Organizations Biggest 20-Year Challenges

Points: 250
Assignment 3:Biggest Challenges Facing Organizations in the
Next 20 Years
Criteria
Unacceptable
Below 60% F
Meets Minimum Expectations
60-69% D
Fair
70-79% C
Proficient
80-89% B
Exemplary
90-100% A
1. Provide a title slide followed by a slide with an introduction
to your presentation.
Weight: 5%
Did not submit or incompletely provided a title slide followed
by a slide with an introduction to your presentation.
Insufficiently provided a title slide followed by a slide with an
introduction to your presentation.
Partially provided a title slide followed by a slide with an
Satisfactorily provided a title slide followed by a slide with an
Thoroughly provided a title slide followed by a slide with an
2. Presentation should include your choice of the five (5)
challenges you believe organizations will face in the next
twenty (20) years. Only include one (1) challenge and your

explanation for choosing that challenge per slide for a total of
five (5) slides. Weight: 50%
Did not submit or incompletely included your choice of the five
(5) challenges you believe organizations will face in the next
twenty (20) years. Did not submit or incompletely included one
(1) challenge and your explanation for choosing that challenge
per slide for a total of five (5) slides.
Insufficiently included your choice of the five (5) challenges
you believe organizations will face in the next twenty (20)
years. Insufficiently included one (1) challenge and your
five (5) slides.
Partially included your choice of the five (5) challenges you
believe organizations will face in the next twenty (20) years.
Partially included one (1) challenge and your explanation for
choosing that challenge per slide for a total of five (5) slides.
Satisfactorily included your choice of the five (5) challenges
you believe organizations will face in the next twenty (20)
years. Satisfactorily included one (1) challenge and your
five (5) slides.
Thoroughly included your choice of the five (5) challenges you
believe organizations will face in the next twenty (20) years.
Satisfactorily included one (1) challenge and your explanation
for choosing that challenge per slide for a total of five (5)
slides.
3. Provide one (1) summary slide which addresses key points of
your paper.
Weight: 5%
Did not submit or incompletely provided one (1) summary slide
which addresses key points of your paper.
Insufficiently provided one (1) summary slide which addresses
key points of your paper.
Partially provided one (1) summary slide which addresses key
points of your paper.
Satisfactorily provided one (1) summary slide which addresses

Thoroughly provided one (1) summary slide which addresses
4. Narrate each slide, using a microphone, indicating what you
would say if you were actually presenting in front of an
audience. Weight: 30%
Did not submit or incompletely narrated each slide, using a
microphone, indicating what you would say if you were actually
presenting in front of an audience.
Insufficiently narrated each slide, using a microphone,
indicating what you would say if you were actually presenting
in front of an audience.
Partially narrated each slide, using a microphone, indicating
what you would say if you were actually presenting in front of
an audience.
Satisfactorily narrated each slide, using a microphone,
indicating what you would say if you were actually presenting
in front of an audience.
Thoroughly narrated each slide, using a microphone, indicating
what you would say if you were actually presenting in front of
an audience.
5. Clarity, writing mechanics, and formatting requirements.
Weight: 10%
More than 8 errors present
7-8 errors present
5-6 errors present
3-4 errors present
0-2 errors present
Chs 1 – 3
1. A type of variable where arithmetic operations do not make

sense are called _______.
A) quantitative
B) categorical
C) distributions
D) cases
2. When using a pie chart, the sum of all the percentages
should be _____.
A) 0
B) 1
C) 100
D) 50
3. What method is useful when comparing two distributions
using a stemplot?
A) Splitting the stem
B) Trimming the leaves
C) Back-to-back stemplots
D) None of the above
4. The histogram at right shows data from 30 students who
were asked,
“How much time do you spend on the Internet in minutes?”
What are
some features about the data?
A) There is a potential outlier.
B) Most values are around 800.
C) The range of values is between 0 and 400.

5. In a statistics class with 136 students, the professor records
how
much money each student has in their possession during the
first
class of the semester. The histogram shown below represents the
data he collected. What is approximately the percentage of
students with under $10 in their possession?
A) 35%
B) 40%
C) 44%
D) 50%
6. A study is being conducted on air quality at a small college
in the
South. As part of this study, monitors were posted at every
entrance to this college from 6:00 a.m. to 10:00 p.m. on a
randomly
chosen day. The monitors recorded the mode of transportation
used
by each person as they entered the campus. Based on the
information recorded, the following bar graph was constructed.
Approximately what percentage of people entering campus on
this
particular day arrived by car?
A) 9%
B) 31%
C) 53%
D) 62%

7. The Insurance Institute for Highway Safety publishes data on
the total damage suffered by compact
automobiles in a series of controlled, low-speed collisions. The
cost for a sample of nine cars, in
hundreds of dollars, is provided below
10 6 8 10 4 3.5 7.5 8 9
What is the median cost of the total damage suffered for this
sample of cars?
A) $400 B) $730 C) $800 D) $1000
8. What is the interquartile range of the above data?
A) $300 B) $350 C) $400 D) $450
9. In a statistics class with 136 students, the professor records
how much
money each student has in their possession during the first class
of the
semester. The histogram shown below represents the data he
collected.
From the histogram, which of the following is true?
A) The mean is larger than the median.
B) The mean is smaller than the median.
C) The mean and median are approximately equal.
D) It is impossible to compare the mean and median for these
data.

10. The following boxplot is of the birth weights (in ounces) of
160 infants born
in a local hospital. About 40 of the birth weights were below
A) 92 ounces
B) 102 ounces
C) 112 ounces
D) 122 ounces
11. This is a standard deviation contest. Which of the following
sets of four
numbers has the largest possible standard deviation?
A) 7, 8, 9, 10
B) 5, 5, 5, 5
C) 0, 0, 10, 10
D) 0, 1, 2, 3
12. Agricultural fairs often hold competitions for produce
grown by local gardeners. The following data
are the weight (in pounds) of tomatoes entered into an annual
fair in Roland, Manitoba, Canada, in
2007.
2.48, 1.52, 1.15, 1.13, 1.00, 0.99, 0.96, 0.94, 0.75
Apply the 1.5 ×IQR rule to the data to check for outlier values.

