9.46 Education and Child Development Inter tive Tylenol PM indicated that 8% of
ID: 3180627 • Letter: 9
Question
9.46 Education and Child Development Inter tive Tylenol PM indicated that 8% of American studens have missed a test because they overslept. Suppose officials ai state college decide to apply a new academic policy regarding exams. student arrives late for a the student receiv If a a 0 for the test and cannot take a make-up test at a later time. a. What hypotheses should be tested, in terms of p, the true proportion of students who have missed a test because they overslept, in order for college officials to prove the new academic policy is causing fewer students tote late for exams? b. Which type I more serious for colleg error, or type II, is officials? Why? C. Which error, type or more serious for I type II, is Why?Explanation / Answer
9.46
(a) Hypothesis that should be are as follows:
H0 : p = .08 and Ha : p <.08 . This will be one tailed test . Type 1 error means rejecting the null hypothesis when it is true and type 2 error means not rejecting the null hypothesis when it is false.
Here type one error means rejecting the fact that there is no difference between the proportions when actually there is no difference and type two error means accepting the fact that there is no difference in the proportions but actually there is a difference.
(b) type two error is more serious for college officials as they believe that there is no difference between the proportions when actually there is a difference. Then the rate of missing the test would be higher as the policy will not be set up and hence students will skip more.
(c) type one error is more serious for students because college officials believe that there is a difference between the proportions and they devise the new academic policy but actually there isn't any difference. So students suffer.
9.54 (a) Hypothesis that should be are as follows:
H0 : p = .15 and Ha : p >.15 . This will be one tailed test . Type 1 error means rejecting the null hypothesis when it is true and type 2 error means not rejecting the null hypothesis when it is false.
(b) Here type one error means rejecting the fact that there is no difference between the proportions when actually there is no difference and type two error means accepting the fact that there is no difference in the proportions but actually there is a difference.
(c) As p approaches from .2 to .15 then probability of null hypotheisis being true increases, hence probabilty of type one error falls.
TY!
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