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Test Bank For Probability and Statistics for Engineering and the Sciences 9th Edition By Jay L. Devore, Matt Carlton|9781305251809| All Chapters included| LATEST $18.49   Add to cart

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Test Bank For Probability and Statistics for Engineering and the Sciences 9th Edition By Jay L. Devore, Matt Carlton|9781305251809| All Chapters included| LATEST

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Test Bank For Probability and Statistics for Engineering and the Sciences 9th Edition By Jay L. Devore, Matt Carlton|9781305251809| All Chapters included| LATEST

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  • November 12, 2024
  • 268
  • 2024/2025
  • Exam (elaborations)
  • Questions & answers
  • 9th edition
  • 9781305251809
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TestBank ForProbabilityAnd Statistics For Engineering And
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The Sciences 8th Ed by Jay L. Devore. ll ll ll ll ll ll ll ll




Chapter 1 – Overview and Descriptive Statistics
ll ll ll ll ll ll




SHORT ANSWER
ll




1. Give one possible sample of size 4 from each of the following populations:
ll ll ll ll ll ll ll ll ll ll ll ll

a. All daily newspapers published in the United States
ll ll ll ll ll ll ll

b. All companies listed on the New York Stock Exchange
ll ll ll ll ll ll ll ll

c. All students at your college or university ll ll ll ll ll ll

d. All grade point averages of students at your college or university
ll ll ll ll ll ll ll ll ll ll




ANS:

a. Houston Chronicle, Des Moines Register, Chicago Tribune, Washington Post
ll ll ll ll ll ll ll ll

b. Capital One, Campbell Soup, Merrill Lynch, Pulitzerll ll ll ll ll ll

c. John Anderson, Emily Black, Bill Carter, Kay Davis
ll ll ll ll l l ll ll

d. 2.58. 2.96, 3.51, 3.69 ll ll ll




PTS: l l l l 1

2. A Southern State University system consists of 23 campuses. An administrator wishes to make an inference
ll ll ll ll ll ll ll ll ll ll ll ll ll ll ll

about the average distance between the hometowns of students and their campuses. Describe and discuss several
ll ll ll ll ll ll ll ll ll ll ll ll ll ll ll ll

different sampling methods that might be employed. Would this be an enumerative or an analytic study?
ll ll ll ll ll ll ll ll ll ll ll ll ll ll ll ll

Explain your reasoning.
ll ll ll




ANS:
One could take a simple random sample of students from all students in the California State University system and
ll ll ll ll ll ll ll ll ll ll ll ll ll ll ll ll ll ll

ask each student in the sample to report the distance from their hometown to campus. Alternatively, the sample
ll ll ll ll ll ll ll ll ll ll ll ll ll ll ll ll ll ll

could be generated by taking a stratified random sample by taking a simple random sample from each of the 23
ll ll ll ll ll ll ll ll ll ll ll ll ll ll ll ll ll ll ll ll

campuses and again asking each student in the sample to report the distance from their hometown to campus.
ll ll ll ll ll ll ll ll ll ll ll ll ll ll ll ll ll ll

Certain problems might arise with self reporting of distances, such as recording error or poor recall. This study is
ll ll ll ll ll ll ll ll ll ll ll ll ll ll ll ll ll ll

enumerative because there exists a finite, identifiable population of objects from which to sample.
ll ll ll ll ll ll ll ll ll ll ll ll ll ll




PTS: l l l l 1

3. A Michigan city divides naturally into ten district neighborhoods. How might a real estate appraiser select a
ll ll ll ll ll ll ll ll ll ll ll ll ll ll ll ll

sample of single-family homes that could be used as a basis for developing an equation to predict appraised
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value from characteristics such as age, size, number of bathrooms, and distance to the nearest school, and so
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on? Is the study enumerative or analytic?
ll l l ll ll ll ll ll




ANS:

One could generate a simple random sample of all single family homes in the city or a stratified random sample by
ll ll ll ll ll ll ll ll ll ll ll ll ll ll ll ll ll ll ll ll

taking a simple random sample from each of the 10 district neighborhoods. From each of the homes in the
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sample the necessary variables would be collected. This would be an enumerative study because there exists a
ll ll ll ll ll ll ll ll ll ll ll ll ll ll ll ll ll

finite, identifiable population of objects from which to sample.
ll ll ll ll ll ll ll ll ll

, PTS: l l l l 1

4. An experiment was carried out to study how flow rate through a solenoid valve in an automobile‘s pollution-
ll ll ll ll ll ll ll ll ll ll ll ll ll ll ll ll ll

control system depended on three factors: armature lengths, spring load, and bobbin depth. Two different
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levels (low and high) of each factor were chosen, and a single observation on flow was made for each
ll ll ll ll ll ll ll ll ll ll ll ll ll ll ll ll ll ll ll

combination of levels.
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a. The resulting data set consisted of how many observations?
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b. Is this an enumerative or analytic study? Explain your reasoning.
ll ll ll ll ll ll ll ll ll




