ch 9 concepts

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a

An assumption made about the value of a population parameter is called a a. hypothesis b. conclusion c. confidence d. significance

a

As the test statistic becomes larger, the p-value a. gets smaller b. becomes larger c. stays the same, since the sample size has not been changed d. becomes negative

a

A Type II error is committed when a. a true alternative hypothesis is mistakenly rejected b. a true null hypothesis is mistakenly rejected c. the sample size has been too small d. not enough information has been available

c

For a lower bounds one-tailed test, the test statistic z is determined to be zero. The p- value for this test is a. zero b. -0.5 c. +0.5 d. 1.00

a

For a lower tail test, the p-value is the probability of obtaining a value for the test statistic a. at least as small as that provided by the sample b. at least as large as that provided by the sample c. at least as small as that provided by the population d. at least as large as that provided by the population.

d

For a one-tailed hypothesis test (upper tail) the p-value is computed to be 0.034. If the test is being conducted at 95% confidence, the null hypothesis a. could be rejected or not rejected depending on the sample size b. could be rejected or not rejected depending on the value of the mean of the sample c. is not rejected d. is rejected

b

For a two-tail test, the p-value is the probability of obtaining a value for the test statistic as a. likely as that provided by the sample b. unlikely as that provided by the sample c. likely as that provided by the population d. unlikely as that provided by the population

c

For the following hypothesis test, Ho: m = 150 Ha: m < 150 the test statistic a. must be negative b. must be positive c. can be either negative or positive d. must be a number between zero and 1

a

If a hypothesis is not rejected at the 5% level of significance, it a. will also not be rejected at the 1% level b. will always be rejected at the 1% level c. will sometimes be rejected at the 1% level d. None of these alternatives is correct.

b

If a hypothesis is rejected at 95% confidence, it a. will always be accepted at 90% confidence b. will always be rejected at 90% confidence c. will sometimes be rejected at 90% confidence d. None of these alternatives is correct.

d

If a hypothesis is rejected at the 5% level of significance, it a. will always be rejected at the 1% level b. will always be accepted at the 1% level c. will never be tested at the 1% level d. may be rejected or not rejected at the 1% level

d

If a hypothesis test leads to the rejection of the null hypothesis, a. a Type II error must have been committed b. a Type II error may have been committed c. a Type I error must have been committed d. a Type I error may have been committed

d

If the probability of a Type I error (a) is 0.05, then the probability of a Type II error (b) must be a. 0.05 b. 0.95 c. 0.025 d. None of these alternatives is correct.

b

If the test is done at 95% confidence, the null hypothesis should a. not be rejected b. be rejected c. Not enough information is given to answer this question. d. None of these alternatives is correct.

a

If the test is done at the 5% level of significance, the null hypothesis should a. not be rejected b. be rejected c. Not enough information given to answer this question. d. None of these alternatives is correct.

d

In hypothesis testing if the null hypothesis has been rejected when the alternative hypothesis has been true, a. a Type I error has been committed b. a Type II error has been committed c. either a Type I or Type II error has been committed d. the correct decision has been made

b

In hypothesis testing if the null hypothesis is rejected, a. no conclusions can be drawn from the test b. the alternative hypothesis is true c. the data must have been accumulated incorrectly d. the sample size has been too small

b

In hypothesis testing, a. the smaller the Type I error, the smaller the Type II error will be b. the smaller the Type I error, the larger the Type II error will be c. Type II error will not be effected by Type I error d. the sum of Type I and Ttype II errors must equal to 1

b

In hypothesis testing, the tentative assumption about the population parameter is a. the alternative hypothesis b. the null hypothesis c. either the null or the alternative d. None of these alternatives is correct.

a

In order to test the following hypotheses at an a level of significance H0: m 800 Ha: m > 800 the null hypothesis will be rejected if the test statistic Z is a. >/Za b. < Za c. < -Za d. = a

a

In the hypothesis testing procedure, a is a. the level of significance b. the critical value c. the confidence level d. 1 - level of significance

a

The error of rejecting a true null hypothesis is a. a Type I error b. a Type II error c. is the same as β d. committed when not enough information is available

c

The level of significance a. can be any positive value b. can be any value c. is (1 - confidence level) d. can be any value between -1.96 to 1.96

c

The level of significance in hypothesis testing is the probability of a. accepting a true null hypothesis b. accepting a false null hypothesis c. rejecting a true null hypothesis d. None of these alternatives is correct.

b

The level of significance is the a. maximum allowable probability of Type II error b. maximum allowable probability of Type I error c. same as the confidence coefficient d. same as the p-value

d

The p-value a. is the same as the Z statistic b. measures the number of standard deviations from the mean c. is a distance d. is a probability

d

The p-value a. can be any value b. can be any positive value c. can be any value, negative or positive d. must be a number between zero and 1

a

The p-value is a probability that measures the support (or lack of support) for the a. null hypothesis b. alternative hypothesis c. either the null or the alternative hypothesis d. sample statistic

c

The p-value ranges between a. zero and infinity b. minus infinity to plus infinity c. zero to one d. -1 to +1

d

The probability of committing a Type I error when the null hypothesis is true is a. the confidence level b. c. greater than 1 d. the Level of Significance

alpha

The probability of making a Type I error is denoted by which sign? meaning level of significance. type II error is denoted by the cursive B

a

What type of error occurs if you fail to reject H0 when, in fact, it is not true? a. Type II b. Type I c. either Type I or Type II, depending on the level of significance d. either Type I or Type II, depending on whether the test is one tail or two tail

a

When the following hypotheses are being tested at a level of significance of a (alpha) H0: m> 500 Ha: m < 500 the null hypothesis will be rejected if the p-value is a. < a b. > a c. > a/2 d. 1 - a/2

a

When the p-value is used for hypothesis testing, the null hypothesis is rejected if a. p-value < a b. a < p-value c. p-value >a d. p-value = 1 - a

a

When the p-value is used for hypothesis testing, the null hypothesis is rejected if a. p-value </ α b. α < p-value c. p-value α d. p-value = 1 - α

c

Which of the following does not need to be known in order to compute the p-value? a. knowledge of whether the test is one-tailed or two-tailed b. the value of the test statistic c. the level of significance d. None of these alternatives is correct.

t

under and over filling /difference and different= two tail


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