Nonparametric equivalents are proposed by XLSTAT. The normality of the distribution can be tested beforehand using the normality tests. Moreover, it also assumed that the observations are independent and identically distributed. These two tests are said to be parametric as their use requires the assumption that the samples are distributed normally. Use the z-test when the true variance σ² of the population is known. Use the Student's t-test when the true variance of the population from which the sample has been extracted is unknown the variance of sample s² is used as variance estimator. Two parametric tests are possible but they should be used on certain conditions: The Student's t-test When to use the Student's t-test or the z-test One-sample t-test uses a t-distribution with n-1 degrees of freedom. To compare this mean with a reference value μ 0 , two parametric tests are possible: Let the average of a sample be represented by μ. This tool is used to compare the average of a sample represented by µ with a reference value.
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