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Peregrine Modules > Quantitative Research Techniques and Statistics > Flashcards

Quantitative Research Techniques and Statistics Flashcards

1
Q

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?

A

Inferential statistics

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2
Q

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

A

sample.

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3
Q

A summary measure that is computed from a population is called a

A

parameter.

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4
Q

Which of the following is a measure of the reliability of a statistical inference?

A

A significance level.

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5
Q

The process of using sample statistics to draw conclusions about population parameters is called

A

doing inferential statistics.

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6
Q

Which of the following represents a population, as opposed to a sample?

A

All registered voters in the State of Michigan.

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7
Q

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

A

the 500 adult pine trees selected at random selected at random from this forest.

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8
Q

The significance level of a statistical inference measures

A

the proportion of times a conclusion about a population will be wrong in the long run.

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9
Q

The confidence level of a statistical inference measures

A

the proportion of times an estimation procedure will be correct in the long run.

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10
Q

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?

A

A survey.

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11
Q

Which of the following statements is true regarding the design of a good survey?

A

All of these choices are true.

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12
Q

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?

A

Direct observation.

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13
Q

The difference between a sample mean and the population mean is called

A

sampling error.

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14
Q

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

A

stratified random sample.

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15
Q

When every possible sample with the same number of observations is equally likely to be chosen, the result is called a

A

simple random sample.

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16
Q

Which of the following types of samples is almost always biased?

A

Self-selected samples.

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17
Q

Which of the following is an example of a nonsampling error?

A

All of these choices are true.

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18
Q

Which of the following situations lends itself to cluster samples?

A

All of these choices are true.

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19
Q

Which of the following causes sampling error?

A

Taking a random sample from a population instead of studying the entire population.

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20
Q

Which of the following describes selection bias?

A

Some members of the target population are excluded from possible selection for the sample.

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21
Q

An approach of assigning probabilities which assumes that all outcomes of the experiment are equally likely is referred to as the

A

classical approach.

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22
Q

The collection of all possible outcomes of an experiment is called

A

a sample space.

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23
Q

If event A and event B cannot occur at the same time, then A and B are said to be

A

mutually exclusive.

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24
Q

Which of the following best describes the concept of marginal probability?

A

It is a measure of the likelihood that a particular event will occur, regardless of whether another event occurs.

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25
Q

The intersection of events A and B is the event that occurs when

A

both A and B occur.

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26
Q

If the outcome of event A is not affected by event B, then events A and B are said to be

A

independent.

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27
Q

If the outcome of event A is not affected by event B, then events A and B are said to be

A

independent.

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28
Q

Suppose P(A) = 0.35. The probability of the complement of A is

A

0.65.

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29
Q

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

A

0.12.

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30
Q

If A and B are mutually exclusive events with P(A) = 0.30 and P(B)=0.40, then P(A or B) is

A0.10.

B0.12.

C0.70.

DNone of these choices.

A

0.70.

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31
Q

Bayes’ Law is used to compute

A

posterior probabilities.

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32
Q

Initial estimates of the probabilities of events are known as

A

prior probabilities.

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33
Q

The standard deviation of the sampling distribution of x̄ is also called the

A

standard error of the sample mean.

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34
Q

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

A

is approximately normal if n > 30.

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35
Q

If all possible samples of size n are drawn from a population, the probability distribution of the sample mean x̄ is called

A

the sampling distribution of x̄

36
Q

Sampling distributions describe the distributions of

A

sample statistics.

37
Q

Suppose X has a distribution that is not normal. The Central Limit Theorem is important in this case because

A

it says the sampling distribution of x̄ is approximately normal if n is large enough.

38
Q

As a general rule, the normal distribution is used to approximate the sampling distribution of the sample proportion only if

A

np and n(1 - p) are both greater than or equal to 5.

39
Q

The standard deviation of p̂ is also called the

A

standard error of the sample proportion.

40
Q

If two populations are normally distributed, the sampling distribution of the difference in the sample means, x̄1 – x̄2 is

A

exactly normal for any sample sizes.

41
Q

If two random samples of sizes n1 and n2 are selected independently from two populations with means μ1 and μ2, then the mean of x̄1 - x̄2 equals

A

μ1 - μ2

42
Q

If two random samples of sizes n1 and n2 are selected independently from two non-normally distributed populations, then the sampling distribution of the sample mean difference, x̄1- x̄2

A

is approximately normal only if n1 and n2 are both larger than or equal to 30.

43
Q

The standard deviation of x̄1 - x̄2 is also called the

A

standard deviation of the difference between the population means.

44
Q

The hypothesis of most interest to the researcher is

A

the alternative hypothesis.

45
Q

A Type I error occurs when we

A

reject a true null hypothesis.

