# Jeopardy Final Exam - Part 2 without answers

```Linear
Regression
Linear
Regression II
Probability I
Probability II
Inference
200
200
200
200
200
400
400
400
400
400
600
600
600
600
600
800
800
800
800
800
1000 1000 1000 1000 1000
Linear Regression – 200
Here is a graph of the percent of
adults in each state who were
obese in 1991 and the percent
who were obese in 1998. What
graph?
A.
B.
C.
D.
Positive, linear, moderate
Positive, linear, strong
Positive, linear, weak
Random, linear, moderate
Linear Regression - 400
Given the scatterplot shown below,
the correlation between X and Y is
probably closest to:
A.
B.
C.
D.
–1.3
0.55
0.99
1.3
Linear Regression - 600
A newscaster read a study comparing the amount of time spent
cleaning and weight of the homeowner. The study reported a
correlation of –0.87. She then reported on the evening news that the
more time you spend cleaning your house the skinner you will get.
Which of the following is true?
A. She is incorrect since the correlation is negative which shows no
relationship between the two variables.
B. She is correct since –0.87 shows a strong relationship between the
variables.
C. The study must be incorrect because the correlation should be
positive.
D. She is incorrect because she is confusing association with
causation.
Linear Regression - 800
The least-squares regression line for predicting the percent of a
country's females who are illiterate from the percent of males
who are illiterate is female% = 3.34 + 1.39(male%).
Daily
Double!
In China, 10.1% of men are illiterate. Predict the percent of
illiterate women in China.
A. 4.7%
B. 14%
C. 17.4%
D. 47.8%
Linear Regression - 1000
The least-squares regression line for predicting the percent of a
country's females who are illiterate from the percent of males
who are illiterate is female% = 3.34 + 1.39(male%).
The equation of the regression line tells us that (on
average) when the male illiteracy rate goes up by 1%, the
female rate goes up by
A. 4.73%
B. 3.34%
C. 1.95%
D. 1.39%
Linear Regression II - 200
You are planning an experiment to study the effect
of gasoline octane value on the gas mileage (miles
per gallon) of sport utility vehicles. In this study
A. gas mileage is a response variable.
B. gas mileage is an explanatory variable.
C. gas mileage is a lurking variable.
D. gas mileage is a categorical variable.
Linear Regression II - 400
Suppose that the least squares regression line for
predicting y from x is y = 100 + 1.3x. Which of the
following is a possible value for the correlation between y
and x?
A. 1.3
B. 1.3
C. 0
D. 0.5
E. 0.5
Linear Regression II - 600
Which of these is not true of the correlation r between the
length (in inches) and weight (in pounds) of a sample of
salamanders?
A. r must take a value between -1 and 1.
B. r is measured in inches.
C. if longer salamanders tend to also be heavier, then r &gt;
0.
D. r would not change if we measured these trout in
Linear Regression II - 800
A study found that SAT verbal scores were positively associated with
first-year grade point averages for liberal arts majors. We can conclude
from this that
A. students who scored high on the SAT verbal test tended to get lower
GPAs than those who scored lower on the SAT verbal test
B. students who scored high on the SAT verbal test tended to get
higher GPAs than those who scored lower on the SAT verbal test
C. we can use the SAT verbal score to accurately predict GPAs for
liberal arts majors
D. grade point averages are higher for older students
E. the correlation between the SAT verbal score and GPA is higher
than 0.5
Linear Regression II - 1000
A scatterplot has a correlation of –0.0002. Which of the
following must be true?
A. There is no association between the explanatory and
response variables
B. The scatterplot has no form
C. The scatterplot shows a negative direction
D. There is no linear association between the explanatory
and response variables
Probability I – 200
Color
Frequency
Red
Blue
Green
Yellow
Purple
15
19
26
5
15
A student spun a given spinner 80 times and recorded the
results of each spin in the table. Based on his findings
what is the probability of landing on Red?
A.
B.
C.
D.
0.1500
0.1875
0.8000
0.2000
Probability I - 400
Color
Frequency
Red
Blue
Green
Yellow
Purple
15
19
26
5
15
A student spun a given spinner 80 times and recorded the
results of each spin in the table. What is the probability of
not landing on Yellow?
A.
B.
C.
D.
0.0625
0.2000
0.8000
0.9375
Probability I - 600
Of American adults 24% have a genetic marker for
breast cancer. If a random sample of 3 adults is
taken, what is the probability that all 3 have the
genetic marker?
A.
B.
C.
D.
0.2400
0.7200
0.0138
0.0800
Probability I - 800
A fair die is rolled 4 times and 6 appears each time.
What is the probability that on the next roll the 6 will
appear again?
A.It would be close to zeros since it is very unlikely
that 6 would appear again after coming up so many
times.
