Ch10 Introduction To Hypothesis Testing Test Bank + Answers

MULTIPLE‑CHOICE TEST ITEMS

CHAPTER 10

INTRODUCTION TO HYPOTHESIS TESTING: THE z TEST

10.1 A sample mean qualifies as a common outcome if the difference between its value and that of the

a) population mean is small enough to be viewed as merely another random outcome.

b) population mean is large enough to be viewed as merely another random outcome.

c) hypothesized population mean is small enough to be viewed as merely another random outcome.

d) hypothesized population mean is large enough to be viewed as merely another random outcome.

10.2 A sample mean qualifies as a rare outcome if it appears to emerge from the

a) dense concentration of possible sample means in the middle of the sampling distribution.

b) dense concentration of possible sample means in either tail of the sampling distribution.

c) sparse concentration of possible sample means in the middle of the sampling distribution.

d) sparse concentration of possible sample means in either tail of the sampling distribution.

10.3 A rare outcome signifies that, with respect to the null hypothesis,

a) nothing special is happening in the underlying population.

b) something special is happening in the underlying population.

c) nothing special is happening in the sample.

d) something special is happening in the sample.

10.4 A common outcome signifies that the null hypothesis should be

a) retained.

b) rejected.

c) ignored.

d) modified.

10.5 A rare outcome

a) cannot be readily attributed to variability and leads to the retention of the null hypothesis.

b) cannot be readily attributed to variability and leads to the rejection of the null hypothesis.

c) can be readily attributed to variability and leads to the retention of the null hypothesis.

d) can be readily attributed to variability and leads to the rejection of the null hypothesis.

10.6 If the sampling distribution of is normally distributed, then, it would be most informative to describe the corresponding sampling distribution for z as

a) the normal distribution.

b) the standard normal distribution.

c) having the same mean but a different standard error.

d) having the same standard error but a different mean.

10.7 The shift from to z (in the z test)

a) modifies the results of the hypothesis test.

b) standardizes the test across all situations.

c) increases the accuracy of the test.

d) produces a more conservative test.

10.8 When testing a hypothesis, rejection regions are located in the

a) extreme areas of the hypothesized sampling distribution.

b) middle areas of the hypothesized sampling distribution.

c) most sensitive areas of the hypothesized sampling distribution.

d) most questionable areas of the hypothesized sampling distribution.

10.9 To express a sample mean as a z ratio,

a) subtract the hypothesized population mean.

b) subtract the hypothesized population mean and divide by the standard deviation.

c) subtract the hypothesized population mean and divide by the variance.

d) subtract the hypothesized population mean and divide by the standard error.

10.10 In a z test, the z ratio indicates how many __________units the sample mean deviates from the hypothesized population mean.

a) original

b) standard deviation

c) standard error

d) critical

10.11 The z test for a population mean requires that you know the value of

a) the population standard deviation.

b) the sample standard deviation.

c) the population mean.

d) all of the above.

10.12 In the step-by-step hypothesis testing procedure, the first step describes the

a) research problem.

b) decision rule.

c) calculations.

d) statistical hypotheses.

10.13 The null hypothesis

a) is tested indirectly.

b) makes a claim about a range of values.

c) usually asserts that nothing special is happening with respect to some population

characteristic.

d) usually is identified with the research hypothesis.

10.14 The alternative hypothesis

a) is the opposite of the null hypothesis.

b) specifies a range of possible values.

c) usually is identified with the research hypothesis.

d) is described by all of the above

10.15 In those cases where you can't identify a meaningful null hypothesis,

a) use an arbitrary number.

b) convert to zero.

c) move on to another situation where a meaningful null hypothesis can be identified.

d) use an entirely different technique known as estimation.

10.16 A decision to reject the null hypothesis implies that

a) there is a lack of support for the alternative hypothesis.

b) there is support for the alternative hypothesis.

c) the sample is probably not representative.

d) the sample size is probably inadequate.

10.17 A decision rule specifies precisely when the null hypothesis should be rejected because the observed z qualifies as

a) a rare outcome.

b) a common outcome.

c) an erroneous outcome.

d) an impossible outcome.

10.18 One very prevalent decision rule specifies that the null hypothesis should be rejected if the observed z

a) equals or is more positive that 1.96.

b) equals or is more negative than ‑1.96.

c) equals or is more positive than 1.96 or equals or is more negative than ‑1.96.

d) falls between ‑1.96 and 1.96.

10.19 Critical z scores separate

a) true and false hypotheses.

b) valid and invalid samples.

c) common and rare outcomes.

d) correct and incorrect decisions.

10.20 The level of significance indicates the

a) proportion of probable outcomes.

b) importance of the statistical analysis.

c) probability that a correct decision has been made.

d) degree of rarity required to reject the null hypothesis.

10.21 The .05 level of significance indicates a degree of rarity of one time in

a) five or less.

b) ten or less.

c) twenty or less.

d) one hundred or less.

10.22 Reject the null hypothesis if the observed z

a) deviates too far into the tails of the sampling distribution.

b) appears to originate from the middle of the sampling distribution.

c) approaches a value of zero.

d) differs from zero.

10.23 Given critical z values of ±1.96 and an observed z value of -2.40, the appropriate decision is to

a) retain the null hypothesis.

b) reject the null hypothesis.

c) neither retain nor reject, but increase the size of the sample.

d) neither retain nor reject, but conduct another investigation.

10.24 Given an observed difference between a sample mean of 42 and a hypothesized population mean of 50, you

a) can conclude that the hypothesis is true.

b) can conclude that the hypothesis is false.

c) must determine whether this observed difference can reasonably be attributed to chance.

d) must determine whether this observed difference reappears in subsequent random samples.

10.25 (NOTE: This question requires Greek letters.) From among the following statistical hypotheses, select the one with the correct form.

a) H₀: μ = 2000

H₁: μ ≠ 2100

b) H₀: μ = 800

H₁: μ = 800

c) H₀: = 50

H₁: ≠ 50

d) H₀: μ = 32

H₁: μ ≠ 32

10.26 (NOTE: This question requires Greek letters.) Given the following information: = 1825; σ = 120; n = 144; and μ_hyp = 1800, the value of the z ratio equals

a) 0.17

b) 2.50

c) 25.00

d) 1825.00