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Sample size determination or estimation is the act of choosing the number of observations or replicates to include in a statistical sample. 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 ...
p. -value. In null-hypothesis significance testing, the p-value[note 1] is the probability of obtaining test results at least as extreme as the result actually observed, under the assumption that the null hypothesis is correct. [2][3] A very small p -value means that such an extreme observed outcome would be very unlikely under the null hypothesis.
A statistical hypothesis test is a method of statistical inference used to decide whether the data sufficiently supports a particular hypothesis. A statistical hypothesis test typically involves a calculation of a test statistic. Then a decision is made, either by comparing the test statistic to a critical value or equivalently by evaluating a ...
Statistical significance. In statistical hypothesis testing, [1][2] a result has statistical significance when a result at least as "extreme" would be very infrequent if the null hypothesis were true. [3] More precisely, a study's defined significance level, denoted by , is the probability of the study rejecting the null hypothesis, given that ...
Power (statistics) In frequentist statistics, power is a measure of the ability of an experimental design and hypothesis testing setup to detect a particular effect if it is truly present. In typical use, it is a function of the test used (including the desired level of statistical significance), the assumed distribution of the test (for ...
Tukey's range test. Tukey's range test, also known as Tukey's test, Tukey method, Tukey's honest significance test, or Tukey's HSD (honestly significant difference) test, [1] is a single-step multiple comparison procedure and statistical test. It can be used to correctly interpret the statistical significance of the difference between means ...
In statistics, an effect size is a value measuring the strength of the relationship between two variables in a population, or a sample-based estimate of that quantity. It can refer to the value of a statistic calculated from a sample of data, the value of a parameter for a hypothetical population, or to the equation that operationalizes how statistics or parameters lead to the effect size ...
0.00034 has 2 significant figures (3 and 4) if the resolution is 0.00001. Zeros to the right of the last non-zero digit (trailing zeros) in a number with the decimal point are significant if they are within the measurement or reporting resolution. 1.200 has four significant figures (1, 2, 0, and 0) if they are allowed by the measurement resolution.