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Homework answers / question archive / Liberty University  BUSINESS BMAL 590 ALC9 Quantitative 1)You take a random sample of 100 students at your university and find that their average GPA is 3
Liberty University  BUSINESS BMAL 590
ALC9 Quantitative
1)You take a random sample of 100 students at your university and find that their average GPA is 3.1. If you use this information to help you estimate the average GPA for all students at your university, then you are doing what branch of statistics?
Descriptive statistics
Inferential statistics
Sample statistics
Population statistics
2. A company has developed a new computer sound card whose average lifetime is unknown. In order to estimate this average, 200 sound cards are randomly selected from a large production line and tested; their average lifetime is found to be 5 years. The 200 sound cards represent a
parameter.
statistic.
sample.
population.
3. A company has developed a new computer sound card whose average lifetime is unknown. In order to estimate this average, 200 sound cards are randomly selected from a large production line and tested; their average lifetime is found to be 5 years. The five years represents a
parameter.
statistic.
sample.
population.
4. A summary measure that is computed from a population is called a
sample.
statistic.
population.
parameter.
5. Which of the following is a measure of the reliability of a statistical inference?
A population parameter.
A significance level.
A descriptive statistic.
A sample statistic.
6. The process of using sample statistics to draw conclusions about population parameters is called
finding the significance level.
calculating descriptive statistics.
doing inferential statistics.
calculating the confidence level.
7. Which of the following represents a population, as opposed to a sample?
1,000 respondents to a magazine survey which has 500,000 subscribers.
The first 10 students in your class completing a final exam.
Every fifth student to arrive at the book store on your campus.
All registered voters in the State of Michigan.
8. A study in under way to determine the average height of all 32,000 adult pine trees in a certain national forest. The heights of 500 randomly selected adult pine trees are measured and analyzed. The sample in this study is
the average height of the 500 randomly selected adult pine trees.
the average height of all the adult pine trees in this forest.
all adult pine trees in this forest.
the 500 adult pine trees selected at random selected at random from this forest.
9. The significance level of a statistical inference measures
the proportion of times a conclusion about a population will be correct in the long run.
the proportion of times a conclusion about a population will be wrong in the long run.
the proportion of times an estimation procedure will be correct in the long run.
the proportion of times an estimation procedure will be wrong in the long run.
10.The confidence level of a statistical inference measures
the proportion of times a conclusion about a population will be correct in the long run.
the proportion of times a conclusion about a population will be wrong in the long run.
the proportion of times an estimation procedure will be correct in the long run.
the proportion of times an estimation procedure will be wrong in the long run.
11. A marketing research firm selects a random sample of adults and asks them a list of questions regarding their beverage preferences. What type of data collection is involved here?
An experiment.
A survey.
Direct observation.
None of these choices
12. Which of the following statements is true regarding the design of a good survey?
The questions should be kept as short as possible.
A mixture of dichotomous, multiplechoice, and openended questions may be used.
Leading questions must be avoided.
All of these choices are true.
13. Which method of data collection is involved when a researcher counts and records the number of students wearing backpacks on campus on a given day?
An experiment.
A survey.
Direct observation.
None of these choices.
14. The difference between a sample mean and the population mean is called
nonresponse error.
selection bias.
sampling error.
nonsampling error.
15. The manager of the customer service division of a major consumer electronics company is interested in determining whether the customers who have purchased a videocassette recorder over the past 12 months are satisfied with their products. If there are four different brands of videocassette recorders made by the company, the best sampling strategy would be to use a
simple random sample.
stratified random sample.
cluster sample.
selfselected sample.
16. When every possible sample with the same number of observations is equally likely to be chosen, the result is called a
simple random sample.
stratified random sample.
cluster sample.
biased sample.
17.Which of the following types of samples is almost always biased?
Simple random samples.
Stratified random samples.
Cluster samples.
Selfselected samples.
18.Which of the following is an example of a nonsampling error?
Some incorrect responses are recorded.
Responses are not obtained from all members of the sample.
Some members of the target population cannot possibly be selected for the sample.
All of these choices are true.
19. Which of the following situations lends itself to cluster samples?
When it is difficult to develop a complete list of the population members.
When the population members are widely disbursed.
When selecting and collecting data from a simple random sample is too costly.
All of these choices are true.
