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Answer :
This is a condensed explanation of the hypothesis testing procedure; other elements like sample size, population distribution, and t-test assumptions should also be taken into account.
The rationale for hypothesis testing.
A claim is tested for plausibility using sample data to see if it is true. The test provides evidence that, given the available information, the hypothesis is tenable.
Consider a scenario in which we have a sample of n Martian people and want to evaluate the claim that the population's mean height is higher than 1.70 metres. The alternate and nil hypotheses are as follows:
sqrt(sum((height - x)2) / (n - 1)) = x = (sum of all heights) / n s =
When is the assumed population mean, the formula for time is t = (x - ) / (s / sqrt(n)).
The alternative hypothesis—that the mean height on Mars is more than 1.70 meters—is supported by evidence if the p-value is less than or equal to 0.05, which means we reject the null hypothesis.
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