Deck 8: Sampling Distributions and Hypothesis Testing

Question 1

In hypothesis testing our job would be much easier if

A) sample statistics accurately reflected population parameters.
B) subjects didn't vary so much from one another.
C) we knew the population values.
D) all of the above

Answer 1

all of the above

Question 2

To look at the sampling distribution of the mean we would

A) calculate a mean and compare it to the standard deviation.
B) calculate a mean and compare it to the standard error.
C) calculate many means and plot them.
D) look the sampling distribution up in a book.

Answer 2

calculate many means and plot them.

Question 3

The central feature of all hypothesis testing procedures is

A) the sample mean.
B) a sampling distribution.
C) a range of outcomes.
D) the type of experiment we run.

Answer 3

a sampling distribution.

Question 4

Which of the following is a statement of H ₁?

A) H ₁ : m > 0
B) H ₁ : m
C) H ₁ : m  ≠ 0
D) all of the above

Question 5

In testing hypotheses we have to take into account

A) sample means.
B) random variability.
C) differences from one set of data to another.
D) all of the above

Question 6

Another name for sampling error is

A) variability due to chance.
B) error variance.
C) constancy.
D) both a and b

Question 7

The sampling distribution of the mean that you saw in the text

A) resembled a normal distribution.
B) was very skewed.
C) had a mean that was unusually large relative to the population mean.
D) had little to do with the population mean.

Question 8

If we were to repeat an experiment a large number of times and calculate a statistic such as the mean for each experiment, the distribution of these statistics would be called

A) the distributional distribution
B) the error distribution.
C) the sampling distribution.
D) the test outcome.

Question 9

The hypothesis that we are trying to support by running an experiment is often called

A) the null hypothesis.
B) the test hypothesis.
C) the sample hypothesis.
D) the research hypothesis.

Question 10

The basic reason for running an experiment is usually to

A) reject the null hypothesis.
B) reject the experimental hypothesis.
C) reject the research hypothesis.
D) find a non-significant difference.

Question 11

We are more likely to declare two populations to be different if

A) the means of our samples are very different.
B) the variability of our samples is very large.
C) the samples are normally distributed.
D) all of the above

Question 12

If I calculate the probability of obtaining a particular outcome when the null hypothesis is true, I must deal with

A) the outcome.
B) a sampling distribution.
C) conditional probability.
D) all of the above

Question 13

If the data are reasonably consistent with the null hypothesis, we are likely to

A) accept the alternative hypothesis.
B) reject the null hypothesis.
C) retain the null hypothesis.
D) accept the null hypothesis.

Question 14

One of the problems we face when we try to draw conclusions from data is that we have to deal with

A) means.
B) error variance.
C) population size.
D) hypotheses.

Question 15

Which of the following is most likely to represent a statement of the null hypothesis?

A) H ₀ : m > 0
B) H ₀ : m
C) H ₀ : m ≠ 0
D) H ₀ : m = 0

Question 16

The standard deviation of a sampling distribution is known as

A) the standard error.
B) the variance.
C) error.
D) the sampling deviation.

Question 17

Whether or not we reject the null hypothesis depends on

A) the probability of the result given the null hypothesis is true.
B) how far the data depart from what we would expect if the null hypothesis were true.
C) the size of some test statistic.
D) all of the above

Question 18

Sampling distributions help us test hypotheses about means by

A) telling us exactly what the population mean is.
B) telling us how variable the population is.
C) telling us what kinds of means to expect if the null hypothesis is true.
D) telling us what kinds of means to expect if the null hypothesis is false.

Question 19

Hypothesis testing is necessarily part of

A) descriptive statistics.
B) order statistics.
C) test construction statistics.
D) inferential statistics.

Question 20

The basic idea behind hypothesis testing

A) depends on the kind of test you want to run.
B) has little to do with whatever data you collect.
C) is largely the same across a wide variety of procedures.
D) is important only if you want to compare two populations.

Question 21

The null hypothesis is the statement that

A) population means are equal.
B) population means differ between groups.
C) it is the hypothesis you generally hope to prove.
D) exciting things are going on.

Question 22

A two-tailed test is _______ powerful than a one-tailed test if we are sure the difference is in the direction that we would have predicted.

