The Shapiro-Wilk check examines if a variable is Ordinarily dispersed within a population. This assumption is required by some statistical assessments such as t-tests and ANOVA.
Sort I and Type II errors are errors built in exploration conclusions. A sort I mistake implies rejecting the null speculation when it’s essentially accurate, when a Type II mistake means failing to reject the null hypothesis when it’s Fake.
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Change the nonconstant variance by the appliance of the variance-stabilizing transformation to the response variable. This process aims at making sure the data satisfies the common assumptions (standardization of the information).
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