In this case,
A) there are no outliers
B) the value 0.75 is the only outlier
C) the values 0.75 and 2.48 are both outliers
D) the value 2.48 is the only outlier
E) the values 1.52 and 2.48 are both outliers
13. The number of Facebook friends students at a university
have are Normally distributed with a mean
of 1200 and a standard deviation of 200. What percentage of
students has exactly 1000 Facebook
friends?
A) 84.13%
B) 15.86%
C) 42.07%
60 65 70 75 80 85 90
Height
10
20
30
40
50

60
70
80
V
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lu
m
e
14. Many residents of suburban neighborhoods own more than
one car but consider one of their cars to
be the main family vehicle. The age of these family vehicles can
be modeled by a Normal distribution
with a mean of 2 years and a standard deviation of 6 months.
What is the standardized value (Z score) for a family vehicle
that is 3 years and 3 months old?
A) 0.22
B) 2.5
C) 2.6
D) 2.92
15. Using the standard Normal distribution tables, what is the
area under the standard Normal curve
corresponding to Z< 1.1?
A) 0.1357
B) 0.2704
C) 0.8413
D) 0.8643

16. Using the standard Normal distribution tables, what is the
area under the standard Normal curve
corresponding to –0.5 <Z< 1.2?
A) 0.3085
B) 0.8849
C) 0.5764
D) 0.2815
17. Chocolate bars produced by a certain machine are labeled
with 8.0 ounces. The distribution of the
actual weights of these chocolate bars is Normal with a mean of
8.1 ounces and a standard deviation
of 0.1 ounces. A chocolate bar is considered underweight if it
weighs less than 8.0 ounces. What
proportion of chocolate bars weighs less than 8.0 ounces?
A) 0.159
B) 0.341
C) 0.500
D) 0.841
18. Which of the following statements about the standardized
z-score of a value of a variable X, which
has a mean of m and a standard deviation of s, is/are TRUE?
A) The z-score has a mean equal to 0.
B) The z-score has a standard deviation equal to 1.
C) The z-score tells us how many standard deviation units from
the original observation fall away
from the mean.

D) The z-score tells us the direction the observation falls away
from the mean.
E) All of the above statements about the z-score are true.
19. A researcher measured the height (in feet) and volume of
usable
lumber (in cubic feet) of 32 cherry trees. The goal is to
determine if the
volume of usable lumber can be estimated from the height of a
tree.
The results are plotted at right. Select all descriptions that
apply to the
scatterplot.
A) There is a positive association between height and volume.
B) There is a negative association between height and volume.
C) There is an outlier in the plot.
D) The plot is skewed to the left.
E) Both A and C
20. John’s parents recorded his height at various ages between
36 and 66 months. Below is a record of
the results:
Age (months) 36 48 54 60 66
Height (inches) 34 38 41 43 45
John’s parents decide to use the least-squares regression line of

John’s height on age to predict his
height at age 21 years (252 months). What conclusion can we
draw?
A) John’s height, in inches, should be about half his age, in
months.
B) The parents will get a fairly accurate estimate of his height
at age 21 years, because the data are
clearly correlated.
C) Such a prediction could be misleading, because it involves
extrapolation.
D) All of the above.
Questions 21 – 23
Colorectal cancer (CRC) is the third most commonly diagnosed
cancer among Americans (with nearly
147,000 new cases), and the third leading cause of cancer death
(with over 50,000 deaths annually).
Research was done to determine whether there is a link between
obesity and CRC mortality rates among
African Americans in the United States by county. Below are
the results of a least-squares regression
analysis from the software StatCrunch.
Simple linear regression results:
Dependent Variable: Mortality.rate
Independent Variable: Obesity.rate
Mortality.rate = 13.458199 – 0.21749489 Obesity.rate
Sample size: 3098
R (correlation coefficient) = –0.0067
R-sq = 4.5304943E-5
Estimate of error standard deviation: 111.20661
Parameter estimates:

Parameter Estimate Std. Err. Alternative DF T-Stat
P-Value
Intercept 13.458199 15.9797735 ≠ 0 3096 0.84220207
0.3997
Slope –0.21749489 0.5807189 ≠ 0 3096 –0.37452698 0.708
Analysis of variance table for regression model:
Source DF SS MS F-stat P-value
Model 1 1734.7122 1734.7122 0.14027046 0.708
Error 3096 3.8287952E7 12366.91
Total 3097 3.8289688E7
21. What is the equation to predict mortality rates from obesity
rates?
A) Mortality.rate = 13.458199 – 0.21749489 Obesity.rate
B) Obesity.rate = 13.458199 - 0.21749489 Mortality.rate
C) Mortality.rate = 13.458199 + 0.21749489 Obesity.rate
D) Mortality.rate = 13.458199 – 0.0067 Obesity.rate
22. What fraction of the variation in mortality rates is
explained by the least-squares regression?
A) 0.000045
B) 111.201
C) –0.0067
D) 13.45
23. A study of the salaries of full professors at a small

university shows that the median salary for female
professors is considerably less than the median male salary.
Further investigation shows that the
median salaries for male and female full professors are about
the same in every department (English,
physics, etc.) of the university. Which phenomenon explains
the reversal in this example?
A) extrapolation
B) Simpson’s paradox
C) causation
D) correlation
Questions 24 – 26
Is age a good predictor of salary for CEO’s? Sixty CEO’s
between the age of 32 and 74 were asked their
salary (in thousands). The results of a statistical analysis are
shown below:
Simple linear regression results:
Dependent Variable: SALARY
Independent Variable: AGE
SALARY = 242.70212 + 3.1327114 AGE
Sample size: 59
R (correlation coefficient) = 0.1276
R-sq = 0.016270384
Estimate of error standard deviation: 220.64246
Parameter estimates:
Parameter Estimate Std. Err. Alternative DF T-Stat P-Value
Intercept 242.70212 168.7604 ≠ 0 57 1.4381461 0.1559
Slope 3.1327114 3.2264276 ≠ 0 57 0.9709536 0.3357
Analysis of variance table for regression model:
Source DF SS MS F-stat P-value
Model 1 45896.027 45896.027 0.9427509 0.3357

Error 57 2774936.2 48683.094
Total 58 2820832.2
24. Suppose a CEO is 57 years old. What do you predict his/her
salary to
be?
A) over $400,000
B) between $100,00 and $400,000
C) under $100,00
D) None of the above.
25. Suppose you wanted to predict the salary of the CEO of
Facebook, Mark Zuckerberg, based on the
information here. How well do you think your prediction would
be assuming Mr. Zuckerberg was 23
when he started Facebook and became CEO?
A) The prediction would be accurate and around $300,000.
B) The prediction would require extrapolation and therefore
would not be accurate.
C) The prediction would be accurate and around $240,000.
26. What are possible reasons for a correlation around 0.13 for
the above data?
A) Age is a very strong predictor of CEO salary.
B) Age is not a good predictor and something else may be a
better a predictor
C) There is not enough data to accurately estimate the
correlation.
D) The range of ages is too small.