A) more
B) less
C) equally
D) We cannot tell.

Question 23

Sometimes we reject the null hypothesis when it is true. This is technically referred to as

A) a Type I error.
B) a Type II error.
C) a mistake.
D) good fortune.

Question 24

When we are willing to reject the null hypothesis for any extreme outcome, we are making a

A) two-tailed test.
B) one-tailed test.
C) singular test.
D) omnibus test.

Question 25

Which of the following pairings is correct?

A) Type I; Type II:: a ; b
B) Type I; Type II :: b ; a
C) Type I; Type II :: 1- a ; 1- b
D) Type I; Type II :: a ; 1- b

Question 26

We are most likely to reject a null hypothesis if the test statistic we compute is

A) very small.
B) quite extreme.
C) what we would expect if the null hypothesis were true.
D) equal to the number of observations in the sample.

Question 27

The area that encompasses the extreme 5% of a distribution is frequently referred to as

A) the retention region.
B) the rejection region
C) the decision region.
D) none of the above

Question 28

In the finger tapping example in the text, we would reject the null hypothesis when

A) the patient tapped too quickly.
B) the patient tapped too slowly.
C) the patient tapped either very quickly or very slowly.
D) We would be unlikely to ever reject the null hypothesis.

Question 29

To reject a null hypothesis for the finger tapping example in the text, we would

A) calculate the probability of that result if the null hypothesis were false.
B) calculate the probability of that result if the null hypothesis were true.
C) compare the probabilities of that result if the null hypothesis were true and if it were false.
D) reject the null hypothesis unless that subject closely resembled normal subjects.

Question 30

A Type II error refers to

A) rejecting a true null hypothesis.
B) rejecting a false null hypothesis.
C) failing to reject a true null hypothesis.
D) failing to reject a false null hypothesis.

Question 31

Another name for a one-tailed test is a

A) directional test.
B) non-directional test.
C) uniform test.
D) specific test.

Question 32

The difference between a test comparing two means and a test comparing the frequency of two outcomes is

A) the test statistics that they employ and their calculation.
B) the logic behind the two different hypothesis testing procedures.
C) the way we go about drawing conclusions from the tests.
D) all of the above

Question 33

Dr. Harmon expected that her neurotic patients would come significantly earlier to all scheduled appointments compared to other patients, and planned to run a one-tailed test to see if their arrival times were much earlier. Unfortunately, she found the opposite result: the neurotic patients came to appointments later than other patients. What can Dr. Harmon conclude from her one-tailed test?

A) Neurotic patients came to appointments significantly later than other patients.
B) Neurotic patients came to appointments significantly earlier than other patients.
C) Non-neurotic patients came to appointments significantly earlier than neurotic patients.
D) Neurotic patients did not come to appointments significantly earlier than other patients.

Question 34

If we erroneously conclude that motorists are more likely to honk at low status cars than high status cars, we

A) have made a Type I error.
B) have made a Type II error.
C) would have made that conclusion 5% of the time if the null hypothesis were true.
D) both a and c

Question 35

What is a major advantage of using null hypotheses?

A) The null hypothesis gives us a starting point.
B) If the null hypothesis is false, that provides evidence for an alternative hypothesis.
C) We have procedures for testing null hypotheses.
D) all of the above

Question 36

A researcher was interested in seeing if males or females in large lecture classes fell asleep more during in-class videos. The null hypothesis of this study is

A) males will fall asleep more than females.
B) females will fall asleep more than males.
C) males and females fall asleep at the same rate.
D) More information is needed.

Question 37

We would like to

A) maximize the power of a test.
B) minimize the probability of a Type I error.
C) do both a and b
D) maximize the probability of a Type II error.

Question 38

The value of the test statistic that would lead us to reject the null hypothesis is called

A) the critical value.
B) the test value.
C) the rejection value.
D) the acceptance value.

Question 39

Most psychological research is undertaken with the hope of

A) proving the null hypothesis.
B) proving the alternative hypothesis.
C) rejecting the null hypothesis.
D) discovering ultimate truth.

