ArmCo Company initiated an employee empowerment program (in which employee feedback are collected and responded by the management on a regular basis). The Company wishes to find out if employees at all five of its plants --- in the South, Midwest, Northeast, Southwest,and West --- have equally positive perceptions towards the empowerment program.Random samples of employees at the five plants were asked to rate the success of the empowerment program on a scale of 1 to 10, 10 being the most favorable rating. The collected data is shown to the right. Use Alpha = .05
1: What is the Null Hypothesis (select one)?
2. From the ANOVA table, what is the p-value?
3. From ANOVA table, what is F-statistics for the data?
4. From ANOVA table, what is F-critical?
5. Based on the ANOVA table, what is your decision?
6. Is there any indication of differences in mean ratings across the plants?
Empowerment Ratings from Five Plants
South Midwest Northeast
Southwest West
7 7
7
6 6
1 6
5
9 6
8 10
5
7 6
7 3
5
4 6
2 9
4
7 3
9 10
3
6 4
3 8
4
6 8
8 4
5
7 6
4 9
5
7 6
7 9
1
6 6
6 7
3
6 1
7 6
3
6 6
3 6
7
7 5
8 4
3
6 6
6 6
6
5 5
6 9
3
7 5
2 6
5
8 5
3 5
6
6 4
6 5
3
7 3
8 1
7
5 3
7 6
5
8 6
4 3
1
6 6
3 4
3
7 6
3 4
4
6 5
5 4
1
7 9
6 4
3
8 8
7 7
4
3 4
9 4
6
4 5
9 4
6
6 5
5 4
7
7 5
4 2
2
4 5
5 5
6
6 2
3 2
5
7 1
7 8
7
7 5
5 3
5
4 2
7 2
8
3 4
4 7
9
7 5
7
10
8 6
5
5
9 4
10
5
4 7
10
4
4
6
2
3
3
4
5
5
6
4
2
7
6
6
4
4
5
2
7
8
7
In: Statistics and Probability
Construct the following network(AOA) and determine the minimum total cost to complete the project if indirect cost is Rs.1500 per day.
|
Activity |
NT |
CT |
NC |
CC |
|
1-2 |
6 |
4 |
6000 |
7800 |
|
1-3 |
7 |
4 |
3000 |
4200 |
|
2-3 |
4 |
1 |
5000 |
9200 |
|
2-5 |
6 |
5 |
6000 |
7500 |
|
3-4 |
7 |
3 |
2000 |
6800 |
|
4-5 |
3 |
1 |
2000 |
4000 |
|
4-6 |
7 |
3 |
4000 |
5600 |
|
5-6 |
5 |
4 |
3000 |
4100 |
In: Operations Management
ABC Company has the following asset on its books: Using the double declining balance depreciation method, what is the depreciation expense in years 1 through 4.
Truck cost 31,000
Salvage value 1,000
Estimated life in years 4
Estimated life in miles 100,000
Miles driven in years 1 = 25,000, year 2 = 20,000, year 3 = 33,000, year 4 = 24,000
Question 9 options:
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In: Accounting
Topic: Developing an Ethical Organizational Culture:
critically review Apple Inc. culture related to ethics and. Complete the following table by selecting Five behaviors per category
IMPORTANT: structure to answer: Introduce Organization. Consider answers that can improve leadership agility in support of an ethical organizational culture. Conclude on effectiveness of Ethical Culture
|
Categories |
Action behaviors |
|
Need to stop doing? |
1 2 3 4 5 |
|
Need to start doing? |
1 2 3 4 5 |
|
Need to continue doing? |
1 2 3 4 5 |
|
Need to do more of? |
1 2 3 4 5 |
|
Need to do less of? |
1 2 3 4 5 |
In: Economics
A travel agent (TA) in Athens named “Thomas o Mageiras” has
contracts with 135
hotels from all categories (stars) in the three major Greek summer
destinations,
namely Crete, Ionian Islands and South Aegean Islands. In order to
better support its
clients the TA yearly collects and updates data regarding the
performance of these
hotels.
The dataset in the table that follows, provides various measures
of
all 135 hotels, summarized in the following variables:
Variables Description
STARS Hotel class category
Total_Rooms Total number of rooms per hotel
Region_ID
1= Crete
2=Southern Aegean Islands
3=Ionian Islands
ARR_MAY Average Room Rate in May (in €)
ARR_AUG Average Room Rate in August (in €)
L_COST Labor cost per hotel (in €)
Note: The empty cells in the given Excel spreadsheet indicate
missing values.
Question 1:
1.1 Construct the frequency distribution, the percentage
distribution and the frequency
histogram of the variables ARR_MAY and ARR_AUG for ALL 135 hotels.