0.0 0.5 1.0 1.5 2.0 2.5
X
0.0
0.5
1.0
1.5
2.0
2.5
Y
27. Consider the scatterplot at right. What do we call the point
indicated by
the plotting symbol O?
A) a residual
B) influential
C) a z-score
Questions 28 – 29
The 94 students in a statistics class are categorized by gender
and by the
year in school. The numbers obtained are displayed below:

Year in school
Gender Freshman Sophomore Junior Senior Graduate Total
Male 1 2 9 17 2 31
Female 23 17 13 7 3 63
Total 24 19 22 24 5 94
28. What proportion of the statistics students in this class are
sophomores, given they are female?
A) 0.11 B) 0.202 C) 0.27 D) 19
29. What proportion of the statistics students in this class are
male?
A) 0.065 B) 0.105 C) 0.33 D) 31
30. What is the best way to control for lurking variables?
A) Compare two or more treatments
B) Randomize to assign experimental units to treatments
C) Repeat each treatment on many units
Extra Credit
1. In order to determine if drinking from plastic water bottles
causes cancer, researchers surveyed a large
sample of adults. For each adult they recorded whether the
person drank regularly from plastic water
bottles at any period in their life and whether the person had
cancer. They then compared the
proportion of cancer cases in those who drank from plastic

water bottles regularly at some time in
their lives with the proportion of cases in those who never drank
from plastic water bottles at any point
in their lives. The researchers found a higher proportion of
cancer cases among those who drank
from plastic water bottles regularly than among those who never
drank from plastic water bottles.
What type of study is this?
A) An observational study
B) An experiment but not a double-blind experiment
C) A double-blind experiment
D) A block design
2.. Which of the following best describes a simple random
sample (SRS) of size n?
A) It is a random sample of size n selected so that everyone in
the population has a known
probability of being included in the sample.
B) It is a random sample of size n selected so that everyone in
the population has the same chance
of being included in the sample.
C) It is a probability sample of size n with known probabilities
of selection.
D) It is a sample selected from the population in such a way that
every set of n individuals has an
equal chance of being in the sample actually selected.
E) It is a sample of n individuals selected in such a way that
only chance determines who is included
in the sample.

A common fear for incoming freshman in college is the dreaded
“freshman fifteen.” The combination of
being in a new environment away from home, a high stress
level, alcohol consumption, and eating dining
hall food can cause weight gain in college students. A study
examined weight gained during the first year
of college and what factors contribute to it. A 27-question
survey was sent to 252 students at over 50
universities in the United States. Questions included
information on demographics, weight gain, diet,
family relationships, etc. Ninety-five survey responses were
received from students across 37 United
States colleges and universities, with 32 respondents from Rose-
Hulman Institute of Technology.
3. What is the sample in this study?
A) U.S. college students
B) All college students
C) The survey respondents
D) The 50 universities
4. What is the response rate?
A) 50/252
B) 95/252

C) 32/50
D) 32/25
5. What type of sample is this?
A) Simple random sample
B) Probability sample
C) Stratified random sample
D) Voluntary response sample
6. Does the survey suffer from nonresponse?
A) No, everyone chosen for the survey participated.
B) No, this was an experiment so nonresponse is not an issue.
C) Yes, because not everyone chosen for the survey
participated.
D) Yes, because the survey contained too many questions and it
is likely participants did not
answer all the questions.
7. What could you do to improve the study?
A) Increase the coverage of universities that were selected for
the study.
B) Conduct a matched-pairs design instead. Weigh students on
the first day of class and at the end
of their freshman year.
C) Follow up with students who did not respond to the study to
improve the response rate.

D) All of the above could be done to improve the study.
8. One of the questions asked was, “How much weight did you
gain after your freshman year?” This
would be an example of ______.
A) poor wording of a question because some students may have
lost weight.
B) response bias because the question does not allow for a valid
response from students who lost
weight.
C) voluntary response because the students can write whatever
they want.
D) only A and B.
E) None of the above
Chs 4 – 5
1. A penny is tossed. We observe whether it lands heads up or
tails up. Suppose the penny is a fair
coin, i.e., the probability of heads is ½ and the probability of
tails is ½. What does this mean?
A) Every occurrence of a head must be balanced by a tail in one
of the next two or three tosses.
B) If the coin is tossed many, many times, the proportion of
tosses that land heads will be
approximately ½, and this proportion will tend to get closer and
closer to ½ as the number of

tosses increases.
C) Regardless of the number of flips, half will be heads and half
tails.
2. Which of the following is (are) appropriate statements about
randomness and/or probability?
A) A phenomenon is called random if individual outcomes are
uncertain, but in a large number of
repetitions, there is a regular distribution of outcomes.
B) The word random in statistics is a description of a kind of
order that emerges in the long run.
C) Probability describes only what happens in the long run.
D) In a small or moderate number of repetitions, the observed
proportion of an outcome can be far
from the probability of the outcome.
E) All of the above are appropriate statements.
3. Suppose a fair coin is flipped twice and the number of heads
is counted. Which of the following is a
valid probability model for the number of heads observed in two
flips?
A) Number of heads 0 1 2 C) Number of heads 0 1 2
Probability ¼ ½ ½ Probability ¼ ¼ ¼

B) Number of heads 0 1 2 D) None of the above.
Probability ⅓ ½ ⅓
Use the following to answer questions 4–5:
Ignoring twins and other multiple births, assume babies born at
a hospital are independent events with
the probability that a baby is a boy and the probability that a
baby is a girl both equal to 0.5.
4. What is the probability that the next three babies are of the
same sex?
A) 0.125 C) 0.250
B) 0.375 D) 0.500
5. Define event B = {at least one of the next two babies is a
boy}. What is the probability of the
complement of event B?
A) 0.125 C) 0.250
B) 0.375 D) 0.500
6. The American Veterinary Association claims that the annual
cost of medical care for dogs averages
$100 with a standard deviation of $30. The cost for cats
averages $120 with a standard deviation of
$35. Some basic algebraic and statistical steps show us that the
average of the difference in the cost
of medical care for dogs and cats is then $100 –$120 = –$20.

The standard deviation of that same
difference equals $46. If the difference in costs follows a
Normal distribution, what is the probability
that the cost for someone’s dog is higher than for the cat?
A) 0.2839 C) 0.6618
B) 0.3319 D) 0.7161
Use the following situation to answer questions 7–8:
A study was conducted in a large population of adults
concerning eyeglasses for correcting reading
vision. Based on an examination by a qualified professional,
the individuals were judged as to whether or
not they needed to wear glasses for reading. In addition it was
determined whether or not they were
currently using glasses for reading. The following table
provides the proportions found in the study:
Used glasses for reading
Yes No
Judged to need Yes 0.42 0.18
glasses No 0.04 0.36
7. If a single adult is selected at random from this large
population, what is the probability that the adult is
judged to need eyeglasses for reading?
A) 0.46 C) 0.78
B) 0.42 D) 0.60
8. What is the probability that the selected adult is judged to

need eyeglasses but does not use them for
reading?
A) 0.42 C) 0.54
B) 0.18 D) 0.60
9. Consider the following probability distribution for a discrete
random variable X:
X 3 4 5 6 7
P(X = x) 0.15 0.10 0.20 0.25 0.3
What is the P{X ≤ 5.5}?
A) 0.45 C) 0.20
B) 0.75 D) 0
10. Customers arrive at a Vineyard Vines at an average of 15
per hour (0.25/min).
What is the probability that the manager must wait at least 5
minutes for the first customer?
A) 0.2865 C) 0.6836
B) 0.7135 D) 0.1232
Consider the following probability histogram for a discrete
random variable X: number of hot dogs Capt
Jim eats at a cookout.

