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In this collection there will be a SAMPLE MULTIPLE CHOICE QUESTIONS to help math and pre_university students prepare for their exams

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1- Page

STATISTICS 8

CHAPTERS 1 TO 6, SAMPLE MULTIPLE CHOICE QUESTIONS

Correct answers are in bold italics.

This scenario applies to Questions 1 and 2:

A study was done to compare the lung capacity of

coal miners to the lung capacity of farm workers. The researcher studied 200 workers of each
type. Other factors that might affect lung capacity are smoking habits and exercise habits. The
smoking habits of the two worker types are similar, but the coal miners generally exercise less
than the farm workers.

1.

Which of the following is the explanatory variable in this study?
a.

Exercise

b.

Lung capacity

c.

Smoking or not

d.

Occupation

2.

Which of the following is a confounding variable in this study?

a.

Exercise

b.

Lung capacity

c.

Smoking or not

d.

Occupation

This scenario applies to Questions 3 to 5:

A randomized experiment was done by randomly

assigning each participant either to walk for half an hour three times a week or to sit quietly
reading a book for half an hour three times a week. At the end of a year the change in
participants' blood pressure over the year was measured, and the change was compared for the
two groups.

3.

This is a randomized experiment rather than an observational study because:
a.

Blood pressure was measured at the beginning and end of the study.

b.

The two groups were compared at the end of the study.

c.

The participants were randomly assigned to either walk or read, rather than choosing
their own activity.

d.

A random sample of participants was used.

4.

The two treatments in this study were:

a.

Walking for half an hour three times a week and reading a book for half an hour three
times a week.

b.

Having blood pressure measured at the beginning of the study and having blood pressure
measured at the end of the study.

c.

Walking or reading a book for half an hour three times a week and having blood pressure
measured.

d.

Walking or reading a book for half an hour three times a week and doing nothing.

2- Page

Scenario for Questions 3 to 5, continued

5.

If a statistically significant difference in blood pressure change at the end of a year for the
two activities was found, then:
a.

It cannot be concluded that the difference in activity

caused

a difference in the change in

blood pressure because in the course of a year there are lots of possible confounding
variables.

b.

Whether or not the difference was caused by the difference in activity depends on what
else the participants did during the year.

c.

It cannot be concluded that the difference in activity

caused

a difference in the change in

blood pressure because it might be the opposite, that people with high blood pressure
were more likely to read a book than to walk.

d.

It can be concluded that the difference in activity caused a difference in the change in
blood pressure because of the way the study was done.

6.

What is one of the distinctions between a population parameter and a sample statistic?
a.

A population parameter is only based on conceptual measurements, but a sample statistic
is based on a combination of real and conceptual measurements.

b.

A sample statistic changes each time you try to measure it, but a population parameter
remains fixed.

c.

A population parameter changes each time you try to measure it, but a sample statistic
remains fixed across samples.

d.

The true value of a sample statistic can never be known but the true value of a population
parameter can be known.

7.

A magazine printed a survey in its monthly issue and asked readers to fill it out and send it
in. Over 1000 readers did so. This type of sample is called
a.

a cluster sample.

b.

a self-selected sample.

c.

a stratified sample.

d.

a simple random sample.

8.

Which of the following would be most likely to produce selection bias in a survey?
a.

Using questions with biased wording.

b.

Only receiving responses from half of the people in the sample.

c.

Conducting interviews by telephone instead of in person.

d.

Using a random sample of students at a university to estimate the proportion of people
who think the legal drinking age should be lowered.

9.

Which one of the following variables is not categorical?

a.

Age of a person.

b.

Gender of a person: male or female.

c.

Choice on a test item: true or false.

d.

Marital status of a person (single, married, divorced, other)

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10.

A polling agency conducted a survey of 100 doctors on the question “Are you willing to treat
women patients with the recently approved pill RU-486”?  The conservative margin of error
associated with the 95% confidence interval for the percent who say 'yes' is
a. 50%

b. 10%

c. 5%          d. 2%

11.

Which one of these statistics is unaffected by outliers?
a.

Mean

b.

Interquartile range

c.

Standard deviation

d.

Range

12.

A list of 5 pulse rates is: 70, 64, 80, 74, 92. What is the median for this list?
a.

74

b. 76  c. 77  d. 80

13.

Which of the following would indicate that a dataset is not bell-shaped?
a.

The range is equal to 5 standard deviations.

b.

The range is larger than the interquartile range.

c.

The mean is much smaller than the median.

d.

There are no outliers.

14.

A scatter plot of number of teachers and number of people with college degrees for cities in
California reveals a positive association. The most likely explanation for this positive
association is:
a.

Teachers encourage people to get college degrees, so an increase in the number of
teachers is causing an increase in the number of people with college degrees.

b.

Larger cities tend to have both more teachers and more people with college degrees, so
the association is explained by a third variable, the size of the city.

c.

Teaching is a common profession for people with college degrees, so an increase in the
number of people with college degrees causes an increase in the number of teachers.

d.

Cities with higher incomes tend to have more teachers and more people going to college,
so income is a confounding variable, making causation between number of teachers and
number of people with college degrees difficult to prove.

15.

The value of a correlation is reported by a researcher to be

r

=

0.5. Which of the following

statements is correct?

a.

The x-variable explains 25% of the variability in the y-variable.

b.

