biased sample


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biased sample

[¦bī·əst ′sam·pəl]
(statistics)
A sample obtained by a procedure that incorporates a systematic error introduced by taking items from a wrong population or by favoring some elements of a population.

biased sample

a population SAMPLE which is not a true reflection of the parent population (see BIAS 2), i.e. not a REPRESENTATIVE SAMPLE.

When the incidence of a certain occurrence or piece of behaviour in a population is to be investigated, e.g. voting intention, it is often impossible to examine the total population, so a sample of this population is taken. For this sample to produce acceptable data, it must be a true representation of the parent population, so it is essential that it is selected in a way that ensures this. If this is not managed, bias will result and the information collected will not truly reflect the population being studied. Thus, to select a sample by questioning people in the street will bias it against people who do not walk, do not go shopping, are at work or school all day Postal QUESTIONNAIRES attempt to overcome this type of bias, but are likely to be biased against those who do not bother to fill in questionnaires and re turn them, and against the illiterate. To keep bias to a minimum, if random sampling is not possible, it is necessary to select the sample carefully by matching all relevant parameters of the population, e.g. age, class, residence, etc, and to ensure as high a response rate as possible, probably by personal INTERVIEWS.

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Claims in the Spanish data set are randomly selected from each class to create a biased sample of 1,000 claims with a target sample fraud rate of 25 percent (versus 49.
In other applications of live-capture data, the way to manage bias is less clear and investigators should aim at minimising the bias by using more than one method of capture and apply caution when interpreting the results from possibly biased samples of individuals.
I suppose this might provide a biased sample, though.
Taylor herself acknowledges that her methodological approach has a number of flaws: the sampling framework employed led to a biased sample, both in terms of gender and of care experience, and there is a lack of quantifiable 'evidence' (which could perhaps have been extracted from case-file records) that could have added weight to the conclusions.
For example, the studies have very small sample sizes, biased sample selection, or lack of control groups.
This led to a geographically biased sample, unless the population density of males approximately 20-40 years of age happened to correspond with the catchment areas for testicular cancer of the hospitals used for the recruitment of cases, weighted by the number of cases for each one.
Moreover, many women may not agree to being examined, producing a biased sample.
Summaries of evidence will yield misleading results if they try to combine results across patient groups or test methods that are too heterogeneous; if they assemble an incomplete, biased sample of potentially available studies; or if they use results from studies that are themselves methodologically weak and very susceptible to bias.
Finally, even within this already biased sample, Alford excludes contradictory data.