The following ratings (R) and observed times (OT) represent the elements from question 1. Using the ratings (R) given below for each observation, determine the normal time (NT) for each element. Using the PD&F allowance factor you developed above from question 1, complete the summary and calculate the elemental standard times for each element. Times are in seconds.
A template (which is optional) is available in the course content page, under the Test 3 module.
Element & Description 
1 
2 
3 
4 
5 

Grab stud gun, shoot 5 pins on buikhead 
Return gun to scaffold, grab and install insulation square 
Grab cutting tool, trim insulation square with structure frame 
Return cutting tool to belt, grab seam tape and apply to bottom joint. 
Grab paint marker, inspect installation, write initials and date installed on panel. 

Cycle 
R 
OT 
NT 
R 
OT 
NT 
R 
OT 
NT 
R 
OT 
NT 
R 
OT 
NT 

1 
105 
11.2 
95 
27.7 
110 
15.0 
100 
15.5 
85 
19.4 

2 
85 
16.2 
100 
24.4 
90 
25.0 
90 
17.8 
100 
14.9 

3 
95 
13.2 
110 
17.9 
100 
21.3 
105 
14.0 
100 
13.9 

4 
120 
9.4 
100 
22.7 
100 
21.8 
100 
14.5 
120 
11.3 

5 
100 
12.4 
90 
29.8 
120 
16.5 
110 
10.6 
95 
15.8 

6 
105 
10.2 
100 
26.3 
105 
18.0 
95 
16.5 
100 
14.5 

7 
100 
10.8 
100 
21.4 
100 
21.8 
120 
11.8 
100 
15.0 

8 
90 
14.2 
100 
26.0 
100 
20.4 
100 
12.8 
100 
13.4 

9 
100 
11.6 
100 
23.5 
85 
28.5 
100 
15.6 
100 
12.2 

10 
100 
12.5 
85 
34.0 
100 
22.0 
105 
12.8 
100 
14.9 

11 
110 
8.5 
120 
19.7 
95 
23.2 
100 
14.0 
105 
12.2 

12 
100 
10.2 
105 
21.4 
105 
19.7 
100 
13.5 
90 
17.0 

13 
100 
11.2 
100 
26.0 
100 
19.0 
100 
15.1 
110 
10.2 

14 
100 
12.4 
100 
25.4 
100 
18.0 
85 
20.3 
105 
13.4 

15 
100 
12.1 
105 
23.5 
100 
19.7 
100 
15.5 
100 
13.0 

Summary 

Total OT 

Total NT 

Number of Cycles 

Average NT 

% Allowance 

Elemental Standard time 
In: Math
Q#1
The amounts of time employees of a telecommunications company have worked for the company are normally distributed with a mean of 5.10 years and a standard deviation of 2.00 years. Random samples of size 12 are drawn from the population and the mean of each sample is determined. Round the answers to the nearest hundredth.
Q#2
A coffee machine dispenses normally distributed amounts of coffee with a mean of 12 ounces and a standard deviation of 0.2 ounce. If a sample of 9 cups is selected, find the probability that the mean of the sample will be less than 12.1 ounces. Find the probability if the sample is just 1 cup.
In: Math
Here is a census for an apportionment problem in a hypothetical country comprised of four states. • State of Ambivalence: 8,000; • State of Boredom: 9,000; • State of Confusion: 24,000; • State of Depression: 59,000. (100,000 total) Assume that the house has h = 10 seats to apportion to these four states. What apportionment is determined by the method of: Hamilton, Adam, Jefferson, Webster.
In: Math
In: Math
Soma recorded in the table the height of each player on the basketball team
Basketball Players’ Heights (in inches) 

