5. Conclusions True or false: In hypothesis testing, it is never valid to form a conclusion of supporting the null hypothesis.
Given Statement:
In hypothesis testing, it is never valid to form a conclusion of supporting the null hypothesis.
A hypothesis test is a standard procedure for testing a claim about a property or parameter of a population.
The null hypothesis is a statement that the value of a population parameter is equal to some claimed value.
The alternative hypothesis is the statement that the parameter has a value that somehow differs from the null hypothesis.
We directly test the null hypothesis and null hypothesis cannot be accepted, just because it is not rejected. Data not sufficient to show convincingly that a difference between mean is not zero does not prove that the difference is 0. Such data may even suggest that the null hypothesis is false but not strong enough to make a convincing case that the null hypothesis is false.
Suppose p-value is 0.15 which is greater than significance level we fail to reject the null hypothesis. There would be no basis to conclude that the null hypothesis is true. It may or may not be true, there is just no strong evidence to reject it.
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