CHAPTER 3
DESCRIBING DATA: SUMMARY MEASURES
MULTIPLE CHOICE QUESTIONS
In the following multiple-choice questions, please circle the correct answer.
1.
Which of the following are the three most common measures of central location?
a. Mean, median and mode
b. Average, variance and standard deviation
c. Mode, sample mean, and sample variance
d. Mean, median, and average
ANSWER: a
2.
Which of the following are considered measures of association?
a. Mean and variance
b. Variance and correlation
c. Covariance and correlation
d. Covariance and variance
ANSWER: c
3.
The difference between the first and third quartile is called the
a. interquartile range
b. interdependent range
c. unimodal range
d. common occurrence range
e. none of the above
ANSWER: a
32
.
Describing Data: Summary Measures
4.
If a value represents the 95th percentile, this means:
a. 95% of all values are below this point
b. 95% of all values are above this point
c. 95% of the time you will observe this value
d. there is a 5% chance that this value is incorrect
e. none of the above
ANSWER: a
5.
For a boxplot, the point inside the box indicates the location of the __________.
a. mean
b. median
c. minimum value
d. maximum value
ANSWER: a
6.
For a boxplot, the vertical line inside the box indicates the location of the______.
a. mean
b. median
c. mode
d. minimum value
e. maximum value
ANSWER: b
7.
Suppose that a histogram of a data set is approximately symmetric and "bell
shaped". Approximately
percent of the observations are within three
standard deviation of the mean.
a. 50
b. 68
c. 95
d. 99.7
e. 100
ANSWER:
8.
d
The correlation coefficient is always:
a. between – 1 and 0
b. between 0 and +1
c. between 0.0 and 100
d. between –1 and +1
ANSWER: d
33
Chapter 3
9.
Which of the following are the two most commonly used measures of variability?
a. Variance and mode
b. Variance and standard deviation
c. Sample mean, and sample variance
d. Mean and range
ANSWER: b
10.
Boxplots are probably most useful for
.
a. calculating the mean of the data
b. calculating the median of the data
c. comparing the mean to the median
d. comparing two populations graphically
e. comparing the correlation and the covariance
ANSWER: d
11.
Suppose that a histogram of a data set is approximately symmetric and "bell
shaped". Approximately
percent of the observations are within one
standard deviation of the mean.
a. 50
b. 68
c. 95
d. 99.7
e. 100
ANSWER:
12.
Suppose that a histogram of a data set is approximately symmetric and "bell
shaped". Approximately
percent of the observations are within two
standard deviation of the mean.
a. 50
b. 68
c. 95
d. 99.7
e. 100
ANSWER:
13.
b
c
The mode is best described as:
a. the middle observation
b. the same as the average
c. the 50th percentile
d. the most frequently occurring value
ANSWER: d
34
Describing Data: Summary Measures
14.
The median can also be described as:
a. the middle observation when the data is arranged in ascending order
b. the second quartile
c. the 50th percentile
d. all of the above
e. none of the above
ANSWER: d
15.
For a boxplot, the box itself represents
a. 25
b. 50
c. 75
d. 90
e. 100
ANSWER:
16.
percent of the observations.
b
Which of the following best describes a data warehouse?
a. A physical facility full of databases
b. A storage facility for government information
c. A database specifically structured to enable data mining
d. A database used to track warehousing information
e. None of the above
ANSWER: c
35
Chapter 3
TEST QUESTIONS
QUESTIONS 17 AND 18 ARE BASED ON THE FOLLOWING INFORMATION:
Statistics professor has just given a final examination in his statistical inference course.
He is particularly interested in learning how his class of 40 students performed on this
exam. The scores are shown below.
75
81
88
80
17.
79
82
83
76
72
79
90
84
75
71
82
84
77
73
79
80
71
89
62
68
78
74
73
74
83
75
88
76
84
93
76
70
71
74
76
91
What are the mean and median scores on this exam?
ANSWER:
Mean = 78.40, Median = 77.50
18.
Explain why the mean and median are different.
ANSWER:
There are few higher exam scores that tend to pull the mean away from the
middle of the distribution. While there is a slight amount of positive skewness in
the distribution (skewness = 0.182), the mean and the median are essentially
equivalent in this case.
QUESTIONS 19 AND 20 ARE BASED ON THE FOLLOWING INFORMATION:
The average time in minutes, for a sample of 40 people living in Detroit metropolitan
area to travel to work and back home each day is shown below.
