Reference no: EM13925632

In tests involving a sample mean or proportion, the alternative hypothesis will state that the population parameter is equal to

some value.

True ? False

When a claim or assertion is involved in hypothesis testing, the null hypothesis is always the same as the statement itself. ?

True ? False

When a null hypothesis can be rejected by an extreme result in one direction only, a two-tail test is appropriate. ? True ? False

An Internal Revenue Service official says, "The percentage of taxpayers who overpay the taxes they owe is considerably less

than 10%." In the related hypothesis test, we should apply the "Missouri Rule" in setting up the null and alternative

hypotheses.

True ? False

The level of significance refers to the probability of making a Type I error.

True ? False

For a given sample size, revising a decision rule so that the probability of a Type I error is decreased will also decrease the

probability of making a Type II error.

? True ? False

The first step in hypothesis testing is to determine the critical value(s) of the test statistic.

True ? False

Compared to using a = 0.10, the selection of a = 0.001 will tend to make it less likely that a true null hypothesis will be

rejected.

? True ? False

If the null and alternative hypotheses are H0: μ ≤ 100 and H1: μ >100, the appropriate test will be right-tail.

? True ? False

If the null and alternative hypothesis are H0: μ = 50 and H1: μ 50, the appropriate test will be left-tail.

? True ? False

The normal distribution is always used when the null hypothesis involves a population mean.

? True ? False

In practice, the population standard deviation is usually known, making it unnecessary to approximate its value with the

sample standard deviation, s.

? True ? False

For tests involving a proportion, the normal distribution is considered to be appropriate as an approximation for the binomial

distribution whenever nπ ³ 5 and n(1 - π) ³ 5.

True ? False

Failure to reject a null hypothesis does not constitute proof that it is true, but rather indicates that we are unable to reject it at

the level of significance being used for the test.

? True ? False

The p-Value in hypothesis testing corresponds to the significance level where a critical value of the test statistic is exactly the

same as the calculated value.

? True ? False

The p-Value for a certain hypothesis test is 0.13. If we were to evaluate the results at a significance level of 0.10, the null

hypothesis would be rejected.

? True ? False

The power of a test refers to the probability that the test will correctly reject a null hypothesis that is false.

? True ? False

PART B

Circle the correct answer for questions 18 to 33.

In hypothesis testing, the null hypothesis is a statement assumed to be

true unless we have strong evidence that it is false.

false unless we have strong evidence that it is true.

true regardless of the nature of our evidence.

false regardless of the nature of our evidence.

Whenever the null hypothesis is not rejected, the alternative hypothesis

is also not rejected.

is rejected.

must be revised.

replaces the null hypothesis.

"Well over 70% of last year's graduates have jobs in their field of study." If the "Missouri Rule" is applied to the related

hypothesis test, the null and alternative hypotheses will be:

H0: π ³ 0.70, H1: π < 0.70.

H0: π < 0.70, H1: π ³ 0.70.

H0: π = 0.70, H1: π ¹ 0.70.

H0: π ≤ 0.70, H1: π > 0.70.

The probability of rejecting a true null hypothesis is

the significance level of the test.

the power of the test.

always less than 0.20 for two-tail tests.

None of the preceding.

In hypothesis testing, the decision rule is based on calculated versus critical value(s) for the

population parameter. c. sample size.

test statistic. d. power of the test.

"The proportion of business-improvement loan applications turned down in this state is no more than 15%." If the null

hypothesis is H0: π ≤ 0.15, the appropriate alternative hypothesis is

H1: π ¹ 0.15.

 H1: π = 0.15.

H1: π > 0.15.

H1: π < 0.15.

The population from which a random sample has been selected is normally distributed. For a hypothesis test involving the

sample mean, the t-test should be used instead of the z-test if

n < 30 and standard deviation of the population is not known.

n ³ 30 and standard deviation of the population is unknown.

n < 30 and standard deviation of the population is known.

Both (a) and (b).

"The average management consultant spends $750 per year on industry publications and seminar attendance to stay abreast of developments in the field." In evaluating the null hypothesis derived from this assertion, the appropriate test would be

two-tail. c. right-tail.

left-tail d. None of the preceding.

In a right-tail test with H0: μ ≤ 100 and H1: μ > 100, the sample mean is x = 150. The null hypothesis.

should be rejected.

should be rejected only if n ³ 30.

should not be rejected.

not enough information is given.

In testing H0 : π ≤ 0.30 against H1 : π > 0.30, the critical value of the test statistic is

= +1.96. If the sample proportion is p = 0.35 and the standard error of the sample proportion is = 0.02, the appropriate

conclusion would be to

reject H0.

fail to reject both H0 and H1.

fail to reject H0.

reject both H0 and H1.

An inventor claims that her new device will "drastically reduce" the oil consumption of gasoline-powered vehicles in a corporate

fleet. Currently, the average vehicle requires 2.3 quarts of oil between changes. The appropriate null and alternative

hypotheses in evaluating her claim will be

H0: μ ³ 2.3 and H1: μ < 2.3.

H0: μ ≤ 2.3 and H1: μ > 2.3.

H0: μ ≤ 2.3 and H1: μ < 2.3.

H0: μ = 2.3 and H1: μ ¹ 2.3.

In a given hypothesis test, the null hypothesis cannot be rejected at the 0.025 and 0.01 levels, but can be rejected at the 0.05

and 0.10 levels. The most accurate statement we can make about the p-Value for this test is

p-Value = 0.05.

p-Value > 0.10.

0.025 < p-Value < 0.05.

0.05 < p-Value < 0.10.

In a one-tail test involving a sample mean, the p-Value is found to be equal to 0.10. If the test had been two-tail instead of

one-tail, the p-Value would have been

. 0.20

. 0.10.

. 0.05.

. 0.025.

Based on sample data, the 95% confidence interval for the population mean is from $150 to $250.

If the a = 0.05 level of significance were used in testing H0: μ = $260 versus H1: μ ¹ $260, the null hypothesis

would be rejected.

would not be rejected.

would have to be revised.

Not enough information is given.

The power of a test is the probability that it will

reject a true null hypothesis.

reject a false null hypothesis

fail to reject a true null hypothesis

fail to reject a false null hypothesis

For a given level of significance (a), increasing the sample size will

reduce the probability of making a Type I error.

reduce the probability of making a Type II error.

have no effect on the probability of making either type of error.

Both (a) and (b).