66 
66 
68 
57 
64 
65 
67 
67 
64 
65 
Construct a normal probability distribution curve for this population! Indicate the number for the mean, 1SD, 2SD and 3SD (both sides of the mea) (1+ 6*0.5=4p)
In: Math
1. A random sample of 4040 cars owned by students had a mean age
of 7.37.3 years and a standard deviation of 3.73.7 years, while a
random sample of 2828 cars owned by faculty have a mean age of
5.85.8 years and a standard deviation of 3.53.5 years.
Use a 0.10.1 significance level to test the claim
that, on average, cars owned by students are older than cars owned
by faculty.
The test statistic is ______________
The pvalue is _______________
2. Ten randomly selected people took IQ test A, and next day they took a very similar IQ test B. Their scores are shown in the table below.
Person  A  B  C  D  E  F  G  H  I  J 
Test A  101  118  71  86  129  108  109  96  91  93 
Test B  103  115  69  85  130  109  112  97  89  92 
Calculate (Test B  Test A) to find the differences. Use a 0.010.01
significance level to test the claim that people do better on the
second test than they do on the first.
(b) The test statistic is ___________
(c) The pvalue is _______________
3. 2.38866e05
Jaylon thinks that there is a difference in quality of life between
rural and urban living. He collects information from obituaries in
newspapers from urban and rural towns in Kansas to see if there is
a difference in life expectancy. A sample of 20 people from rural
towns give a life expectancy of xr¯=80.9xr¯=80.9
years with a standard deviation of sr=6.5sr=6.5
years. A sample of 30 people from larger towns give
xu¯=72.4xu¯=72.4 years and
su=5.3su=5.3 years. Does this provide evidence
that people living in rural Kansas communities have, on average,
different life expectancy than those in more urban communities? Use
a 5 % level of significance. Let uu represent urban and
rr represent rural.
(b) The test statistic is ________________
(c) The pvalue is ___________________
In: Math
Do workers prefer to buy lunch rather than pack their own lunch? A survey of employed Americans found that 75% of the 18 to 24 yearolds, 77% of the 25 to 34 yearolds, 72% of the 35 to 44 yearolds, 58% of the 45 to 54 yearolds, 57% of the 55 to 64 yearolds, and 55% of the 65 + yearolds buy lunch throughout the workweek. Suppose the survey was based on 200 employed Americans in each of six age groups.
a. At the 0.05 level of significance, is there evidence of a difference among the age groups in the preference for buying lunch?
b. Determine the pvalue in (a) and interpret its meaning.
In: Math
A survey of the mean number of cents off that coupons give was conducted by randomly surveying one coupon per page from the coupon sections of a recent San Jose Mercury News. The following data were collected: 20¢; 75¢; 50¢; 65¢; 30¢; 55¢; 40¢; 40¢; 30¢; 55¢; $1.50; 40¢; 65¢; 40¢. Assume the underlying distribution is approximately normal.
Construct a 95% confidence interval for the population mean worth of coupons. Use a critical value of 2.16 from the t distribution.
In: Math
You randomly select 20 coffee shops and measure the temperature of the coffee sold at each. The sample mean temperature is 162.0ºF with a sample standard deviation of 10.0ºF. Assume the temperatures are approximately normally distributed. Find the test statistic to test if population average temperature of the coffee is different than 163.5 F.
Solve using R
In: Math
1  49.67 
2  30.14 
3  18.83 
4  22.67 
5  50.09 
6  89.11 
7  79.95 
8  49.19 
9  70.29 
10  57.92 
11  53.37 
12  22.44 
13  29.91 
14  72.20 
15  42.63 
16  83.28 
17  18.02 
18  76.63 
19  89.25 
20  19.48 
21  12.33 
22  72.71 
23  46.25 
24  31.58 
25  36.24 
26  32.19 
27  65.90 
28  40.32 
29  64.30 
30  59.03 
31  44.74 
32  86.43 
33  12.66 
34  28.66 
35  67.27 
36  56.42 
37  87.76 
38  36.30 
39  86.69 
40  23.34 
41  96.76 
42  85.48 
43  87.58 
44  47.26 
45  68.13 
46  73.56 
47  90.61 
48  58.80 
49  99.11 
50  13.87 
51  54.05 
52  57.91 
53  39.68 
54  72.75 
55  29.89 
56  11.72 
57  79.42 
58  35.75 
59  35.44 
60  47.51 
61  84.39 
62  49.04 
63  62.55 
64  41.23 
65  66.10 
66  91.06 
67  47.32 
68  67.71 
69  73.65 
70  94.65 
71  73.05 
72  46.01 
73  23.01 
74  31.65 
75  57.84 
76  72.30 
77  54.58 
78  30.61 
79  96.07 
80  52.86 
81  31.36 
82  42.77 
83  10.14 
84  32.26 
85  45.10 
86  33.71 
87  54.59 
88  74.71 
89  47.22 
90  25.29 
91  59.88 
92  62.41 
93  94.63 
94  38.03 
95  57.27 
96  10.73 
97  57.72 
98  24.58 
99  79.24 
100  18.83 
Either copy & paste each answer from your data sheet, or round your answers to two decimal places where applicable.
Mean
Standard Error
Median
Mode (report #N/A if no mode)
Standard Deviation
Sample Variance
Kurtosis
Skewness
Range
Minimum/smallest
Maximum/Largest
Sum
Count
Did you notice the mistake in the video while using the data analysis tool? The data range to B1:B100 was selected instead of B1:B101 so there were only 99 values for the Count when the data analysis tool ran. Be sure not to make the same mistake.
In: Math
The NBS television network earns an average of $400,000 from a hit show and loses an average
of $100,000 on a flop. Of all shows reviewed by the network, 25% turn out to be hits and 75%
turn out to be flops. For $40,000, a market research firm will have an audience view a pilot of a
prospective show and give its view about whether a show will be a hit or a flop. If a show is
actually going to be a hit, there is a 90% chance that the market research firm will predict the
show to be a hit. If the show is actually going to be a flop, there is an 80% chance that the
market research firm will predict the show to be a flop. Determine how the network can
maximize its expected profits by doing the following:
a. Construct the decision tree.
b. What would be the expected profit if the market research firm is hired?
In: Math
A. According to an airline, flights on a certain route are NOT on time 15% of the time. Suppose 10 flights are randomly selected and the number of NOT on time flights is recorded. Find the probability of the following question. At least 3 flights are not on time.
B. According to an airline, flights on a certain route are NOT on time 15% of the time. Suppose 10 flights are randomly selected and the number of NOT on time flights is recorded. Find the probability of the following question. At the most 8 flights are on time.
c. According to an airline, flights on a certain route are NOT on time 15% of the time. Suppose 10 flights are randomly selected and the number of NOT on time flights is recorded. Find the probability of the following question. In between 6 and 9 flights are on time.
In: Math
Consider the following allinteger linear program:
Max 
x_{1} + x_{2} 
s.t. 