20. Which of the following causes sampling error?
Taking a random sample from a population instead of studying the entire population.
Making a mistake in the process of collecting the data.
Nonresponse bias.
All of these choices are true.
21. Which of the following describes selection bias?
A leading question is selected for inclusion in the survey.
Some members of the target population are excluded from possible selection for the sample.
A person selected for the sample has a biased opinion about the survey.
All of these choices are true.
22. An approach of assigning probabilities which assumes that all outcomes of the experiment are equally likely is referred to as the
subjective approach.
objective approach.
classical approach.
relative frequency approach.
23. The collection of all possible outcomes of an experiment is called
a simple event.
a sample space.
a sample.
a population.
24. If event A and event B cannot occur at the same time, then A and B are said to be
mutually exclusive.
independent.
collectively exhaustive.
None of these choices.
25. Which of the following best describes the concept of marginal probability?
It is a measure of the likelihood that a particular event will occur, regardless of whether another event occurs.
It is a measure of the likelihood that a particular event will occur, if another event has already occurred.
It is a measure of the likelihood of the simultaneous occurrence of two or more events.
None of these choices.
26. The intersection of events A and B is the event that occurs when
either A or B occurs but not both.
neither A nor B occur.
both A and B occur.
All of these choices are true.
27. If the outcome of event A is not affected by event B, then events A and B are said to be
mutually exclusive.
independent.
collectively exhaustive.
None of these choices.
28. Suppose P(A) = 0.35. The probability of the complement of A is
0.35.
0.65.
0.35
None of these choices.
29. If the events A and B are independent with P(A)=0.30 and P(B)=0.40, then the probability that both events will occur simultaneously is
0
0.12.
0.70.
Not enough information to tell.
30. If A and B are mutually exclusive events with P(A) = 0.30 and P(B)=0.40, then P(A or B) is
0.10.
0.12.
0.70.
None of these choices.
31. Bayes' Law is used to compute
prior probabilities.
joint probabilities.
union probabilities.
posterior probabilities.
32. Initial estimates of the probabilities of events are known as
joint probabilities.
posterior probabilities.
prior probabilities.
conditional probabilities.
33. The standard deviation of the sampling distribution of x? is also called the
central limit theorem.
standard error of the sample mean.
finite population correction factor.
population standard deviation
34. The Central Limit Theorem states that, if a random sample of size n is drawn from a population, then the sampling distribution of the sample mean
is approximately normal if n > 30.
is approximately normal if n < 30.
is approximately normal if the underlying population is normal.
None of these choices.
35. If all possible samples of size n are drawn from a population, the probability distribution of the sample mean x? is called
the standard error of x?.
the expected value of x?.
the sampling distribution of x?.
he normal distribution.
36. Sampling distributions describe the distributions of
population parameters.
sample statistics.
both parameters and statistics
None of these choices.
37. Suppose X has a distribution that is not normal. The Central Limit Theorem is important in this case because
t says the sampling distribution of x? is approximately normal for any sample size.
it says the sampling distribution of x? is approximately normal if n is large enough.
it says the sampling distribution of x? is exactly normal, for any sample size.
None of these choices.
38. As a general rule, the normal distribution is used to approximate the sampling distribution of the sample proportion only if
the sample size n is greater than 30.
the population proportion p is close to 0.50.
the underlying population is normal.
np and n(1  p) are both greater than or equal to 5.
39. The standard deviation of p? is also called the
standard error of the sample proportion.
standard deviation of the population.
standard deviation of the binomial.
None of these choices.
40. If two populations are normally distributed, the sampling distribution of the difference in the sample means, x?1 – x?2 is
approximately normal for any sample sizes.
approximately normal if both sample sizes are large.
exactly normal for any sample sizes.
exactly normal only if both sample sizes are large.
41. If two random samples of sizes n1 and n2 are selected independently from two populations with means μ1 and μ2, then the mean of x?1  x?2 equals
μ1 + μ2

μ1  μ2 
μ1 / μ2
μ1 μ2
42. If two random samples of sizes n1 and n2 are selected independently from two nonnormally distributed populations, then the sampling distribution of the sample mean difference, x?1  x?2
is always nonnormal.
is always normal.
is approximately normal only if n1 and n2 are both larger than or equal to 30.
is approximately normal regardless of n1 and n2.