42.8
51.8
41.3
61.5
19.
47.1
43.1
32.6
36.5
46.3
51.5
34.1
48.9
42.2
45.5
31.9
40.6
55.9
40.7
42.9
48.1
35.0
57.6
48.5
39.8
41.4
36.5
46.7
35.6
37.8
32.3
40.9
44.4
33.9
41.9
46.6
38.6
36.6
37.0
29.5
45.6
Find the most representative average commute time.
ANSWER:
The most representative average commute time for Detroit metropolitan area is
slightly greater than 41 minutes. The median is the best measure of central
location due to the distribution positive skewness (skewness = 0.573).
36
Describing Data: Summary Measures
20.
Does it appear that the distribution of average commute time is approximately
symmetric? Explain why or why not.
ANSWER:
The distribution is slightly skewed to the right; it is essentially not symmetric.
Notice that the mean is slightly greater than the median here; the mean is
influenced by the existence of some relatively large commute times in the sample.
QUESTIONS 21 AND 22 ARE BASED ON THE FOLLOWING INFORMATION:
A production manager for Bell Computers is interested in determining the variability of
the proportion defective items in a shipment of one of the computer components used in
their product. The results below were calculated using information on the percent
defective from 50 randomly selected shipments collected over a 6-week period.
Count
Mean
Median
Standard deviation
Minimum
Maximum
Variance
First quartile
Third quartile
21.
50.000
0.210
0.206
0.057
0.104
0.299
0.003
0.153
0.248
Use the above information to determine the rules of thumb in this case.
ANSWER:
Approximately 68% of the values will fall between 0.210  0.057, that is between
0.153 and 0.267.
Approximately 95% of the values will fall between 0.210  2 (0.057), that is
between 0.096 and 0.324.
Approximately 99.7% of the values will fall between 0.210  3 (0.057), that is
between 0.039 and 0.381.
22.
Explain what would cause the mean to be higher than the median in this case.
ANSWER:
The data seems to be skewed to the right. This is causing the mean to be slightly
higher than the median.
37
Chapter 3
QUESTIONS 23 THROUGH 25 ARE BASED ON THE FOLLOWING INFORMATION:
A manager for Marko Manufacturing, Inc. has recently been hearing some complaints
that women are being paid less than men for the same type of work in one of their
manufacturing plants. The boxplots shown below represent the annual salaries for all
salaried workers in that facility (40 men and 34 women).
Female_Salary
Male_Salary
0
23.
20000
40000
60000
80000
Would you conclude that there is a difference between the salaries of women and
men in this plant? Justify your answer.
ANSWER:
Yes. The men seem to have higher salaries than the women do in many cases.
We can see from the boxplots that the mean and median values for the men are
both higher than for the women. You can also see from the boxplots that the
middle 50% of salaries for men is above the median for women. This means that
if you were in the 25th percentile for men, you would be above the 50th percentile
for women. You can also see that the mean and median salaries for the men are
about $10,000 above those for the women.
24.
How large must a person’s salary should be to qualify as an outlier on the high
side? How many outliers are there in these data?
ANSWER:
A person’s salary should be somewhere above $70,000. There is one male salary
that would be considered an outlier (at approximately $80,000)
38
Describing Data: Summary Measures
25.
What can you say about the shape of the distributions given the boxplots above?
ANSWER:
They both appear to be slightly skewed to the right (both have a mean > median).
The total variation seems to be close for both distributions (with one outlier for
the male salaries), but there seems to be more variation in the middle 50% for the
women than for the men. There seem to be more men’s salaries clustered more
closely around the mean than for the women.
QUESTIONS 26 THROUGH 28 ARE BASED ON THE FOLLOWING INFORMATION:
Below you will find current annual salary data and related information for 30 employees
at Gamma Technologies, Inc. These data include each selected employees gender (1 for
female; 0 for male), age, number of years of relevant work experience prior to
employment at Gamma, number of years of employment at Gamma, the number of years
of post-secondary education, and annual salary. The tables of correlations and
covariances are presented below.
Table of Correlations
Gender
Gender
1.000
Age
-0.111
Prior_Exp
0.054
Gamma_Exp -0.203
Education
-0.039
Salary
-0.154
Age
1.000
0.800
0.916
0.518
0.923
Prior Exp
Gamma Exp
Education
Salary
1.000
0.587
0.434
0.723
1.000
0.342
0.870
1.000
0.617
1.000
Table of Covariances (variances on the diagonal)
Gender
Age
Prior Exp
Gamma Exp
Education
Salary
26.
