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Sagot :
We have enough data to reject our null hypothesis if the value of our test statistics falls below critical values of z at a 1.25% level of significance (critical values are -1.645 and 1.645). This is because the test statistic value will not fall within this region.
Given that the population mean is 650, we do a two-tail hypothesis test with a level of significance of 0.025.
Let, μ = population mean
Thus, Null hypothesis, [tex]H_{0}[/tex]:μ= 650.
Alternate Hypothesis, [tex]H_{A}[/tex]:μ≠650
In this case, the population mean is equal to 650, according to the null hypothesis.
The alternative hypothesis, on the other hand, contends that the population mean is not 650.
First things first: the level of significance to be accepted for the two-tailed test is ([tex]\frac{\alpha }{2}[/tex]= [tex]\frac{0.025}{2}[/tex]) = 0.0125 or 1.25%.
Therefore, the following is the decision rule for rejecting a null hypothesis:
We have enough data to reject our null hypothesis if the value of our test statistics falls in the rejection region and is less than the critical values of z at a 1.25% level of significance (critical values are -1.645 and 1.645). This is because the test statistic value will not fall within this region.
Learn more about hypothesis test here :https://brainly.com/question/17221912
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