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  2. Sample size determination - Wikipedia

    en.wikipedia.org/wiki/Sample_size_determination

    The sample size is an important feature of any empirical study in which the goal is to make inferences about a population from a sample. In practice, the sample size used in a study is usually determined based on the cost, time, or convenience of collecting the data, and the need for it to offer sufficient statistical power .

  3. Cross-sectional data - Wikipedia

    en.wikipedia.org/wiki/Cross-sectional_data

    For example, if we want to measure current obesity levels in a population, we could draw a sample of 1,000 people randomly from that population (also known as a cross section of that population), measure their weight and height, and calculate what percentage of that sample is categorized as obese. This cross-sectional sample provides us with a ...

  4. Cross-sectional study - Wikipedia

    en.wikipedia.org/wiki/Cross-sectional_study

    The cross-sectional study has the advantage that it can investigate the effects of various demographic factors (age, for example) on individual differences; but it has the disadvantage that it cannot find the effect of interest rates on money demand, because in the cross-sectional study at a particular point in time all observed units are faced ...

  5. Design effect - Wikipedia

    en.wikipedia.org/wiki/Design_effect

    If the sample size is 1,000, then the effective sample size will be 500. It means that the variance of the weighted mean based on 1,000 samples will be the same as that of a simple mean based on 500 samples obtained using a simple random sample.

  6. PS Power and Sample Size - Wikipedia

    en.wikipedia.org/wiki/PS_Power_and_Sample_Size

    Matched or independent study designs may be used. Power, sample size, and the detectable alternative hypothesis are interrelated. The user specifies any two of these three quantities and the program derives the third. A description of each calculation, written in English, is generated and may be copied into the user's documents.

  7. Jackknife resampling - Wikipedia

    en.wikipedia.org/wiki/Jackknife_resampling

    In statistics, the jackknife (jackknife cross-validation) is a cross-validation technique and, therefore, a form of resampling. It is especially useful for bias and variance estimation. The jackknife pre-dates other common resampling methods such as the bootstrap .

  8. Panel data - Wikipedia

    en.wikipedia.org/wiki/Panel_data

    Both datasets above are structured in the long format, which is where one row holds one observation per time. Another way to structure panel data would be the wide format where one row represents one observational unit for all points in time (for the example, the wide format would have only two (first example) or three (second example) rows of ...

  9. Postcodes in Australia - Wikipedia

    en.wikipedia.org/wiki/Postcodes_in_Australia

    Australian postcodes range from 0200 for the Australian National University (now 2601) to 9944 for Cannonvale, Queensland. Some towns and suburbs have two postcodes — one for street deliveries and another for post office boxes. For example, a street address in the Sydney suburb of Parramatta would be written like this: Mr John Smith 99 George ...

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