A is a claim or assertion either about one or more population or process characteristics (parameters) or else about the form of the population or process distribution.

statistical hypothesis.

Step-by-step explanation:

A statistical hypothesis has the central objective of assisting in a decision-making process about one or more populations in relation to the sample data, allowing the observance of whether the information found in the samples will support the statistical hypothesis.

It is necessary to know concepts of mathematical probability to perform the tests, the most used models for this purpose are the fisher method, by Neyman-Pearson and Bayes.

The variables used in a statistical hypothesis are: the Null Hypothesis, the one that is assumed to be the true one, the Alternative Hypothesis, the one that is used when there is no statistic to analyze the hypothesis given as true, the Type I Error, related to the probability of rejection of the null hypothesis, and the Type II Error, which is the probability of rejection of the alternative hypothesis if it is true.

a

step-by-step explanation:

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