11. This probability histogram corresponds to which of the
following distributions for X?
A) Value of X 1 2 3 4 5
Probability 0.06 0.25 0.38 0.25 0.06
B) Value of X 1 2 3 4 5
Probability 0.10 0.25 0.30 0.20 0.15
C) Value of X 1 2 3 4 5
Probability 0.10 0.25 0.30 0.25 0.10
12. What is the P(X = 3)?
A) 0 C) 0.25
B) 0.20 D) 0.30

13. What is P(X < 3)?
A) 0.10 C) 0.35
B) 0.25 D) 0.65
14. What is P(X ≤ 3)?
A) 0.10 C) 0.35
B) 0.25 D) 0.65
15. Central Limit Theorem only applies when sampling from
Normal populations.
A) True
B) False
The Department of Animal Regulations released information on
pet ownership for the population
consisting of all households in a particular county. Let the
random variable X = the number of licensed
dogs per household. The distribution for the random variable X
is given below:
Value of X 0 1 2 3 4 5
Probability 0.52 0.22 0.13 0.03 0.01

16. The probability for X = 3 is missing. What is it?
A) 0.07 C) 0.1
B) 0.09 D) 0.0
17. What is the probability that a randomly selected household
from this community owns at least one
licensed dog?
A) 0.22 C) 0.48
B) 0.26 D) 0.52
18. What is the average number of licensed dogs per household
in this county?
A) 0 dogs C) 1 dog
B) 0.92 dogs D) 1.22 dogs
In a large city, 72% of the people are known to own a cell
phone, 38% are known to own a pager, and
29% own both a cell phone and a pager.
19. What proportion of people in this large city own either a
cell phone or a pager?
A) 0.29 C) 0.81
B) 0.67 D) 1.1

20. What is the probability that a randomly selected person
from this city owns a pager, given that the
person owns a cell phone?
A) 0.266 C) 0.403
B) 0.38 D) 0.528
21. Are the events “owns a pager” and “owns a cell phone”
independent?
A) Yes.
B) No, because P(owns a pager) and P(owns a cell phone) are
not equal.
C) No, because P(owns a pager) and P(owns a pager|owns a cell
phone) are not equal.
D) Cannot be determined.
Chocolate bars produced by a certain machine are labeled 8.0
oz. The distribution of the actual weights
of these chocolate bars is claimed to be Normal with a mean of
8.1 oz and a standard deviation of 0.1 oz.
22. A quality control manager initially plans to take a simple
random sample of size n from the production
line. If he were to double his sample size (to 2n), by what factor
would the standard deviation of the

sampling distribution of X change?
A) 1/2 C) 2
B) 21 D) 2
23. If the quality control manager takes a simple random
sample of ten chocolate bars from the
production line, what is the probability that the sample mean
weight of the 10 sampled chocolate bars
will be less than 8.0 oz?
A) 0 C) 0.0316
B) 0.00078 D) 0.1587
24. A sample of size n is selected at random from a population
that has mean µ and standard deviation
σ . The sample mean x will be determined from the
observations in the sample. Which of the
following statements about the sample mean, x , is (are) TRUE?
A) The mean of x is the same as the population mean, i.e., µ .
B) The variance of x is
σ 2
n .
C) The standard deviation of x decreases as the sample size
grows larger.
D) All of the above are true.

E) Only A and B are true.
25. From the central limit theorem, we know that if we draw a
SRS from any population the sampling
distribution of the sample mean will be EXACTLY Normal.
A) True
B) False
26. The average batch of chocolate at Schakolad Chocolate
Factory will be ready to serve in 1 hour.
What is the chance the next batch will be ready in less than 50
min?
A) 0.3681 C) 0.6836
B) 0.5654 D) 0.1232
27. The following histogram shows the distribution of 1000
sample
observations from a population with mean µ = 4 and variance
2σ
= 8:
Suppose a simple random sample of 100 observations is to be
selected from the population and the sample average, x ,
calculated. Which of the following statements about the

distribution of x is (are) FALSE?
A) The distribution of x will have a mean of 4.
B) The distribution x will be approximately Normal.
C) Because the distribution shown in the histogram above is
clearly skewed to the right, the shape of the distribution of x
will also show skewness to the
right.
D) Even though the distribution of the population variable
appears to be skewed to the right, the
distribution of x will be approximately symmetric around µ =
4.
E) The standard deviation of the distribution of x will be 0.283.
In a test of extrasensory perception (ESP), the experimenter
looks at cards that are hidden from the
subject. Each card contains either a star, a circle, a wavy line,
or a square. An experimenter looks at
each of 100 cards in turn, and the subject tries to read the
experimenter’s mind and name the shape on
each. A subject who is just guessing has probability 0.25 of
guessing correctly on each card.
28. What is the probability that the subject gets more than 30
correct if the subject does not have ESP
and is just guessing? (Use the continuity correction.)
A) Less than 0.0001
B) 0.1038

C) 0.25
D) 0.31
29. What is the probability of the subject obtaining his/her first
correct guess on the 4th question?
A) 0.1055 C) 0.4219
B) 0.8945 D) 0.5781
30. What is the probability of the subject obtaining his/her first
correct guess within the first 4 questions?
A) 0.3164 C) 0.6836
B) 0.8945 D) 0.5781
Extra Credit
1. What is the probability it will take exactly 6 rolls of two fair
dice to make a 7?
A) 0.9330 C) 0.0804
B) 0.0670 D) 0.9196
2. Let X be a binomial random variable with distribution B(10,
0.6). What is the probability that X equals
8?
A) (0.6)
8

(0.4)
2
B)
10!
8!
(0.6)
8
(0.4)
2
C) 45(0.6)
8
(0.4)
2
D) 45(0.6)
2
(0.4)
8
E) None of the above.

