Ch. 9 QMB

Which of the following describes a Type II Error?

Accept H0 when H0 is false.

A student wants to determine if pennies are really fair, meaning equally likely to land heads up or tails up. He flips a random sample of 50 pennies and finds that 28 of them land heads up. What are the appropriate null and alternative hypotheses?

Ho:p=.5, Ha:p≠.5 (28/50=.5)

Which of the following null hypotheses cannot be correct?

Ho:p≠10

Which of the following describes a Type I Error?

Reject H0 when H0 is true.

Which of the following does not need to be known in order to compute the p-value?

The level of significance

What is the probability of making a Type I error?

a

For a lower tail test, the p-value is the probability of obtaining a value for the test statistic:

at least as small as that provided by the sample.

As the test statistic becomes larger, the p-value:

becomes smaller.

Whenever the probability of making a Type II error has not been determined and controlled, only two conclusions are possible. We either reject H0 or:

do not reject H0.

The probability of making a Type I error when the null hypothesis is true as an equality is called the:

level of significance.

The p-value:

must be a number between 0 and 1.

For the case where σ is unknown, the test statistic has a t distribution. How many degrees of freedom does it have?

n - 1

The p-value is a probability that measures the support (or lack of support) for the:

null hypothesis.

For the case where σ is unknown, which statistic is used to estimate σ?

s

Applications of hypothesis testing that only control for the Type I error are called:

significance tests.

In hypothesis testing, the tentative assumption about the population parameter is called:

the null hypothesis.

For a two-tailed test, the p-value is the probability of obtaining a value for the test statistic as:

unlikely as that provided by the sample.