The x-variable explains

25% of the variability in the

y

-variable.

c.

The x-variable explains 50% of the variability in the

y

-variable.

d.

The x-variable explains

50% of the variability in the

y

-variable.

16.

What is the effect of an outlier on the value of a correlation coefficient?
a.

An outlier will always decrease a correlation coefficient.

b.

An outlier will always increase a correlation coefficient.

c.

An outlier might either decrease or increase a correlation coefficient, depending on

where it is in relation to the other points.

d.

An outlier will have no effect on a correlation coefficient.

4- Page

17.

One use of a regression line is
a.

to determine if any x-values are outliers.

b.

to determine if any y-values are outliers.

c.

to determine if a change in x causes a change in y.

d.

to estimate the change in y for a one-unit change in x.

18.

Past data has shown that the regression line relating the final exam score and the midterm
exam score for students who take statistics from a certain professor is:

final exam

= 50 + 0.5

×

midterm

One interpretation of the slope is
a.

a student who scored 0 on the midterm would be predicted to score 50 on the final exam.

b.

a student who scored 0 on the final exam would be predicted to score 50 on the midterm
exam.

c.

a student who scored 10 points higher than another student on the midterm would be
predicted to score 5 points higher than the other student on the final exam.

d.

students only receive half as much credit (.5) for a correct answer on the final exam
compared to a correct answer on the midterm exam.

Questions 19 to 21:

A survey asked people how often they exceed speed limits. The data are

then categorized into the following contingency table of counts showing the relationship between
age group and response.

Exceed Limit if Possible?

Age Always Not

Always Total

Under 30

100 100 200

Over 30

40 160 200

Total

140 260 400

19.

Among people with age

over 30

, what's the "risk" of always exceeding the speed limit?

a.

0.20

b.

0.40

c.

0.33

d.

0.50

20.

Among people with age

under 30

what are the odds that they always exceed the speed limit?

a.

1 to 2

b.

2 to 1

c.

1 to 1

d.

50%

21.

What is the relative risk of always exceeding the speed limit for people under 30 compared to
people over 30?

a.

2.5

b.

0.4

c.

0.5

d.

30%

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Questions 22 and 23

: A newspaper article reported that "Children who routinely compete in

vigorous after-school sports on smoggy days are three times more likely to get asthma than their
non-athletic peers." (

Sacramento Bee

, Feb 1, 2002, p. A1)

22.

Of the following, which is the most important additional information that would be useful
before making a decision about participation in school sports?
a.

Where was the study conducted?

b.

How many students in the study participated in after-school sports?

c.

What is the baseline risk for getting asthma?

d.

Who funded the study?

23.

The newspaper also reported that "The number of children in the study who contracted
asthma was relatively small, 265 of 3,535." Which of the following is represented by
265/3535 = .075?

a.

The overall risk of getting asthma for the children in this study.

b.

The baseline risk of getting asthma for the “non-athletic peers” in the study.

c.

The risk of getting asthma for children in the study who participated in sports.

d.

The relative risk of getting asthma for children who routinely participate in vigorous
after-school sports on smoggy days and their non-athletic peers.

Questions 24 to 26:

The following histogram shows the distribution of the difference between

the actual and “ideal” weights for 119 female students.  Notice that percent is given on the
vertical axis. Ideal weights are responses to the question “What is your ideal weight”? The
difference = actual

ideal.  (

Source

idealwtwomen

dataset on CD.)

24.

What is the approximate shape of the distribution?
a.

Nearly symmetric.

b.

Skewed to the left.

c.

Skewed to the right.

d.

Bimodal (has more than one peak).

25.

The median of the distribution is approximately
a.

10 pounds.

b.

10 pounds.

c.

30 pounds.

d.

50 pounds.

6- Page

Scenario for Questions 24 to 26, continued

26.

Most of the women in this sample felt that their actual weight was
a.

about the same as their ideal weight.

b.

less than their ideal weight.

c.

greater than their ideal weight.

d.

no more than 2 pounds different from their ideal weight.

27.

A chi-square test of the relationship between personal perception of emotional health and
marital status led to rejection of the null hypothesis, indicating that there is a relationship
between these two variables.  One conclusion that can be drawn is:
a.

Marriage leads to better emotional health.

b.

Better emotional health leads to marriage.

c.

The more emotionally healthy someone is, the more likely they are to be married.

d.

There are likely to be confounding variables related to both emotional health and
marital status.

28.

A chi-square test involves a set of counts called “expected counts.” What are the expected
counts?
a.

Hypothetical counts that would occur of the alternative hypothesis were true.

b.

Hypothetical counts that would occur if the null hypothesis were true.

c.

The actual counts that did occur in the observed data.

d.

The long-run counts that would be expected if the observed counts are representative.

29.

Pick the choice that best completes the following sentence.  If a relationship between two
variables is called statistically significant, it means the investigators think the variables are

a.

related in the population represented by the sample.

b.

not related in the population represented by the sample.

c.

related in the sample due to chance alone.

d.

very important.

30.

a.

No baseline risk is given, so it is not know whether or not a high relative risk has
practical importance.

b.

A confounding variable rather than the explanatory variable is responsible for a change in
the response variable.

c.

The direction of the relationship between two variables changes when the categories of
a confounding variable are taken into account.

d.

The results of a test are statistically significant but are really due to chance.

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