Complete the following:
Q1: The probability of Type I error is referred to as the significance level of the test.
True
False
A Type II error is defined as:
rejecting a true null hypothesis.
rejecting a false null hypothesis.
failing to reject a true null hypothesis.
failing to reject a false null hypothesis.
Q2: Consider testing the hypotheses H0: mu = 50 vs. H1: mu does not equal 50. If n = 64, mean = 53.5, and standard deviation = 10, then the value of the test statistic is:
z = 1.96.
t = 1.64.
z = 2.80.
t = 1.96.
z = 1.64
Q3: Failure to reject a null hypothesis constitutes proof that it is true.
True
False
Q4: In order to determine the p-value, which of the following is not needed?
The level of significance
Whether the test is one or two tail
The value of the test statistic
All of these are needed.
Q5: The p-value of a test is:
the smallest alpha at which the null hypothesis can be rejected.
the largest alpha at which the null hypothesis can be rejected.
the smallest alpha at which the null hypothesis cannot be rejected.
all of the above.
Q6: Reducing the probability of a Type I error also reduces the probability of a Type II error.
True
False
Q7: Suppose that we reject a null hypothesis at the .05 level of significance. Then for which of the following alpha values do we also reject the null hypothesis?
0.06
0.04
0.03
0.02
Q8: In testing the hypotheses H0: pi = 0.40, H1: pi > 0.40 at the 5% significance level, if the sample proportion is 0.45, and the standard error of the sample proportion is 0.035, the appropriate conclusion would be:
to reject H0.
not to reject H0.
to reject H1.
to reject both H0 and H1.
Q9: A professor of math refutes the claim that the average student spends 3 hours studying for the midterm exam. Which hypothesis is used to test the claim?
H0: mu does not equal 3, H1: mu > 3
H0: mu = 3, H1: mu does not equal 3
H0: mu does not equal 3, H1: mu = 3
H0: mu = 3, H1: mu < 3