3. A college basketball player makes 6
5
of her free throws. Assume free throws are independent. What
is the probability that she makes exactly three of her next four
free throws?
A)
( ) ( )1
6
53
6
14
C)
( ) ( )3
6
51
6
14
B)
( ) ( )1
6
53
6

1
D)
( ) ( )3
6
51
6
1
4. A batch of 100 chocolate chip cookies contains 10 burnt
cookies. Five cookies are chosen at random,
without replacement. Find the probability that the sample
contains at least one burnt cookie.
A) 0.3349 C) 0.4162
B) 0.6606 D) 0.5839
5. The exponential distribution is ______.
A) symmetric
B) bell-shaped
C) All of the above
6. Although cities encourage carpooling to reduce traffic
congestion, most vehicles carry only one

person. For example, nationally 75.5% of the people drive to
work alone.
a) If you choose 12 vehicles driving to work at random, what is
the probability that more than half
(that is, 7 or more) carry just one person?
b) If you choose 80 vehicles at random, what is the probability
that more than half (that is, 41 or
more) carry just one person?
Chs 6 – 8
1. The lifetime (in hours) of a 60-watt light bulb is a random
variable that has a Normal distribution with
σ = 30. A random sample of 25 bulbs put on test produced a
sample mean lifetime of x = 1038.
If in a study of the lifetime of 60-watt light bulbs it was desired
to have a margin of error no larger than
6 hours with 99% confidence, how many randomly selected 60-
watt light bulbs should be tested to
achieve this result?
A) 13
B) 97
C) 165
D) 42
E) Not within ±2 of any of the above.
Use the following to answer questions 2 and 3:

A manufacturer of a specific part used in the operation of a gas
turbine engine is concerned because the
part is designated as critical-to-quality (CQT) and is costly to
produce. The process that is used to
produce the part has been studied extensively and has been
shown to be stable and predictable for some
lengthy period of time. When the process is in the stable state,
the crucial measurement on the CQT part
is known to be Normally distributed with a mean of µ = 1.58
cm and with a standard deviation of σ =
0.10 cm. In order to check on the status of the production
process, a monitoring plan has been
established, which requires that a sample of four manufactured
parts should be selected at random each
hour; if the mean x of the sample exceeds 1.71 cm then the
process is stopped, examined for possible
problems, and repairs made to the process if needed.
2. If the process is operating as it should, what is the
probability that this rule regarding x results in a
shutdown when in fact there is nothing wrong with the process
(this is called a false alarm)?
A) 0.0013
B) 0.0094
C) 0.0986
D) 0.0047
E) Not within ± 0.001 of any of the above.
3. If, in fact, the process has changed and the process mean has
shifted to µ = 1.73, what is the
probability that this rule regarding x will fail to detect the
shift?

A) 0.3446
B) 0.6554
C) 0.9987
D) 0.0013
E) Not within ± 0.001 of any of the above.
4. In the last mayoral election in a large city, 47% of the adults
over the age of 65 voted Republican. A
researcher wishes to determine if the proportion of adults over
the age of 65 in the city who plan to
vote Republican in the next mayoral election has changed. Let
p represent the proportion of the
population of all adults over the age of 65 in the city who plan
to vote Republican in the next mayoral
election. In terms of p, the researcher should test which of the
following null and alternative
hypotheses?
A) Ho: p = 0.47 vs. Ha: p < 0.47
B) Ho: p = 0.47 vs. Ha: p ≠ 0.47
C) Ho: p = 0.47 vs. Ha: p > 0.47
The Survey of Study Habits and Attitudes (SSHA) is a
psychological test that measures the motivation,
attitude, and study habits of college students. Scores range
from 0 to 200 and follow (approximately) a
Normal distribution with mean 115 and standard deviation 25.
You suspect that incoming freshmen at
because they are often excited yet anxious about

entering college. To test your suspicion, you decide to test the
hypotheses Ho: µ = 115 versus Ha: µ
≠ 115. You give the SSHA to 25 incoming freshmen and find
their mean score to be 116.2.
5. What is the value of the test statistic?
A) z = 0.048 C) z = 1.2
B) z = 0.24 D) z = 1.96
6. What is the value of the p-value?
A) 0.1151 C) 0.4052
B) 0.2302 D) 0.8104
The attention span of little kids (ages 3–5) is claimed to be
Normally distributed with a mean of 15
minutes and a standard deviation of 4 minutes. A test is to be
performed to decide if the average attention
span of these kids is really this short or if it is longer. You
decide to test the hypotheses Ho: µ = 15
versus Ha: µ > 15 at the 5% significance level. A sample of 10
children will watch a TV show they have
never seen before, and the time until they walk away from the
show will be recorded.
7. Fill in the blank. At a significance level of 5%, the decision
rule would be to reject the null hypothesis if
the observed sample mean is greater than _________ minutes.
A) 15.66 C) 17.48
B) 17.08 D) 19

8. If, in fact, the true mean attention span of these kids is 18
minutes, what is the probability of a Type II
error?
A) 0.0107 C) 0.3405
B) 0.2335 D) 0.7665
9. A study has been completed involving a test of significance
of the null hypothesis Ho: µ = 0. The
researchers have discovered that the power of the test is too
small. What can the researchers try
to do in order to increase the power of their test procedure?
A) Increase the level of significance, α .
B) Increase the sample size, n.
C) Decrease the population standard deviation, σ .
E) None of the above; nothing can be done to increase the
power.
The time needed for college students to complete a certain
paper-and-pencil maze follows a Normal
distribution with a mean of 30 seconds and a standard deviation
of 3 seconds. You wish to see if the
mean time µ is changed by vigorous exercise, so you have a
group of nine college students exercise
vigorously for 30 minutes and then complete the maze. Assume
that σ remains unchanged at 3
seconds. The hypotheses you decide to test are Ho: µ = 30
versus Ha: µ ≠ 30.

10. Suppose it takes the nine students an average of x = 32.05
seconds to complete the maze. At the
1% significance level, what can you conclude?
A) Ho should be rejected because the p-value is less than 0.01.
B) Ho should not be rejected because the p-value is greater than
0.01.
C) Ha should be rejected because the p-value is less than 0.01.
D) Ha should not be rejected because the p-value is greater than
0.01.
11. Suppose you compute the average time x that it takes these
students to complete the maze and
you find that the results are significant at the 5% level. What
can you conclude?
A) The test would also be significant at the 10% level.
B) The test would also be significant at the 1% level.
C) Both of the above.
A 95% confidence interval (using the conservative value for the
degrees of freedom) for
1 2
µ µ− , based on two independent samples of sizes 18 and 20,
respectively, gives us (45.6, 56.7).
12. What was the observed difference between the two sample
means 1x and 2x ?
A) 11.1 C) 51.15

B) 45.6 D) 56.7
13. What would be the margin of error for a 99% confidence
interval for
1 2
µ µ− ?
A) 2.63 C) 5.55
B) 2.898 D) 7.62
14. When the sample size is very large, the corresponding t
distribution is very close to the normal
distribution.
A) True
B) False
You wish to compare the prices of apartments in two
neighboring towns. You take a simple random
sample of 12 apartments in town A and calculate the average
price of these apartments. You repeat this
for 15 apartments in town B. Let
1
µ represent the true average price of apartments in town A and
2
µ the
average price in town B.
15. What would be the hypotheses for this problem?