Gender
0.259
-0.633
0.117
-0.700
-0.033
-1825.97
Age
Prior Exp
Gamma Exp
Education
Salary
134.051
39.060
72.047
9.951
249702.35
19.045
17.413
3.140
73699.75
49.421
3.987
143033.29
2.947
24747.68
584640062
Which two variables have the strongest linear relationship with annual salary?
ANSWER:
Age at 0.923 and Gamma experience at 0.870 have the strongest linear
relationship with annual salary.
39
Chapter 3
27.
For which of the two variables, number of years of prior work experience or
number of years of post-secondary education, is the relationship with salary
stronger? Justify your answer.
ANSWER:
Prior work experience is stronger at 0.723 versus 0.617 for number of years of
post-secondary education.
28.
How would you characterize the relationship between gender and annual salary?
ANSWER:
It is a somewhat weak relationship at –0.154. Also, the negative value tells us that
the salaries are decreasing as the gender value increases. This indicates that the
salaries are lower for females (1) than for males (0).
QUESTIONS 29 THROUGH 31 ARE BASED ON THE FOLLOWING INFORMATION:
The data shown below contains family incomes (in thousands of dollars) for a set of 50
families; sampled in 1980 and 1990. Assume that these families are good representatives
of the entire United States.
1980
58
6
59
71
30
38
36
33
72
100
1
27
22
141
72
165
79
1990
54
2
55
57
26
34
32
29
68
96
0
23
47
166
97
190
104
1980
33
14
48
20
24
82
95
12
93
100
51
22
50
124
113
118
96
1990
29
10
44
16
20
78
97
8
89
102
47
18
75
149
138
143
121
1980
73
26
64
59
11
70
31
92
115
62
23
34
36
125
121
88
40
1990
69
22
70
55
7
66
27
88
111
58
19
30
61
150
146
113
Describing Data: Summary Measures
29.
Find the mean, median, standard deviation, first and third quartiles, and the 95th
percentile for family incomes in both years.
ANSWER:
Mean
Median
Standard deviation
First quartile
Third quartile
95th percentile
30.
Income 1980
62.820
59.000
39.786
30.250
92.750
124.550
Income 1990
67.120
57.500
48.087
27.500
97.000
149.55
The Republicans claim that the country was better off in 1990 than in 1980,
because the average income increased. Do you agree?
ANSWER:
It is true that the mean increased slightly, but the median decreased and the
standard deviation increased. The 95th percentile shows that the mean increase
might be because the rich got riches.
31.
Generate a boxplot to summarize the data. What does the boxplot indicate?
ANSWER:
The boxplot shows that there is not much difference between the two populations.
Income_1990
Income_1980
0
40
80
41
120
160
20
Chapter 3
QUESTIONS 32 THROUGH 35 ARE BASED ON THE FOLLOWING INFORMATION:
In an effort to provide more consistent customer service, the manager of a local fast-food
restaurant would like to know the dispersion of customer service times about their
average value for the facility’s drive-up window. The data below represents the customer
service times (in minutes) for a sample of 47 customers collected over the past week.
Count
Mean
Median
Standard deviation
Minimum
Maximum
Variance
First quartile
Third quartile
32.
47.000
0.914
0.822
0.511
0.095
2.372
0.261
0.563
1.180
Interpret the variance and standard deviation of these sample data.
ANSWER:
The variance = 0.261 and this represents the average of the squared deviations
from the mean. The standard deviation = 0.511 and is the square root of the
variance. The standard deviation is in minutes (the original units).
33.
Determine the rules of thumb in this case.
ANSWER:
Approximately 68% of the values will fall between 0.914  0.511, that is between
0.403 and 1.425.
Approximately 95% of the values will fall between 0.914  2(0.511), that is
between (-0.108 and 1.936.
Approximately 99.7% of the values will fall between 0.914  3(0.511), that is
between -0.632 and 2.447.
34.
Does it appear as though most of the data falls within 3 standard deviations of the
mean? Explain.
ANSWER:
Since the minimum value is 0.095 and the maximum value is 2.372, then all of the
data falls within three standard deviations of the mean.
42
Describing Data: Summary Measures
35.
Explain what would cause the mean to be higher than the median in this case.