B.It would be close to one since the die appears to be
on a streak of 6's
C.The probability remains 1/6
D.The probability would be (1/6)5 = 1/7776
Probability I - 1000
I
x
8
15
16
19
22
28
II
P(x)
0.35
0.20
0.15
0.06
0.14
0.10
x
-8
-2
0
1
6
12
IIII
P(x)
0.08
0.00
0.18
0.68
0.01
0.05
x
18
22
29
56
66
115
P(x)
0.22
0.22
0.22
0.25
0.11
0.08
Which of the following is a legitimate probability distribution?
A. I only
B. II only
C. III only
D. I and II
Probability II - 200
Let the table above give the probabilities for having a
certain number of children for a given town. What is the
expected number of children per family?
A.
B.
C.
D.
1.0
1.3
2.0
2.5
Probability II - 400
Male Female
Total
Smokes
6
14
20
Doesn’t
Smoke
34
46
80
Total
40
60
100
The table relates gender to smoking. What is
the probability that a randomly selected person
smokes or is male?
A.0.20
B. 0.40
C. 0.54
D. 0.60
Probability II - 600
Male Female
Total
Smokes
6
14
20
Doesn’t
Smoke
34
46
80
Total
40
60
100
The table relates gender to smoking. What is
the probability that a randomly selected person
smokes and is male?
A.0.06
B. 0.20
C. 0.40
D. 1.00
Probability II - 800
each of the four players is dealt exactly one ace is about
0.11. To simulate an outcome with probability 0.11 you could
A. look at 2 digits in the random number table; the outcome
occurs if the digits are 11.
B. look at 2 digits in the random number table; the outcome
occurs if the digits are any of 00, 01, …, 11.
C. look at 2 digits in the random number table; the outcome
occurs if the digits are any of 00, 01, …, 10.
D. None of these would work.
Probability II - 1000
In a small community 76% of the population is
over 35 years old, 72% of the population
consider themselves conservatives, and 52% are
over 35 and conservative. What is the probability
that a randomly selected person is over 35 or
conservative? HINT: Make a two-way table.
Daily
Double!
A. 52%
B. 96%
C. 8%
D. 148%
Significance Tests - 200
The teacher wants to perform a test of significance
to see if her students underestimate her actual age
of 50. She samples the 30 students and
calculates an average of 46.5. The null and
alternative hypotheses are:
A.H0:  = 46.5; Ha:   46.5
B.H0:  = 46.5; Ha:  &lt; 46.5
C.H0:  = 50; Ha:  &lt; 50
D.H0:  = 50; Ha:   50
Significance Tests - 400
A CBS News/New York Times opinion poll asked 1,190
adults whether they would prefer balancing the Federal
budget over cutting taxes; 702 of those asked said &quot;Yes.&quot;
Which of these is a correct 95% confidence interval for the
proportion of all adults who prefer balancing the budget
over cutting taxes?
A. 0.59  0.0004
B. 0.59  0.014
C. 0.59  0.018
D. 0.59  0.028
Significance Tests - 600
A Census Bureau report on the income of Americans says that with
95% confidence the median income of all U.S. households in 1997 was
\$37,005 with a margin of error of \$342. This means that
A. 95% of all households had incomes in the range \$37,005 \$342.
B. we can be 95% sure that the median income for all households in
the country lies in the range \$37,005  \$342.
C. 95% of the households in the sample interviewed by the Census
Bureau had incomes in the range \$37,005  \$342.
D. the Census Bureau got the result \$37,005  \$342 using a method
that will cover the true median income 95% of the time when used
repeatedly.
Significance Tests - 800
If a significance test gives P-value 0.005,
A. the margin of error is 0.005.
B. the null hypothesis is very likely to be true.
C. we do not have good evidence against the null
hypothesis.
D. we do have good evidence against the null
hypothesis.
Significance Tests - 1000
A high school football coach claims the average weight of his players
is 230 lbs. You suspect he may be wrong, and take a sample of 18
players and get a mean weight of 228 lbs. with a standard deviation of
4 lbs. What would your conclusion be if you ran a hypothesis test with
 = 0.05?
A. Since our p-value is less than 0.05, we would reject the coach’s
claim.
B. Since our p-value is less than 0.05, we would not reject the coach’s
claim.
C. Since our p-value is greater than 0.05, we would reject the coach’s
claim.
D. Since our p-value is greater than 0.05, we would not reject the
coach’s claim.
Final
Jeopardy!
on this category:
Linear
Regression
a piece of paper.
And now, the Final
Linear Regression
Suppose you run a linear regression for
a data set and get r = 0.92. You then
graph the residuals vs. the x-variable.
The plot is shown on the right. What
would be an appropriate interpretation
of the residual plot?
A. Since the plot has a distinct curve to it, and since r = 0.92, the
linear model is a good fit.
B. Since the plot has a distinct curve to it, and since r = 0.92, the
linear model is not a good fit.
C. The shape of the residual plot doesn’t matter; since r = 0.92, the
linear model is the best one.
D. Since the plot has a distinct curve, the linear model is not the best
model for the data, even though r = 0.92.
```