Use
the same class width = 25 for both frequency distributions. Comment
on the
characteristics of the distributions.
1.2 Construct separately, the frequency distributions and the
percentage distributions
of the variable ARR_AUG for each of the three destinations. Use the
same class
width = 35 for each of the three frequency distributions.
1.3 Construct separately, the frequency distributions and the
percentage distributions
of the variable ARR_MAY for hotels with a) Number of rooms ≤ 50
considered
as small size hotels b) Number of rooms > 50 considered as large
size hotels. Use
the same class width = 25 for both frequency distributions.
1.4 Plot three histograms of the frequency distributions of the
variable ARR_AUG,
one for each of the three destinations, and comment on the main
characteristics of
the three distributions.
1.5 Plot two histograms of frequency distributions of the variable
ARR_MAY, one
for the small and one for the large size hotels, and comment on the
main
characteristics of the two distributions.
1.6 What conclusions can you reach concerning the differences in
distribution a) of
ARR_AUG among the three destinations and b) of ARR_MAY between
the
small and the large size hotels?
| STARS | Total_Rooms | Region_ID | ARR_MAY | ARR_AUG | L_COST |
| 1 | 44 | 2 | 16 | 35 | |
| 1 | 18 | 2 | 16 | 20 | |
| 1 | 21 | 3 | 16 | 40 | 30.000 |
| 1 | 21 | 3 | 16 | 40 | 20.000 |
| 1 | 31 | 2 | 18 | 35 | 10.450 |
| 2 | 32 | 3 | 19 | 45 | 6.500 |
| 1 | 46 | 3 | 19 | 23 | 43.549 |
| 4 | 38 | 1 | 22 | 51 | 59.200 |
| 2 | 73 | 2 | 22 | 41 | 70.000 |
| 4 | 65 | 1 | 25 | 63 | 83.000 |
| 3 | 122 | 2 | 25 | 33 | 568.536 |
| 1 | 16 | 2 | 25 | 70 | 379.498 |
| 1 | 13 | 3 | 25 | 45 | 15.000 |
| 1 | 16 | 3 | 25 | 31 | 27.084 |
| 2 | 29 | 1 | 26 | 44 | 30.000 |
| 2 | 42 | 2 | 28 | 40 | |
| 2 | 17 | 1 | 29 | 53 | 6.121 |
| 1 | 23 | 1 | 30 | 35 | 50.237 |
| 2 | 30 | 2 | 30 | 55 | 40.000 |
| 2 | 15 | 2 | 30 | 45 | 4.296 |
| 1 | 11 | 2 | 30 | 50 | |
| 1 | 22 | 2 | 30 | 35 | 1.520 |
| 3 | 39 | 3 | 30 | 68 | 50.000 |
| 3 | 32 | 3 | 30 | 100 | 40.000 |
| 2 | 49 | 3 | 30 | 73 | 41.000 |
| 1 | 13 | 3 | 30 | 50 | 9.500 |
| 1 | 21 | 3 | 30 | 40 | 10.000 |
| 1 | 8 | 1 | 31 | 49 | 7.888 |
| 2 | 25 | 3 | 32 | 55 | 61.766 |
| 1 | 57 | 1 | 35 | 90 | 11.720 |
| 1 | 20 | 1 | 35 | 45 | |
| 1 | 18 | 1 | 35 | 40 | 112.181 |
| 2 | 26 | 1 | 35 | 40 | 3.575 |
| 2 | 37 | 2 | 35 | 95 | 270.000 |
| 2 | 14 | 3 | 35 | 70 | 5.500 |
| 3 | 98 | 2 | 38 | 75 | 150.000 |
| 3 | 44 | 2 | 38 | 84 | 75.704 |
| 3 | 75 | 1 | 40 | 60 | 37.735 |
| 3 | 32 | 1 | 40 | 60 | 3.500 |
| 2 | 23 | 1 | 40 | 50 | 6.500 |
| 1 | 11 | 1 | 40 | 55 | |
| 1 | 15 | 1 | 40 | 55 | 3.500 |