ANSWER:
The data is skewed to the right. This is causing the mean to be higher than the
median. It is important to understand that service times are bounded on the lower
end by zero (or it is impossible for the service time to be negative). However,
there is no bound on the maximum service time. Therefore, the larger service
times are causing the mean to be somewhat higher than the median.
QUESTIONS 36 THROUGH 39 ARE BASED ON THE FOLLOWING INFORMATION:
The percentage of the US population without health insurance coverage is shown below
with samples from the 50 states and District of Columbia for both 1997 and 1998.
State
Alabama
Alaska
Arizona
Arkansas
California
Colorado
Connecticut
Delaware
District of Columbia
Florida
Georgia
Hawaii
Idaho
Illinois
Indiana
Iowa
Kansas
Kentucky
Louisiana
Maine
Maryland
Massachusetts
Michigan
Minnesota
Mississippi
Missouri
% in 97
19.9
14.0
20.9
18.1
21.8
13.1
11.1
14.2
17.1
17.9
16.9
9.9
14.7
12.1
11.2
10.4
13.6
15.9
19.9
13.8
13.3
13.2
11.5
10.2
18.5
12.9
% in 98
14.2
13.2
21.1
18.6
21.3
15.5
9.5
16.4
18.0
19.0
18.6
9.6
14.7
11.7
13.3
12.0
13.1
15.3
21.2
14.2
16.0
11.8
10.4
8.7
20.4
15.3
State
Montana
Nebraska
Nevada
New Hampshire
New Jersey
New Mexico
New York
North Carolina
North Dakota
Ohio
Oklahoma
Oregon
Pennsylvania
Rhode Island
South Carolina
South Dakota
Tennessee
Texas
Utah
Vermont
Virginia
Washington
West Virginia
Wisconsin
Wyoming
43
% in 97
14.3
11.4
16.4
12.6
13.7
23.8
16.7
14.0
9.1
11.7
18.5
13.8
11.3
12.2
14.9
10.7
10.9
24.9
12.2
9.3
12.7
13.4
16.9
9.6
16.1
% in 98
13.4
9.7
19.4
10.7
14.9
26.3
15.9
15.0
9.0
12.6
19.9
13.2
10.6
13.6
15.3
10.1
15.5
25.2
12.4
13.9
14.2
13.1
16.6
8.0
16.6
Chapter 3
36.
Describe the distribution of state percentages of Americans without health
insurance coverage in 1998. Be sure to employ both measures of central location
and dispersion in developing your characterization of this sample.
ANSWER:
Count
Mean
Median
Standard deviation
Minimum
Maximum
First quartile
Third quartile
Skewness
51.000
14.855
14.200
4.098
8.000
26.300
12.200
16.500
0.699
This distribution is slightly skewed to the right, as evidenced by the fact that its
mean (14.855%) exceeds its median (14.2%). The standard deviation of the 1998
distribution is approximately 4.10%.
37.
Compare the 1998 distribution of percentages with the corresponding set of
percentages taken in 1997. How are these two sets similar? In what ways are
they different?
ANSWER:
Count
Mean
Median
Standard deviation
Minimum
Maximum
First quartile
Third quartile
Skewness
Percentage in 97 Percentage in 98
51.000
51.000
14.455
14.855
13.700
14.200
3.724
4.098
9.100
8.000
24.900
26.300
11.600
12.200
16.800
16.500
0.910
0.699
The two distributions are similar in that both are somewhat positively skewed
(even though the 1997 distribution is more skewed than the 1998 distribution).
They are different inasmuch as the 1998 distribution has higher measures of
central location and dispersion than does the 1997 distribution.
44
Describing Data: Summary Measures
38.
Compute a correlation measure for the two given sets of percentages. What does
the correlation tell you in this case?
ANSWER:
Table of correlations
Percent 97
Percent 98
Percent 97
1.000
0.903
Percent 98
1.000
There is a very large positive correlation between these two sets of percentages.
This indicates that the percentages tend to move together, although not perfectly.
39.
Based on your answers to Questions 37 and 38, what would you expect to find
upon analyzing similar data for 1999?
ANSWER:
Based on the answers to Questions 37 and 38 above, it is reasonable to expect that
the percent of the U.S. population without health insurance coverage in 1999 will
be slightly greater than in the previous year. Also, we expect that there will be
greater variability about the mean in 1999 than was the case in 1998.