ANS:
a. Number observations equal 2 2 2=8 ll ll ll ll l l ll l l

b. This could be called an analytic study because the data would be collected on an existing
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process. There is no sampling frame.
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PTS: l l l l 1

5. The accompanying data specific gravity values for various wood types used in construction .
ll ll ll ll ll ll ll ll ll ll ll ll ll




.41 .41 .42 .42. .42 .42 .42 .43 .44
.54 .55 .58 .62 .66 .66 .67 .68 .75
.31 .35 .36 .36 .37 .38 .40 .40 .40
.45 .46 .46 .47 .48 .48 .48 .51 .54

Construct a stem-and-leaf display using repeated stems and comment on any interesting features of the display.
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ANS:
One method of denoting the pairs of stems having equal values is to denote the stem by L, for ‗low‘ and the second
ll ll ll ll ll ll ll ll ll ll ll ll ll ll ll ll ll ll ll ll ll ll

stem by H, for ‗high‘. Using this notation, the stem-and-leaf display would appear as follows:
ll ll ll ll ll l l ll ll ll ll ll ll ll ll ll




3L 1 stem: tenths ll

3H 56678 leaf: l l hundredths
4L 000112222234
5L 144
5H 58
6L 2
6H 6678
7L
7H 5

The stem-and-leaf display on the previous page shows that .45 is a good representative value for the data. In
ll ll ll ll ll ll ll ll ll ll ll ll ll ll ll ll ll l l

addition, the display is not symmetric and appears to be positively skewed. The spread of the data is .75 - .31 =
ll ll ll ll ll ll ll ll ll ll ll ll l l ll ll ll ll ll ll ll ll ll

.44, which is .44/.45 = .978 or about 98% of the typical value of .45. This constitutes a reasonably large
ll ll ll ll ll ll ll ll ll ll ll ll ll ll ll l l ll ll ll ll

amount of variation in the data. The data value .75 is a possible outlier.
ll ll ll ll ll ll l l ll ll ll ll ll ll ll




PTS: l l l l 1

6. Temperature transducers of a certain type are shipped in batches of 50. A sample of 60 batches was selected,
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and the number of transducers in each batch not conforming to design specifications was determined,
ll ll ll ll ll ll ll ll ll ll ll ll ll ll ll

resulting in the following data:
ll ll ll ll ll




0 4 l l l l 2 l l 1 1 3 4 1 2 3 2 2 8 4 5 1 3 1
l l 1 l l l l 3
2 1 l l l l 2 l l 1 3 2 0 5 3 3 1 3 2 4 7 0 2 3
l l 4 l l l l 0
5 0 l l l l 2 l l 1 0 6 4 2 1 6 0 3 3 3 6 1 2 3
l l 3 l l l l 2

, a. Determine frequencies and relative frequencies for the observed values of x = number of
ll nonconforming ll ll ll ll ll ll ll ll ll ll ll ll

transducers in a batch.
ll ll ll ll

b. What proportion of batches in the sample has at most four nonconforming transducers? What proportion
ll ll ll ll ll ll ll ll ll ll ll ll ll ll

has fewer than four? What proportion has at least four nonconforming units?
ll ll ll ll ll ll ll ll ll ll ll ll




ANS:

a.
Number Nonconforming Relative Frequency ll Frequency ll


0 0.117 7
1 0.200 12
2 0.217 13
3 0.233 14
4 0.100 6
5 0.050 3
6 0.050 3
7 0.017 1
8 0.017 1
1.001
The relative frequencies don’t add up exactly to 1because they have been rounded
ll l l ll ll ll ll ll ll ll ll ll ll




b. The number of batches with at most 4 nonconforming items is 7+12+13+14+6=52, which is a proportion of
ll ll ll ll ll ll ll ll ll ll ll ll ll ll ll ll ll

52/60=.867. The proportion of batches with (strictly) fewer than 4 nonconforming items is 46/60=.767.
ll ll ll ll ll ll ll ll ll ll ll ll ll ll




PTS: l l l l 1

7. The number of contaminating particles on a silicon wafer prior to a certain rinsing process was determined for
ll ll ll ll ll ll ll ll ll ll ll ll ll ll ll ll ll

each wafer in a sample size 100, resulting in the following frequencies:
ll ll ll ll ll ll ll ll ll ll ll ll




Number of particles ll l l Frequency Number of particles ll l l Frequency
0 1 8 12
1 2 9 4
2 3 10 5
3 12 11 3
4 11 12 1
5 15 13 2
6 18 14 1
7 10


a. What proportion of the sampled wafers had at least two particles? At least six particles?
ll ll ll ll ll ll ll ll ll ll ll ll ll ll

b. What proportion of the sampled wafers had between four and nine particles, inclusive? Strictly between four
ll ll ll ll ll ll ll ll ll ll ll ll ll ll ll

and nine particles?
ll ll ll




ANS:
a. From this frequency distribution, the proportion of wafers that contained at least two particles is (100-1-2)/100 =
ll ll ll ll ll ll ll ll ll ll ll ll ll ll ll ll

