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  2. Statistical significance - Wikipedia

    en.wikipedia.org/wiki/Statistical_significance

    The term significance does not imply importance here, and the term statistical significance is not the same as research significance, theoretical significance, or practical significance. [1] [2] [18] [19] For example, the term clinical significance refers to the practical importance of a treatment effect. [20]

  3. Misuse of statistics - Wikipedia

    en.wikipedia.org/wiki/Misuse_of_statistics

    Statistical significance is a measure of probability; practical significance is a measure of effect. [24] A baldness cure is statistically significant if a sparse peach-fuzz usually covers the previously naked scalp. The cure is practically significant when a hat is no longer required in cold weather and the barber asks how much to take off the ...

  4. Sample size determination - Wikipedia

    en.wikipedia.org/wiki/Sample_size_determination

    It is usually determined on the basis of the cost, time or convenience of data collection and the need for sufficient statistical power. For example, if a proportion is being estimated, one may wish to have the 95% confidence interval be less than 0.06 units wide. Alternatively, sample size may be assessed based on the power of a hypothesis ...

  5. Foundations of statistics - Wikipedia

    en.wikipedia.org/wiki/Foundations_of_statistics

    Statistical significance measures probability and does not address practical significance. It can be viewed as a criterion for the statistical signal-to-noise ratio . It is important to note that the test cannot prove the hypothesis (of no treatment effect), but it can provide evidence against it.

  6. Fisher's exact test - Wikipedia

    en.wikipedia.org/wiki/Fisher's_exact_test

    Fisher's exact test (also Fisher-Irwin test) is a statistical significance test used in the analysis of contingency tables. [1] [2] [3] Although in practice it is employed when sample sizes are small, it is valid for all sample sizes.

  7. Statistics - Wikipedia

    en.wikipedia.org/wiki/Statistics

    Two main statistical methods are used in data analysis: descriptive statistics, which summarize data from a sample using indexes such as the mean or standard deviation, and inferential statistics, which draw conclusions from data that are subject to random variation (e.g., observational errors, sampling variation). [4]

  8. Statistical hypothesis test - Wikipedia

    en.wikipedia.org/wiki/Statistical_hypothesis_test

    An example of Neyman–Pearson hypothesis testing (or null hypothesis statistical significance testing) can be made by a change to the radioactive suitcase example. If the "suitcase" is actually a shielded container for the transportation of radioactive material, then a test might be used to select among three hypotheses: no radioactive source ...

  9. Exploratory data analysis - Wikipedia

    en.wikipedia.org/wiki/Exploratory_data_analysis

    Tukey defined data analysis in 1961 as: "Procedures for analyzing data, techniques for interpreting the results of such procedures, ways of planning the gathering of data to make its analysis easier, more precise or more accurate, and all the machinery and results of (mathematical) statistics which apply to analyzing data."