43. The standard deviation of x?1  x?2 is also called the
standard error of the difference between two sample means.
standard deviation of the difference between the population means.
normal approximation to the difference of two binomial random variables.
None of these choices.
44. The hypothesis of most interest to the researcher is
the alternative hypothesis.
the null hypothesis.
both hypotheses are of equal interest.
Neither hypothesis is of interest.
45. Type I error occurs when we
reject a false null hypothesis.
reject a true null hypothesis.
don't reject a false null hypothesis.
don't reject a true null hypothesis.
46. A Type II error is defined as
rejecting a true null hypothesis.
rejecting a false null hypothesis.
not rejecting a true null hypothesis.
not rejecting a false null hypothesis.
47. Which of the following probabilities is equal to the significance level α?
Probability of making a Type I error.
Probability of making a Type II error.
Probability of rejecting H0 when you are supposed to.
Probability of not rejecting H0 when you shouldn't.
48. If we reject the null hypothesis, we conclude that
there is enough statistical evidence to infer that the alternative hypothesis is true.
here is not enough statistical evidence to infer that the alternative hypothesis is true.
there is enough statistical evidence to infer that the null hypothesis is true.
there is not enough statistical evidence to infer that the null hypothesis is true.
49. Statisticians can translate pvalues into several descriptive terms. Suppose you typically reject H0 at level 0.05. Which of the following statements is correct?
If the pvalue < 0.01, there is overwhelming evidence to infer that the alternative hypothesis is true.
If 0.01 < pvalue < 0.05, there is evidence to infer that the alternative hypothesis is true.
If pvalue > 0.10, there is no evidence to infer that the alternative hypothesis is true.
All of these choices are true.
50. The pvalue of a test is the
smallest α at which the null hypothesis can be rejected.
largest α at which the null hypothesis can be rejected.
smallest α at which the null hypothesis cannot be rejected.
largest α at which the null hypothesis cannot be rejected.
51. The numerical quantity computed from the data that is used in deciding whether to reject H0 is the
significance level.
critical value.
test statistic.
parameter.
52. For a given level of significance, if the sample size increases, the probability of a Type II error will
remain the same.
increase.
decrease.
be equal to 1.0 regardless of α.
53.The power of a test is measured by its capability of
rejecting a null hypothesis that is true.
not rejecting a null hypothesis that is true.
rejecting a null hypothesis that is false.
not rejecting a null hypothesis that is false.
54. If the probability of committing a Type I error for a given test is decreased, then for a fixed sample size n, the probability of committing a Type II error will
decrease.
increase.
stay the same.
Not enough information to tell.
55. A robust estimator is one that is
unbiased and symmetrical about zero.
consistent and is also moundshaped.
efficient and less spread out.
not sensitive to moderate nonnormality.
56. For statistical inference about the mean of a single population when the population standard deviation is unknown, the degrees for freedom for the tdistribution equal n  1 because we lose one degree of freedom by using the
sample mean as an estimate of the population mean.
sample standard deviation as an estimate of the population standard deviation.
sample proportion as an estimate of the population proportion.
sample size as an estimate of the population size.
57. The degrees of freedom for the test statistic for μ when σ is unknown is
1
n
n  1
None of these choices.
58. The statistic (n  1)s2 / σ2 has a chisquared distribution with n  1 degrees of freedom if
the population is normally distributed with variance equal to σ2
he sample is normally distributed with variance equal to s2.
the sample has a Student tdistribution with degrees of freedom equal to n  1.
All of these choices are true.
59. Which of the following is an example illustrating the use of variance?
As a measure of risk.
As a judge of consistency.
To search for and reduce variability in a process.
All of these choices are true.
60. Which of the following conditions is needed regarding the chisquared test statistic for the test of variance?
The population random variable must be normal.
The test statistic must be a nonnegative number
The test statistic must have a chisquared distribution with n  1 degrees of freedom.
All of these choices are true.
61. Under what condition(s) does the test statistic for p have an approximate normal distribution?
When np > 5.
When np and np(1  p) are both > 5.
When n > 30.
When np and n(1  p) are both > 5.
62. In selecting the sample size to estimate the population proportion p, if we have no knowledge of even the approximate values of the sample proportion p? , we
take another sample and estimate p? .
we take two more samples and find the average of their p?
let p? = 0.50.
we let p? = 0.95.