.97, or 97%. In a similar fashion, the proportion containing at least 6 particles is (100 – 1-2-3-12-11-15)/100
ll ll ll ll ll ll ll ll ll ll ll ll ll ll ll ll ll

= 56/100 = .56, or 56%.
ll ll ll ll ll ll

b. The proportion containing between 4 and 9 particles inclusive is (11+15+18+10+12+4)/100 = 70/100 = .70,
ll ll ll ll ll ll ll ll ll ll ll ll ll ll

or 70%. The proportion that contain strictly between 4 and 9 (meaning strictly more than 4 and strictly less
ll ll ll ll ll ll ll ll ll ll ll ll ll ll ll ll ll ll ll

than 9) is (15+ 18+10+12)/100= 55/100 = .55, or 55%.
ll ll ll ll ll ll ll ll ll ll

, PTS: l l l l 1

8. The cumulative frequency and cumulative relative frequency for a particular class interval are the sum of
ll ll ll ll ll ll ll ll ll ll ll ll ll ll ll

frequencies and relative frequencies, respectively, for that interval and all intervals lying below it. Compute
ll ll ll ll ll ll ll ll ll ll ll ll ll ll ll

the cumulative frequencies and cumulative relative frequencies for the following data:
ll ll ll ll ll ll ll ll ll ll ll




75 89 80 93 64 67 72 70 66 85
89 81 81 71 74 82 85 63 72 81
81 95 84 81 80 70 69 66 60 83
85 98 84 68 90 82 69 72 87 88

ANS:

Class Frequency Relative Cumulative Cumulative
ll Frequency Frequency
ll Relative
ll

Frequency
ll

60 – under 65 ll ll ll 3 .075 3 .075
65 – under 70 ll ll ll 6 .15 9 .225
70 – under 75 ll ll ll 7 .175 16 .40
75 – under 80 ll ll ll 1 .025 17 .425
80 – under 85 ll ll ll 12 .30 29 .725
85 – under 90 ll ll ll 7 .175 36 .90
90 – under 95 ll ll ll 2 .05 38 .95
95 – under 100 ll ll ll 2 .05 40 1.0

PTS: l l l l 1

9. Consider the following observations on shear strength of a joint bonded in a particular manner:
ll ll ll ll ll ll ll ll ll ll ll ll ll ll




30.0 4.4 33.1 66.7 81.5 22.2 40.4 16.4 73.7 36.6 109.9

a. Determine the value of the sample mean. ll ll ll ll ll ll

b. Determine the value of the sample median. Why is it so different from the mean?
ll ll ll ll ll ll ll ll ll ll ll ll ll ll

c. Calculate a trimmed mean by deleting the smallest and largest observations. What is the
ll ll ll ll ll ll ll ll ll ll ll ll ll


ll corresponding trimming percentage? How does the value of this ll ll ll ll ll ll ll ll l l ll compare to the mean and ll ll ll ll


ll median?

ANS:
a. The sum of the n = 11 data points is 514.90, so
ll ll = 514.90/11 = 46.81.
ll ll ll ll ll ll ll ll ll l l l l ll ll ll

b. The sample size (n = 11) is odd, so there will be a middle value. Sorting from smallest to largest: 4.4 16.4
ll ll ll ll ll ll ll ll ll ll ll ll ll ll ll ll ll ll ll ll l l

22.2
l l

30.0 33.1 36.6 40.4 66.7 73.7 81.5 109.9. The sixth value, 36.6 is the middle, or median, value. The
l l l l l l l l l l l l l l ll ll ll ll ll ll ll ll ll ll ll

mean differs from the median because the largest sample observations are much further from the median than
ll ll ll ll ll ll ll ll ll ll ll ll ll ll ll ll ll

are the smallest values.
ll ll ll ll

c. Deleting the smallest (x = 4.4) and largest (x = 109.9) values, the sum of the remaining 9 observations is
ll ll ll ll ll ll ll ll ll ll ll ll ll ll ll ll ll ll ll


400.6. The trimmed mean
ll is 400.6/9 = 44.51. The trimming percentage is 100(1/11) = 9.1%.
ll ll ll l l l l ll ll ll ll ll ll ll ll ll ll l l


lies between the mean and median.
l l ll ll ll ll ll




PTS: l l l l 1

10. A sample of 26 offshore oil workers took part in a simulated escape exercise, resulting in the accompanying data
ll ll ll ll ll ll ll ll ll ll ll ll ll ll ll ll ll ll

on time (sec) to complete the escape:
ll ll ll ll ll ll ll




373 370 364 366 364 325 339 393
356 359 363 375 424 325 394 402

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