QUESTIONS 40 THROUGH 43 ARE BASED ON THE FOLLOWING INFORMATION:
Below you will find summary measures on salaries for classroom teachers across the
United States. You will also find a list of selected states and their average teacher salary.
All values are in thousands of dollars.
State
Alabama
Colorado
Connecticut
Delaware
Nebraska
Nevada
New Hampshire
New Jersey
New Mexico
South Carolina
South Dakota
Tennessee
Texas
Utah
Vermont
Virginia
Wyoming
Salary
31.3
35.4
50.3
40.5
31.5
36.2
35.8
47.9
29.6
31.6
26.3
33.1
32.0
30.6
36.3
35.0
31.6
Count
Mean
Median
Standard deviation
Minimum
Maximum
Variance
First quartile
Third quartile
45
Salary
51.000
35.890
35.000
6.226
26.300
50.300
38.763
31.550
40.050
Chapter 3
40.
Which of the states listed paid their teachers average salaries that exceed at least
75% of all average salaries?
ANSWER:
Connecticut at 50.3; Delaware at 40.5; and New Jersey at 47.9 (all those > 40.05).
41.
Which of the states listed paid their teachers average salaries that are below 75%
of all average salaries?
ANSWER:
Alabama at 31.3; Nebraska at 31.5; New Mexico at 29.6; South Dakota at 26.3;
and Utah at 30.6 (all those < 31.55).
42.
What salary amount represents the second quartile?
ANSWER:
$35,000 (median)
43.
How would you describe the salary of Virginia’s teachers compared to those
across the entire United States? Justify your answer.
ANSWER:
Virginia = $35,000 which is also the median. Virginia is at the 50th percentile or
50% of the teachers’ salaries across the U.S. are below Virginia and 50% of the
salaries are above theirs.
QUESTIONS 44 THROUGH 48 ARE BASED ON THE FOLLOWING INFORMATION:
A manager at Abby Technologies, Inc. (ATI) is interested in analyzing the compensation
of employees at her company. ATI currently has 25 employees and below you will find
summary measures for the 25 employees.
Count
Mean
Median
Standard deviation
Minimum
Maximum
Variance
First quartile
Third quartile
25.00
43957.20
42220.00
12478.24
18440.00
71250.00
155706456.42
37250.00
51125.00
46
Describing Data: Summary Measures
44.
Interpret the mean and median values.
ANSWER:
The mean value of $43,957.20 represents the average compensation for the 25
employees. The median value of $42,220.00 represents the 50th percentile or the
second quartile. This means that 50% of the values are below $42,220.
45.
Why is there a difference in the mean and median values? Which of these two
values do you believe is more appropriate in describing this distribution?
ANSWER:
The mean could be somewhat inflated due to one or two large values (such as the
maximum compensation of $71,250). The median may be more appropriate.
46.
Explain what the first quartile and third quartile values represent.
ANSWER:
The first quartile means that 25% of the employees have a compensation package
below $37,250 (also means that 75% of the employees have a compensation
package above this amount). The third quartile means that 75% of the employees
have a compensation package below $51,125 (also means that 25% of the
employees have a compensation package above this amount).
47.
What range of values would contain approximately 95% of the observations?
ANSWER:
Approximately $43,957.20  2(12,478.24) or from $19,000.72 to $68,913.68.
48.
Do any of the values fall outside of the range calculated in Question 47?
ANSWER:
Yes, the minimum value ($18,440) and the maximum value ($71,250) fall outside
of this range.
QUESTIONS 49 THROUGH 55 ARE BASED ON THE FOLLOWING INFORMATION:
The following are two sets of data, each with a sample of size n = 9
Set 1
Set 2
5
15
2
12
4
14
2
12
3
13
47
2
12
10
20
2
12
12
22
Chapter 3
49.
For each data, compute the mean, median, and mode
ANSWER:
Mean
Median
Mode
50.
Set 1
4.667
3
2
Set 2
14.667
13
12
Compare your results in Question 49, and summarize your findings
ANSWER:
The measures of central tendency (mean, median, and mode) for Set 2 are all 10
more than the comparable statistics for Set 1.
51.
Compare the first sampled item in each set, compare the second sampled item in
each set, and so on. Briefly describe your findings in light of your summary in
Question 50.
ANSWER:
The data values in Set 2 are each 10 more than the corresponding values in Set 1. The is
the reason behind the results in Question 50.
52.
For each set, compute the range, interquartile range, variance and standard
deviation.
