Electoral Calculus is a member of the British Polling Council and abides by its rules.

One of these rules is that members should disclose their sampling methodology for conducting polls. Electoral Calculus commissions fieldwork, and the methodology can vary from one fieldwork provider to another. Where appropriate, links are given to the fieldwork agent's own declaration.

Find Out Now have their statement of sampling methodology here.

Electoral Calculus will then weight the raw responses from the fieldwork agent, according to those demographic and political variables which are most relevant to the survey. Weighting details will be disclosed on each individual poll.

Electoral Calculus will also publish the effective sample size of the opinion poll (where possible). This is a measure which adjusts the actual sample size, to show a sample size which reflects how non-uniform the sample is. Samples which are close to uniform, will have an effective sample size which is close to the original sample size, but samples which are significantly non-uniform will have a lower effective sample size. The effective sample size is defined as the size of the uniform sample which has the same sample noise as the actual sample, and is defined via the classic polling weights $w_i$ as $$ n_{\hbox{eff}} = {\bigl(\sum_{i=1}^n w_i\bigr)^2\over\sum_{i=1}^n w_i^2}. $$ This provides a useful simple measure of the precision of the survey.

Where regression methods are used, there is less need for samples to be perfectly uniform, since the regression only needs represenatives from each sub-group which is regressed. But the effective sample size will still be shown on the cross-tab tables for information.

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