4x_{1} + 6x_{2} ≤ 22 

x_{1} + 5x_{2} ≤ 15 

2x_{1} + x_{2} ≤ 9 

x_{1}, x_{2} ≥ 0 and integer 
In: Math
A steel company is considering the relocation of one of its manufacturing plants. The company’s executives have selected four areas that they believe are suitable locations. However, they want to determine if the average wages are significantly different in any of the locations, since this could have a major impact on the cost of production. A survey of hourly wages of similar workers in each of the four areas I performed with the following results.
Hourly Wages ($) 

Area 1 
Area 2 
Area 3 
Area 4 

1 
11 
15 
13 
20 
2 
12 
16 
14 
16 
3 
11 
18 
15 
18 
4 
13 
17 
15 
17 
5 
10 
14 
12 
16 
a. Do the data indicate a significant difference among the average hourly wages in the four areas? Construct the 10 steps of hypothesis testing using α = 0.05 to answer the question.
b. What assumptions were mad in performing the test in part a? Do the data appear to satisfy these assumptions? Explain.
In: Math
Problem 2: (Revised 6.3) Magazine Advertising: In a study of revenue from advertising, data were collected for 41 magazines list as follows. The variables observed are number of pages of advertising and advertising revenue. The names of the magazines are listed as:
Here is the code help you to paste data into your R:
data6<'Adv Revenue
25 50
15 49.7
20 34
17 30.7
23 27
17 26.3
14 24.6
22 16.9
12 16.7
15 14.6
8 13.8
7 13.2
9 13.1
12 10.6
1 8.8
6 8.7
12 8.5
9 8.3
7 8.2
9 8.2
7 7.3
1 7
77 6.6
13 6.2
5 5.8
7 5.1
13 4.1
4 3.9
6 3.9
3 3.5
6 3.3
4 3
3 2.5
3 2.3
5 2.3
4 1.8
4 1.5
3 1.3
3 1.3
4 1
2 0.3
'
data6n<read.table(textConnection(object=data6),
header=TRUE,
sep="",
stringsAsFactors = FALSE)
a. You should not be surprised by the presence of a large number of outliers because the magazines are highly heterogeneous and it is unrealistic to expect a single relationship to connect all of them. Find outliers and high leverage points. Delete the outliers and obtain an acceptable regression equation that relates advertising revenue to advertising pages.
b. For the deleted data, check the homogeneity of the variance. Choose an appropriate transformation of the data and fit the model to the transformed data. Evaluate the fit.
In: Math