should reevaluate the heavy reliance on haphazard sampling. For critical applications random selection techniques should be used since these techniques are not affected by the features of the population.