63. When determining the sample size needed for a proportion for a given level of confidence and sampling error, the closer to 0.50 that p is estimated to be
the smaller the sample size required.
the larger the sample size required.
he sample size is not affected.
the effect cannot be determined from the information given.
64. Which of the following would be an appropriate null hypothesis?
The population proportion is equal to 0.60.
The sample proportion is equal to 0.60.
The population proportion is not equal to 0.60.
All of these choices are true.
65. The analysis of variance is a procedure that allows statisticians to compare two or more population
means.
proportions
variances.
standard deviations.
66. The distribution of the test statistic for analysis of variance is the
normal distribution.
Student tdistribution.
Fdistribution.
None of these choices
67. In oneway analysis of variance, betweentreatments variation is measured by the
SSE
SST
SS(total)
standard deviation.
68. When is the Tukey multiple comparison method used?
To test for normality.
To test equal variances.
To test for equality of a group of population means.
To test for differences in pairwise means.
69. In Fisher's least significant difference (LSD) multiple comparison method, the LSD value will be the same for all pairs of means if
all sample means are the same.
all sample sizes are the same.
all population means are the same.
None of these choices.
70. Fisher's least significant difference (LSD) multiple comparison method is flawed because
it will increase α; the probability of committing a Type I error.
it will increase β; the probability of committing a Type II error.
it will increase both α and β, the probabilities of committing Type I and Type II errors, respectively.
None of these choices.
71. When the objective is to compare more than two populations, the experimental design that is the counterpart of the matched pairs experiment is called a
completely randomized design.
oneway ANOVA design.
randomized block design.
None of these choices.
72. The primary interest of designing a randomized block experiment is to
reduce the variation among blocks.
increase the betweentreatments variation to more easily detect differences among the treatment means.
reduce the withintreatments variation to more easily detect differences among the treatment means
None of these choices.
73. A complete 3 x 2 factorial experiment is called balanced if
data is collected at all three levels of factor A.
data is collected at both levels of factor B.
the number of replicates is the same for each of the 6 treatments.
None of these choices.
74. In a twofactor ANOVA, there are 4 levels for factor A, 5 levels for factor B, and 3 observations for each combination of factor A and factor B levels. The number of treatments in this experiment equals
60
25
20
16
75. A tabular presentation that shows the outcome for each decision alternative under the various states of nature is called a
payback period matrix.
decision matrix.
decision tree.
payoff table.
76.Which of the following would be considered a state of nature for a business firm?
Inventory levels
Salaries for employees
Site for new plant
Worker safety laws
77. A payoff table lists the monetary values for each possible combination of the
mean and median.
mean and standard deviation.
event (state of nature) and act (alternative).
None of these choices.
78. Which of the following is true?
The process of determining the EMV decision is called the rollback technique.
We choose the act that produces the smallest expected opportunity loss (EOL).
The EMV decision is always the same as the EOL decision.
All of these choices are true.
79. Which of the following statements is false regarding the expected monetary value (EMV)?
To calculate the EMV, the probabilities of the states of nature must be already decided upon.
We choose the decision with the largest EMV.
In general, the expected monetary values represent possible payoffs.
None of these choices.
80. Which of the following statements is correct?
The EMV criterion selects the act with the largest expected monetary value.
The EOL criterion selects the act with the smallest expected opportunity loss.
The expected value of perfect information (EVPI) equals the smallest expected opportunity loss.
All of these choices are true.
81. The expected value of perfect information is the same as the
expected monetary value for the best alternative.
expected monetary value for the worst alternative.
expected opportunity loss for the best alternative.
expected opportunity loss for the worst alternative.
82. The expected value of sample information (EVSI) is the difference between
the posterior probabilities and the prior probabilities of the states of nature.
he expected payoff with perfect information (EPPI) and the expected monetary value for the best decision (EMV*).
the expected monetary value with additional information (EMV') and the expected monetary value for the best decision (EMV*).
the expected value of perfect information (EVPI) and the smallest expected opportunity loss (EOL*).
83. The procedure for revising probabilities based upon additional information is referred to as
utility theory.
Bernoulli's theorem.
central limit theorem.
Bayes' Law.
84. The difference between expected payoff under certainty and expected value of the best act without certainty is the
expected monetary value.
expected net present value.
expected value of perfect information.
expected rate of return.
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