46
Q

A Type II error is defined as

A

not rejecting a false null hypothesis.

47
Q

Which of the following probabilities is equal to the significance level α?

A

Probability of making a Type I error.

48
Q

If we reject the null hypothesis, we conclude that

A

there is enough statistical evidence to infer that the alternative hypothesis is true.

49
Q

Statisticians can translate p-values into several descriptive terms. Suppose you typically reject H0 at level 0.05. Which of the following statements is correct?

A

All of these choices are true.

50
Q

The p-value of a test is the

A

smallest α at which the null hypothesis can be rejected.

51
Q

The numerical quantity computed from the data that is used in deciding whether to reject H0 is the

A

test statistic.

52
Q

For a given level of significance, if the sample size increases, the probability of a Type II error will

A

decrease.

53
Q

The power of a test is measured by its capability of

A

rejecting a null hypothesis that is false.

54
Q

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

A

increase.

55
Q

A robust estimator is one that is

A

not sensitive to moderate nonnormality.

56
Q

For statistical inference about the mean of a single population when the population standard deviation is unknown, the degrees for freedom for the t-distribution equal n - 1 because we lose one degree of freedom by using the

A

sample mean as an estimate of the population mean.

57
Q

The degrees of freedom for the test statistic for μ when σ is unknown is

A

n - 1

58
Q

The statistic (n - 1)s2 / σ2 has a chi-squared distribution with n - 1 degrees of freedom if

A

the population is normally distributed with variance equal to σ2

59
Q

Which of the following is an example illustrating the use of variance?

A

All of these choices are true.

60
Q

Which of the following conditions is needed regarding the chi-squared test statistic for the test of variance?

AThe population random variable must be normal.

BThe test statistic must be a non-negative number.

CThe test statistic must have a chi-squared distribution with n - 1 degrees of freedom.

DAll of these choices are true.

A

All of these choices are true.

61
Q

Under what condition(s) does the test statistic for p have an approximate normal distribution?

A

Under what condition(s) does the test statistic for p have an approximate normal distribution?

62
Q

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 p̂ , we

A

let p̂ = 0.50.

63
Q

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

A

the larger the sample size required.

64
Q

Which of the following would be an appropriate null hypothesis?

A

The population proportion is equal to 0.60.

65
Q

The analysis of variance is a procedure that allows statisticians to compare two or more population

A

means.

66
Q

The distribution of the test statistic for analysis of variance is the

A

F-distribution.

67
Q

In one-way analysis of variance, between-treatments variation is measured by the

A

SST

68
Q

When is the Tukey multiple comparison method used?

A

To test for differences in pairwise means.

69
Q

In Fisher’s least significant difference (LSD) multiple comparison method, the LSD value will be the same for all pairs of means if

A

all sample sizes are the same.

70
Q

Fisher’s least significant difference (LSD) multiple comparison method is flawed because

A

it will increase α; the probability of committing a Type I error.

71
Q

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

A

randomized block design.

72
Q

The primary interest of designing a randomized block experiment is to

A

reduce the within-treatments variation to more easily detect differences among the treatment means.

73
Q

A complete 3 x 2 factorial experiment is called balanced if

A

the number of replicates is the same for each of the 6 treatments.

74
Q

In a two-factor 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

A

20

75
Q

A tabular presentation that shows the outcome for each decision alternative under the various states of nature is called a

A

payoff table.

76
Q

Which of the following would be considered a state of nature for a business firm?

A

Worker safety laws

77
Q

A payoff table lists the monetary values for each possible combination of the

A

event (state of nature) and act (alternative).

78
Q

Which of the following is true?

A

All of these choices are true.

79
Q

Which of the following statements is false regarding the expected monetary value (EMV)?

A

In general, the expected monetary values represent possible payoffs.

80
Q

Which of the following statements is correct?

A

AThe EMV criterion selects the act with the largest expected monetary value.

BThe EOL criterion selects the act with the smallest expected opportunity loss.

CThe expected value of perfect information (EVPI) equals the smallest expected opportunity loss.

DAll of these choices are true.

81
Q

The expected value of perfect information is the same as the

A

expected opportunity loss for the best alternative.

82
Q

The expected value of sample information (EVSI) is the difference between

A

the expected monetary value with additional information (EMV’) and the expected monetary value for the best decision (EMV*).

83
Q

The procedure for revising probabilities based upon additional information is referred to as

A

Bayes’ Law.

84
Q

The difference between expected payoff under certainty and expected value of the best act without certainty is the

Aexpected monetary value.

Bexpected net present value.

Cexpected value of perfect information.

Dexpected rate of return.

A

expected value of perfect information.

85
Q
A

Peregrine Modules (3 decks)

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