ANSWER:
Range
Interquartile range
Variance
Standard deviation
53.
Set 1
10
5
14.25
3.7749
Set 2
10
5
14.25
3.7749
Describe the shape of each set.
ANSWER:
Since the mean is greater than the median for each data set, the distributions are
both right-skewed.
54.
Compare your results in Questions 52 and 53, and discuss your findings.
ANSWER:
Because the data values in Set 2 are each 10 more than the corresponding values
in Set 1, the measures of spread among the data values remain the same across the
two sets. Set 2 is a reflection of Set 1 simply shifted up the scale 10 units, so the
distributions are also reflections of each other.
48
Describing Data: Summary Measures
55.
On the basis of your answers to Questions 49 through 54, what can you generalize
about the properties of central tendency, variation, and shape?
ANSWER:
Generally stated, when a second data set is an additive shift from an original set,
the measures of central tendency for the second set are equal to the comparable
measures for the original set plus the value, or distance, of the shift; the measures
of spread for the second set are equal to the corresponding measures for the
original set, and the shape of the second distribution will be a reflection of the
shape of the original distribution.
49
Chapter 3
TRUE / FALSE QUESTIONS
56.
If all values in a data set are negative, the value of the standard deviation may be
either positive or negative.
ANSWER: F
57.
Assume that the histogram of a data set is symmetric and bell shaped, with mean
of 72 and standard deviation of 10. Then, using the “rules of thumb”, we can say
that 95% of the data values were between 52 and 92.
ANSWER: T
58.
If a histogram has a single peak and looks approximately the same to the left and
right of the peak, we should expect no difference in the values of the mean,
median, and mode.
ANSWER: T
59.
The mean is a measure of central location.
ANSWER: T
60.
In a negatively skewed distribution, the mean is larger than the median and the
median is larger than the mode.
ANSWER: F
61.
Since the population is always larger than the sample, the population mean is
always larger than the sample mean.
ANSWER: F
62.
The length of the box in the boxplot portrays the interquartile range.
ANSWER: T
63.
In a positively skewed distribution, the mean is smaller than the median and the
median is smaller than the mode.
ANSWER: F
64.
The interquartile range is considered the weakest measure of central location.
ANSWER: F
65.
The value of the standard deviation always exceeds that of the variance.
ANSWER: F
66.
The difference between the first and third quartiles is called the interquartile
range.
ANSWER: T
50
Describing Data: Summary Measures
67.
The standard deviation is measured in original units, such as dollars and pounds.
ANSWER: T
68.
The median is one of the most frequently used measures of variability.
ANSWER: F
69.
Each of the covariance and correlation measures the strength and direction of a
linear relationship between two numerical variables.
ANSWER: T
70.
Abby has been keeping track of what she spends to rent movies. The last seven
week's expenditures, in dollars, were 6, 4, 8, 9, 6, 12, and 4. The mean amount
Abby spends on renting movies is $7.
ANSWER: T
71.
If two data sets have the same range, the smallest and largest observations in both
sets will be the same
ANSWER: F
72.
The variance is a measure of the linear relationship between two variables
ANSWER: F
73.
Generally speaking, if two variables are unrelated, the covariance will be a
positive or negative number close to zero
ANSWER: T
74.
The correlation between two variables is a unitless quantity that is always
between –1 and +1.
ANSWER: T
75.
The variance is the positive square root of the standard deviation.
ANSWER: F
76.
It is possible that the data points are close to a curve and have a correlation close
to 0, because correlation is relevant only for measuring linear relationships.
ANSWER: T
77.
Expressed in percentiles, the interquartile range is the difference between the 25th
and 75th percentiles.
ANSWER: T
78.
A data sample has a mode 0f 140, a median of 130, and a mean of 120. The
distribution of the data is positively skewed.
ANSWER: F
51
Chapter 3
79.
A student scores 85, 75, and 80 on three exams during the semester and 90 on the
final exam. If the final is weighted double and the three others weighted equally,
the student's final average would be 80.
ANSWER: F
80.
Suppose that a sample of 10 observations has a standard deviation of 3, then the
sum of the squared deviations from the sample mean is 30.
ANSWER: F
81.
The value of the mean times the number of observations equals the sum of all of
the data values.
ANSWER: T
82.
The difference between the largest and smallest values in a data set is called the
range.
ANSWER: T
83.
There are four quartiles that divide the values in a data set into four equal parts.
ANSWER: F
52