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A technique in which samples are taken repeatedly from an existing sample or existing samples.
Resampling using randomisation is a method used at Level Eight. Two examples of this method are provided in the description of randomisation and a summary of the method is given in the paragraphs below this paragraph.
Data are collected to investigate an assertion or a question, usually involving a comparison of a numerical variable between two categories of a category variable (i.e., that there is a link between the numerical variable and the category variable). An estimate of a population parameter is calculated from the data. This observed estimate is often a difference between means but could be a difference between two proportions or a slope of a fitted regression line.
Could an estimate as big as the observed estimate be produced just by chance?
To answer this question, the effect of sampling variation alone on the estimate needs to be considered when it is assumed that there is no link between the two variables. If random allocation alone could easily produce an estimate as big as the observed estimate then the data cannot be interpreted as support for the existence of a link between the two variables. Values of the numerical variable obtained from the data collection are randomly allocated to the two categories of the category variable. An estimate is calculated from this ‘resampling using randomisation’ process. This process is repeated many times to form a distribution of estimates under sampling variation alone.
By comparing the observed estimate with the distribution of estimates, an assessment can be made of the strength of evidence the data provide for the assertion or provide for a conclusion to the question. This assessment is made by looking at the percentage of estimates under sampling variation alone that are at least as far from zero as the observed estimate.
See: randomisation, strength of evidence
Curriculum achievement objectives reference
Statistical investigation: Level 8