Question 40

By convention, we often reject the null hypothesis if the probability of our result, given that the null hypothesis were true, is

A) greater than .95.
B) less than .05.
C) greater than .05.
D) either b or c

Question 41

A null hypothesis is rejected when

A) the differences are due to sampling error.
B) the probability of finding a difference that large if the population means are equal is very low.
C) the probability of finding a difference that large if the population means are equal is very high.
D) the distribution is not normal.

Question 42

When testing a hypothesis, we normally retain the null hypothesis when the test statistic is smaller than the critical value.

Question 43

Rejecting a true null hypothesis is known as

A) Type II Error
B) Type I Error
C) alpha ( a )
D) both b and c

Question 44

A Type I error has occurred if we

A) reject a null hypothesis that is really false.
B) retain a null hypothesis that is really false.
C) retain a null hypothesis that is really true.
D) reject a null hypothesis that is really true.

Question 45

Type I error is rejecting the null hypothesis when it is true.

Question 46

If the alternative hypothesis in a study is H₀ > 0, a one-tailed test is called for.

Question 47

Power is the probability of making a Type II error.

Question 48

When the direction of difference between the sample mean and the population mean is not specified, a two-tailed test is appropriate.

Question 49

Type II error is retaining the null hypothesis when it is true.

Question 50

After running a t-test on the mean numbers of jelly beans that men and women eat over the course of the year, I conclude that men eat significantly more jelly beans than women. If men and women actually eat the same number of jelly beans, my conclusion is

A) a valid conclusion
B) a Type I error
C) a Type II error
D) an example of power

Question 51

The _______ assumes all means are equal for a given measure?

A) alternative hypothesis
B) random hypothesis
C) predicted hypothesis
D) null hypothesis

Question 52

Alpha is the probability of making a Type I error.

Question 53

The probability of NOT rejecting a null hypothesis when it is false is called?

A) a Type I error
B) a Type II error
C) experimenter error
D) method error

Question 54

If .05 is the rejection level, we would reject the null hypothesis if the probability of the test statistic, given that the null hypothesis is true, was .07.

Question 55

Another name for sampling error is

A) variability due to chance.
B) error variance.
C) constancy.
D) both a and b

Question 56

A child psychologist is interested in determining if a new type of cognitive therapy will reduce behavior problems among children with ADHD more than Ritalin will in another group of children with ADHD.
a. Write an appropriate null hypothesis.
b. Write an appropriate research hypothesis.

Question 57

A Type I error concerns

A) the probability of rejecting a true null hypothesis.
B) the probability of rejecting a false null hypothesis.
C) the probability of not rejecting a true null hypothesis.
D) the probability of not rejecting a false null hypothesis.

Question 58

The probability of NOT rejecting a FALSE null hypothesis is also known as

A) Type II Error
B) Type I Error
C) alpha ( a )
D) both b and c

Question 59

The probability of making a Type I error is unrelated to the probability of making a Type II error.

Question 60

A standard error is the value of a statistic at or beyond which the null hypothesis is rejected.

Question 61

Given the following hypotheses, is a one-tailed or two-tailed test more appropriate?
a. H₀: m = 5, H₁: m ≠ 5
b. H₀: m = 0, H₁: m > 0
c. H₀: m = 100, H₁: m

Question 62

A research article stated that there was a mean difference in depressive symptoms between male and female clients. The p value was .075. What does this mean?

Question 63

Explain how a critical value is used to test hypotheses.

Question 64

Another student concluded that James was in the study skills class based on his exam score, but in fact he was not. What type of error did the student make?

Question 65

A researcher has calculated power as .40.
a. What does this mean?
b. What is the probability that this researcher will make a Type II error if the null hypothesis is false? Explain.

Question 66

Give an example of a hypothesis that would be appropriate for testing with a two-tailed test.

Question 67

Give an example of a hypothesis that would be appropriate for testing with a one-tailed test.

Question 68

The average test score of individuals in the study skills group is 80 and the standard deviation is 7.5. Jessica got a 65. Do you think Jessica was in the study skills group? Explain.

Question 69

Given the following p values, would you reject or retain the null hypothesis if you want to be 95% confident that you are not making a Type I error.
a. p = .05
b. p = 1.0
c. p = .10
d. p = .025
e. p = .075