A) Ho:
1
µ =
2
µ versus Ha:
1
µ <
2
µ
B) Ho:
1
µ =
2
µ versus Ha:
1
µ >
2
µ
C) Ho:
1
µ =
2
µ versus Ha:

1
µ ≠
2
µ
16. If we were to use the pooled t test, what would be the
degrees of freedom?
A) 11 C) 14
B) 12 D) 25
17. If we were to use the unpooled t test, what would be the
conservative estimate for the degrees of
freedom?
A) 11 C) 14
B) 12 D) 25
18. Suppose we were to use the unpooled t test with the
conservative estimate for the degrees of
freedom. The t statistic for comparing the mean prices is 2.1.
What can we say about the value of the
p-value?
A) p-value < 0.01 C) 0.05 < p-value < 0.10
B) 0.01 < p-value < 0.05 D) p-value > 0.10

Ten couples are participating in a small study on cholesterol.
Neither the man nor the woman in each
couple is known to have any problems with high cholesterol.
The researcher conducting the study wishes
to use the t test for matched pairs to determine if there is
evidence that the cholesterol level for the
husband tends to be higher than the cholesterol level for the
wife. The cholesterol measurements for the
ten couples are given below:
Couple 1 2 3 4 5 6 7 8 9 10
Husband’s cholesterol 224 310 266 332 244 178 280 276 242
260
Wife’s cholesterol 200 270 288 296 270 180 268 244 210 236
19. What are the hypotheses the researcher wishes to test?
A) Ho:
D
µ = 0 versus Ha:
D
µ > 0, where
D
µ = the mean of the differences in cholesterol levels
(Husband – Wife) for all couples without cholesterol problems.
B) Ho: p = ½ versus Ha: p ≠ ½, where p = the proportion of
cholesterol levels of the husband that
are higher than those of the wife.
C) Ho: p = ½ versus Ha: p < ½, where p = the proportion of

cholesterol levels of the husband that
are higher than those of the wife.
D) Ho: population median = 0 versus Ha: population median >
0, where the differences for which the
median is calculated are measured as Husband – Wife.
20. What is the (approximate) value of the p-value?
A) 0.039 C) 0.079
B) 0.055 D) 0.172
A sportswriter wished to see if a football filled with helium
travels farther, on average, than a football filled
with air. To test this, the writer used 18 adult male volunteers.
These volunteers were randomly divided
into two groups of nine subjects each. Group 1 kicked a
football filled with helium to the recommended
pressure. Group 2 kicked a football filled with air to the
recommended pressure. The mean yardage for
Group 1 was 1x = 30 yards with a standard deviation
1
s = 8 yards. The mean yardage for Group 2 was
2x = 26 yards with a standard deviation
2
s = 6 yards. Assume that the two groups of kicks are
independent. Let
1

µ and
2
µ represent the mean yardage we would observe for the entire
population
represented by the volunteers if all members of this population
kicked, respectively, a helium-filled football
and an air-filled football. Let
1
σ and
2
σ be the corresponding population standard deviations.
21. Assuming two-sample t procedures are safe to use, what is
a 99% confidence interval for
1
µ –
2
µ ?
(Use the conservative value for the degrees of freedom.)
A) 4 ± 4.7 yards C) 4 ± 7.7 yards
B) 4 ± 6.2 yards D) 4 ± 11.2 yards
22. Suppose we wish to test the hypothesis that the groups are
equivalent in how variable their kicks are.
To do this, we wish to test the hypotheses Ho:
1

µ =
2
µ versus Ha:
1
µ ≠
2
µ . Assume the
distribution of the lengths of these kicks is Normal. What can
we say about the value of the p-value?
A) p-value < 0.025 C) 0.05 < p-value < 0.10
B) 0.025 < p-value < 0.05 D) p-value > 0.10
23. Based on the confidence interval for the difference in
means and the test for equality of the standard
deviations, we can draw a conclusion about the distribution of
the lengths of the kicks with the two
different kinds of footballs. Determine which of the following
statements is true.
A) Both the means and standard deviations of the air and helium
groups seem to be the same.
B) The means of the air and helium groups seem to be the same.
However, the standard deviations
seem to be different.
C) The standard deviations of the air and helium groups seem to
be the same. However, the means
seem to be different.

D) Both the means and standard deviations of the air and helium
groups seem to be different from
one another.
24. If we had used the more accurate software approximation to
the degrees of freedom, what would be
the number of degrees of freedom for the two-sample t
procedures?
A) 8 C) 14
B) 9.374 D) 14.837
There is substantial interest in the health benefits of the
consumption of high amounts of fiber in diets. A
market research team is interested in the public acceptance of a
new high-fiber cereal (more than 8 gm of
fiber per serving) that is to be marketed. To that end, the
researchers selected a random sample of
subjects from one region of the country. The selected subjects
were provided with two bowls of cereal.
One bowl contained the new cereal and the other bowl a well-
known and popular cereal. The bowls were
presented in random order and subjects asked which cereal they
preferred. The study was repeated
independently in a second region. In region 1, of the 400
subjects, 220 preferred the new cereal; in
region 2, 195 of the 300 subjects indicated a preference for the
new cereal.
25. The researchers wanted to test whether the proportions of
consumers who preferred the new high-
fiber cereal are the same or different in the two regions. What

null and alternative hypotheses should
they establish?
A) Ho: p1 = p2 against Ha: p1 > p2
B) Ho: p̂ 1 = p̂ 2 against Ha: p̂ 1 ≠ p̂ 2
C) Ho: p1 = p2 against Ha: p1 ≠ p2
D) Ho: p̂ 1 = p̂ 2 against Ha: p̂ 1 > p̂ 2
E) Ho: p1 − p2 = 0 against Ha: p1 − p2 = 0.5
26. What is the value of the test statistic?
A) t = −2.67
B) z = −2.70
C) z = −3.84
D) z = −2.66
E) t = −2.70
27. What is the p-value for this test?
A) 0.0077
B) 0.0035
C) 0.0070
D) 0.0038
E) < 0.0002

Use the following to answer questions 28 – 30:
A study was conducted at the University of Waterloo on the
impact characteristics of football helmets
used in competitive high school programs. There were three
types of helmets considered, classified
according to liner type: suspension, padded-suspension, and
padded. In the study, a measurement
called the Gadd Severity Index (GSI) was obtained on each
helmet using a standardized impact test. A
helmet was deemed to have failed if the GSI was greater than
1200. Of the 81 helmets tested, 29 failed
the GSI 1200 criterion.
28. Assume that the suspension helmets tested were selected at
random. What are the point estimates
of the proportion of suspension helmets that fail and the
standard error of the estimate, respectively?
A) 0.36; 0.0028
B) 0.64; 0.053
C) 0.36; 0.053
D) 0.64; 0.0028
E) 0.36: 0.089
29. Based on the sample results, what is the 90% confidence
interval estimate for the true population
proportion of suspension helmets that would fail the test?
A) (0.304, 0.416)
B) (0.256, 0.464)
C) (0.213, 0.507)
D) (0.272, 0.448)
E) (0.553, 0.737)

