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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. In complex studies ...

  3. 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.

  4. Research design - Wikipedia

    en.wikipedia.org/wiki/Research_design

    A strong research design yields valid answers to research questions while weak designs yield unreliable, imprecise or irrelevant answers. [ 1 ] Incorporated in the design of a research study will depend on the standpoint of the researcher over their beliefs in the nature of knowledge (see epistemology ) and reality (see ontology ), often shaped ...

  5. Fisher's exact test - Wikipedia

    en.wikipedia.org/wiki/Fisher's_exact_test

    With large samples, a chi-squared test (or better yet, a G-test) can be used in this situation. However, the significance value it provides is only an approximation, because the sampling distribution of the test statistic that is calculated is only approximately equal to the theoretical chi-squared distribution. The approximation is poor when ...

  6. Power (statistics) - Wikipedia

    en.wikipedia.org/wiki/Power_(statistics)

    A priori power analysis is conducted prior to the research study, and is typically used in estimating sufficient sample sizes to achieve adequate power. Post-hoc analysis of "observed power" is conducted after a study has been completed, and uses the obtained sample size and effect size to determine what the power was in the study, assuming the ...

  7. Statistical hypothesis test - Wikipedia

    en.wikipedia.org/wiki/Statistical_hypothesis_test

    Report the exact level of significance (e.g. p = 0.051 or p = 0.049). Do not refer to "accepting" or "rejecting" hypotheses. If the result is "not significant", draw no conclusions and make no decisions, but suspend judgement until further data is available. If the data falls into the rejection region of H1, accept H2; otherwise accept H1.

  8. Sampling (statistics) - Wikipedia

    en.wikipedia.org/wiki/Sampling_(statistics)

    In social science research, snowball sampling is a similar technique, where existing study subjects are used to recruit more subjects into the sample. Some variants of snowball sampling, such as respondent driven sampling, allow calculation of selection probabilities and are probability sampling methods under certain conditions.

  9. Analysis of variance - Wikipedia

    en.wikipedia.org/wiki/Analysis_of_variance

    Power analysis is often applied in the context of ANOVA in order to assess the probability of successfully rejecting the null hypothesis if we assume a certain ANOVA design, effect size in the population, sample size and significance level. Power analysis can assist in study design by determining what sample size would be required in order to ...