Here are several situations in which there is an incorrect application of the id

Question

Here are several situations in which there is an incorrect application of the ideas presented in this section. Write a short explanation of what is wrong in each situation and why it is wrong. A report says that the alternative hypothesis is rejected because the P-value is 0.002. A significance test rejected the null hypothesis that the sample mean is 120. A report on a study says that the results are statistically significant and the P-value is 0.87. The z statistic had a value of 0.014, and the null hypothesis was rejected at the 5% level because 0.014

Explanation / Answer

(a) The alternative hypothesis will be rejected or not it depends on level of significance and p-value both.

here p-value is given 0.002, and alternative hypothesis is rejected. Thats mean null hypothesis is accepted and thats mean p-value is greater than level of significance. So here level of significance should be given. And also we test always on null hypothesis not on alternative hypothesis. So we must have null hypothesis is accepted.

(b) Here it is given that the null hypothesis sample mean 120 is rejected. But it should be population mean. Because we test the population on base of sample. And also any test is said to be significant if null hypothesis is rejected. So before reaching any conclusion we can not say to any test significant or not.

(c) results arestatistically significant means the null hypothesis is rejected. but if we see the p-value , it is very high, ie 0.87. But to reject null hypothesis we should have p-value less than level of significance. Therefore level of significance must be greater than 0.87, which is not possible.

(d) We reject the null hypothesis if p-value less than level of significance not z-statistic less than level of significance.

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