30. If the test was to be conducted again, how many
suspension-type helmets should be tested so that
the margin of error does not exceed 0.05 with 95% confidence?
A) 355
B) 20
C) 271
D) 250
E) 82
Extra Credit
1. The scores on the Wechsler Intelligence Scale for Children
(WISC) are thought to be Normally
distributed with a standard deviation of σ = 10. A simple
random sample of 25 children is taken, and
each is given the WISC. The mean of the 25 scores is x =
104.32. Based on these data, what is a
95% confidence interval for µ ?
A) 104.32 ± 0.78
B) 104.32 ± 3.29
C) 104.32 ± 3.92
D) 104.32 ± 19.60
2. A sample of size n = 27 is used to conduct a significance test
for Ho: µ = 75 versus
Ha: µ > 75. The test statistic is t = 3.45. What are the degrees
of freedom for this test statistic?
A) 26
B) 27

C) 74
D) 75
3. A simple random sample of five female basketball players is
selected. Their heights (in cm) are 170,
175, 169, 183, and 177. What is the standard error of the mean
of these height measurements?
A) 2.538
B) 2.837
C) 5.075
D) 5.675
Chs 9 – 12
For Questions 1 – 2
A sample of 50 male and 50 female infants were put on an
experimental infant formula. After two weeks
the parents of each infant were asked to fill out a questionnaire
concerning infant satisfaction on the
formula. One of the questions was "Did Baby Seem to Like the
Formula?" with possible responses
1 – Like Very Much; 2 – Like Somewhat; 3 – Neutral; 4 –
Dislike Somewhat; 5 – Dislike Very Much
The resulting data are presented below.
Gender
Male Female
Like Very Much 16 14

Like Somewhat 13 18
Neutral 17 16
Dislike Somewhat 3 2
Disike Very Much 1 0
1. This is a
a) 2 x 2 table.
b) 2 x 5 table.
c) 5 x 2 table.
d) 5 x 5 table
2. The appropriate null hypothesis for this data is that
a) the distribution of parents' responses on this question is the
same for male and female infants.
b) the distribution of gender is the same for each parents'
response to this question.
c) gender and parents' responses on this question are
independent.
d) gender and parents' responses on this question are dependent
3. A study to compare two types of infant formula was run at
two sites, one in Atlanta and the second in
Denver. The study was run over a three-week period. Subjects at
both sites were classified as
dropouts if they left the study before the conclusion, or
completers if they finished the study. The
following table gives the number of dropouts and completers at
each site. A chi-square test was
performed and the result was X

2
= 5.101 with p-value = 0.024.
Responder
Dropout Completer
Atlanta 16 134
Denver 21 379
The correct conclusion is
a) we found evidence to suggest that Atlanta had a greater
dropout rate.
b) we found evidence to suggest that Denver had a greater
dropout rate.
c) any differences can be explained by sampling variability.
d) there is no association between responder and dropout rate.
A study was performed to examine the personal goals of
children in grades 4, 5, and 6. A random sample
of students was selected for each of the grades from schools in
Georgia. The students received a
questionnaire regarding personal goals. They were asked what
they would most like to do at school:
make good grades, be popular, or be good at sports. Results are
presented in the table below by the sex
of the child.
Make good grades Be popular Be good in sports

Boys 96 32 94
Girls 295 45 40
4. The proportion of boys who chose the goal "be good in
sports" and the proportion of girls who chose
the goal "be good in sports" are
a) proportion of boys = 0.42, proportion of girls = 0.07.
b) proportion of boys = 0.70, proportion of girls = 0.30.
c) proportion of boys = 0.16, proportion of girls = 0.07.
d) proportion of boys = 0.42, proportion of girls = 0.11.
5. Suppose we wish to test the null hypothesis that there are no
differences among the proportion of boys
and the proportion of girls choosing each of the three personal
goals. Under the null hypothesis, the
expected number of boys that would select "be good in sports"
is
a) 49.4
b) 67
c) 74
d) 33
6.. Suppose we wish to test the null hypothesis that there are no
differences among the proportion of
boys and the proportion of girls choosing each of the three
personal goals. The value of the chi-
square statistic X

2
is
a) 0.2893
b) 1.2644
c) 90.0266
d) 45.4335
At what age do babies learn to crawl? Does it take longer to
learn in the winter when babies are often bundled
in clothes that restrict their movement? Data were collected at
the University of Denver Infant Study Center
where parents and their babies participated in one of a number
of experiments between 1988 and 1991.
Parents reported the age (in weeks) at which their child was
first able to creep or crawl a distance of four feet
within one minute. The researchers also recorded the average
outdoor temperature (in °F) six months after
each baby's birthdate. For each month of the year, the
researchers selected one baby, at random, born in that
month. If we fit the least-squares line to the 12 data points (one
for each month) we obtain the following
results from a software package. Notice that temperature is
taken as the explanatory variable and crawling
age as the response.
s = 1.319
Variable Parameter estimate Standard error of estimate
Intercept 35.6781 1.318

Temperature -0.077739 0.0251
Here is a scatterplot of average crawling age versus average
outdoor temperature six months after birth
followed by a plot of the residuals versus average outdoor
temperature six months after birth.
Suppose the researchers test the hypotheses
0
H : the slope of the least-squares regression line = 0
a
H : the slope of the least-squares regression line ≠ 0.
7. The explanatory variable in this study is
a) crawling age
b) the age (in weeks) at which a baby was first able to creep or
crawl a distance of four feet within
one minute.
c) the extent to which parents honestly reported the age at
which their baby was first able to crawl
and didn't exaggerate in order to make their baby appear gifted.
d) the average outdoor temperature six months after a baby's

birthdate
8. The slope of the least-squares regression line is
(approximately)
a) 35.68.
b) 1.32.
c) -0.08.
d) -0.80
9. The quantity s = 1.319 is an estimate of the standard
deviation of the deviations in the simple linear
regression model. The degrees of freedom for s
2
are
a) 1.74.
b) 10.
c) 11.
d) 12
10. The value of the t statistic for this test is
a) -0.06.
b) -3.10.
c) 27.07.
d) 3.10

11. Which of the following statements is supported by these
plots?
a) There is no striking evidence in these plots that the
assumptions for regression are violated.
b) There is evidence in these plots that the assumptions for
regression are violated.
c) There is an influential observation in the plot, which should
be deleted.
d) There is an outlier in the plots suggesting that our above
results must be interpreted with caution.
12. A 90% confidence interval for the slope of the least-squares
regression line is (approximately)
a) -0.078 ± 0.041.
b) -0.078 ± 0.045.
c) -0.078 ± 0.056.
d) -0.078± 0.059.
13. Suppose we wish to determine the mean crawling age for
all babies born when the average outdoor
temperature is 25°F six months after birth. We use computer
software to do the prediction and obtain
the following output.
Temp. Predict Stdev. Mean Predict

25° F 33.735 0.739
95% C.I. for Mean Predict 95% Predict Interval
(32.087, 35.382) (30.364, 37.105)
A 95% interval for mean crawling age is
a) (32.087, 35.382).
b) (30.364, 37.105).
c) 33.735 ± 0.739.
d) 33.735 ± 6.741
Is there a relationship between brain size and intelligence? The
Full Scale IQ scores (FSIQ) and brain
sizes (in pixels, as measured by MRI scans) of 39 subjects were
measured. Researchers wished to study
the relationship between FSIQ and brain size, using brain size
to predict FSIQ. However, the researchers
believed that brain size is also dependent on body size and that
some adjustment for body size might be
necessary in order to understand the relation between brain size
and intelligence. Therefore, the
researchers also measured the heights (in inches) of the 39
subjects and used height as a measure of
body size. They then used a multiple regression model to
predict FSIQ from brain size and height. They
obtained the following results.
Analysis of Variance
Source df Sum of squares Mean Squares F

Model 2 5861.7
Error 36 15805.2
Total 38 21666.9
Variable Parameter estimate Standard error
Intercept 117.22 59.09
Brain size 0.00020957 0.00005816
Height -2.824 1.065
s = 20.95,
2
R = 0.271
The researchers assume that the statistical model for the relation
between FSIQ, brain size, and
height is the multiple linear regression model
i
FSIQ =
0
β +
1
β (brain size)i +
2
β (height)i +

i
ε
for i = 1, 2,..., 39. The deviations
i
ε are assumed to be independent and normally distributed with
mean 0 and standard deviation σ.
Complete the above ANOVA Table and then answer questions
14 – 16.
14. One of the subjects had FSIQ = 130, brain size = 866,662,
and height = 66.5. The residual for this
subject is
a) 18.95.
b) 20.95.
c) 111.05.
d) 5.35.
15. The p-value of the analysis of variance F test of the
hypothesis Ho:
1 2
0β β= = is
a) less than 0.01.

b) between 0.01 and 0.05.
c) between 0.05 and 0.10
d) greater than 0.10.
16. Based on the above results, we may conclude that
a) the proportion of the variation of FSIQ that is explained by
brain size in a multiple linear regression is
0.271.
b) the proportion of the variation of FSIQ that is explained by
the variables brain size and height in a
multiple linear regression is 0.271.
c) the proportion of the variation of FSIQ that is explained by
the variables brain size and height in a
multiple linear regression is 0.52.
d) None of the above
A manufacturer of infant formula is running an experiment
using the standard (control) formula, and two
new formulas, A and B. The goal is to boost the immune system
in infants. 120 infants in the study are
randomly assigned to each of three groups: group A, group B,
and a control group. There are 40 infants
per group, and the study is run for 12 weeks. At the end of the
study the variable measured is total IGA
(in mg per dl), with higher values being more desirable. We are
going to run a one-way ANOVA on these
data. A partial ANOVA table is given below.

One-Way Analysis of Variance
Source DF SS MS F p
Group
Error 0.00252
Total 0.31841
17. Complete the ANOVA table above. What is the value of
the F-statistic?
a) 5.469
b) 0.002
c) 0.118
d) 4.679
18. The hypotheses tested by the one-way ANOVA F test are
a) Ho: the mean IGA score is the same for all three formulas.
Ha: the mean IGA score is higher for both treatment groups A
and B than the control group.
b) Ho: the mean IGA score is the same for all three formulas.
Ha: the mean IGA score is higher for at least one of the two
treatment groups than the control
group.
c) Ho: the mean IGA score is the same for all three formulas.
Ha: the mean IGA score is not the same for all three formulas.
d) Ho: the mean IGA score is the same for all three formulas.

Ha: the mean IGA score is lower for at least one of the two
treatment groups than the control
group.
19. The mean square for groups in this table is
a) 0.00786.
b) 0.01179.
c) 0.02357.
d) 0.31841
20. The p-value for testing
Ho: the mean IGA score is the same for all three formulas
Ha: the mean IGA score is not the same for all three formulas
a) is less than 0.001.
b) is between 0.001 and 0.025.
c) is between 0.05 and 0.1
d) is greater than 0.10.
Extra Credit
A study was conducted to monitor the emissions of a noxious
substance from a chemical plant and the
concentration of the chemical at a location in close proximity to
the plant at various times throughout the
year. A total of 14 measurements were made. Computer output
for the simple linear regression least-
squares fit is provided (some entries have been omitted and

replaced with *****):
Linear Fit
Concentration = 1.5429211 + 1.8247687 Emissions
Summary of Fit
RSquare 0.793919
RSquare Adj 0.776745
Root Mean Square Error 1.513979
Mean of Response 8.810714
Observations (or Sum Wgts) 14
Source DF Sum of Squares Mean Square F Ratio Prob > F
Model ** 105.96390 ********* 46.229 <.0001
Error ** *********** *********
C. Total ** 133.46949
Parameter Estimates
Term Estimate Std Error t Ratio Prob>|t|
Intercept 1.5429211 1.142937 **** 0.2019
Emissions 1.8247687 0.268379 **** <.0001
1. The degrees of freedom for SSM and SSE are, respectively:
a) DFM = 2, DFE = 12.
b) DFM = 1, DFE = 12.
c) DFM = 1, DFE = 13.
d) DFM = 1, DFE = 14.

2. What is the value for the SSE?
a) 27.50559
b) 10.26688
c) 1.142937
d) 2.292
3. What is the estimate of σ
2
?
a) 1.514
b) 1.143
c) 0.794
d) 2.292
4. What is the test statistic and its value to test Ho:
1
0β = against Ha:
1
0β ≠ ?
a) F = 46.2294
b) t = 6.80
c) t = 1.35
d) Either A or B.
5. What is the 95% confidence interval estimate for
0

β ?
A) (1.24, 2.41)
B) (-0.49, 3.58)
C) (-0.95, 4.03)
D) (1.35, 2.39)
6. What is the goal of statistics?
a) Creating sampling distributions of the sample mean that are
approximately normal
b) Maximize systematic variance, minimize error variance.
c) A density curve has an area underneath it of 1
d) P-values are more informative than the reject-or-not result
of a fixed level α test.

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