| 3 | 23 | 1 | 40 | 55 | |
| 3 | 10 | 2 | 40 | 70 | 10.000 |
| 1 | 22 | 2 | 40 | 100 | 20.000 |
| 1 | 12 | 2 | 40 | 65 | |
| 4 | 112 | 3 | 40 | 56 | 363.825 |
| 3 | 72 | 3 | 40 | 75 | 177.833 |
| 1 | 21 | 1 | 42 | 54 | 5.700 |
| 5 | 378 | 3 | 44 | 128 | 2.429.367 |
| 2 | 68 | 1 | 45 | 55 | 199.000 |
| 3 | 75 | 2 | 45 | 70 | 220.000 |
| 3 | 62 | 2 | 45 | 90 | 50.302 |
| 3 | 25 | 2 | 45 | 95 | 118.049 |
| 2 | 15 | 1 | 47 | 50 | 19.670 |
| 4 | 221 | 2 | 47 | 102 | 623.117 |
| 3 | 27 | 1 | 48 | 55 | 20.906 |
| 4 | 117 | 2 | 48 | 91 | 360.000 |
| 3 | 62 | 3 | 50 | 90 | 252.390 |
| 3 | 30 | 3 | 50 | 80 | 45.000 |
| 2 | 41 | 3 | 50 | 90 | 166.903 |
| 2 | 14 | 3 | 50 | 80 | 4.000 |
| 3 | 66 | 1 | 51 | 65 | 230.000 |
| 2 | 48 | 1 | 52 | 60 | 284.569 |
| 2 | 39 | 1 | 53 | 104 | 107.447 |
| 3 | 102 | 3 | 53 | 91 | 173.481 |
| 4 | 62 | 2 | 55 | 75 | 249.205 |
| 2 | 21 | 2 | 55 | 100 | 12.000 |
| 2 | 53 | 3 | 55 | 80 | 48.200 |
| 4 | 10 | 1 | 57 | 97 | 30.000 |
| 4 | 70 | 1 | 59 | 128 | 437.684 |
| 1 | 25 | 1 | 59 | 128 | 156.316 |
| 3 | 69 | 1 | 60 | 70 | 256.658 |
| 3 | 47 | 1 | 60 | 120 | 255.020 |
| 3 | 170 | 2 | 60 | 104 | 538.848 |
| 2 | 18 | 2 | 60 | 100 | 10.000 |
| 5 | 270 | 3 | 60 | 90 | 1.934.820 |
| 5 | 240 | 2 | 61 | 132 | 1.312.601 |
| 4 | 241 | 1 | 64 | 109 | 793.009 |
| 4 | 121 | 1 | 64 | 132 | 494.566 |
| 3 | 54 | 1 | 65 | 90 | 200.000 |
| 4 | 172 | 1 | 68 | 148 | 1.383.854 |
| 5 | 57 | 2 | 68 | 140 | 300.000 |
| 4 | 227 | 3 | 69 | 123 | 1.538.000 |
| 4 | 322 | 1 | 70 | 159 | 1.608.013 |
| 4 | 27 | 1 | 70 | 100 | 130.000 |
| 2 | 10 | 2 | 70 | 100 | 12.500 |
| 4 | 56 | 3 | 70 | 100 | 96.000 |
| 3 | 78 | 3 | 70 | 120 | 377.182 |
| 2 | 24 | 3 | 70 | 120 | 116.056 |
| 2 | 20 | 3 | 70 | 120 | 96.713 |
| 5 | 133 | 1 | 71 | 136 | 801.469 |
| 4 | 96 | 3 | 73 | 134 | 210.000 |
| 3 | 93 | 1 | 76 | 130 | 626.000 |
| 4 | 200 | 2 | 77 | 178 | 796.026 |
| 2 | 35 | 1 | 80 | 110 | 64.702 |
| 1 | 25 | 2 | 80 | 120 | 36.277 |
| 1 | 25 | 2 | 80 | 120 | 36.277 |
| 3 | 16 | 2 | 80 | 100 | 14.300 |
| 4 | 216 | 3 | 80 | 124 | 1.339.903 |
| 3 | 74 | 3 | 80 | 95 | 111.000 |
| 5 | 265 | 1 | 81 | 174 | 1.393.550 |
| 5 | 280 | 3 | 81 | 138 | 903.000 |
| 5 | 127 | 1 | 85 | 114 | 1.072.000 |
| 3 | 33 | 3 | 85 | 120 | 238.000 |
| 4 | 353 | 2 | 87 | 152 | 1.511.457 |
| 5 | 172 | 1 | 90 | 195 | 1.151.600 |
| 4 | 10 | 1 | 90 | 105 | 15.950 |
| 5 | 219 | 3 | 93 | 162 | 1.675.995 |
| 5 | 313 | 1 | 94 | 173 | 2.214.985 |
| 3 | 18 | 1 | 94 | 104 | 722.069 |
| 4 | 97 | 3 | 94 | 120 | 441.737 |
| 2 | 43 | 3 | 94 | 120 | 195.821 |
| 5 | 412 | 1 | 95 | 160 | 2.165.000 |
| 4 | 276 | 2 | 95 | 160 | 2.050.000 |
| 3 | 11 | 3 | 95 | 120 | 3.000 |
| 5 | 166 | 3 | 98 | 183 | 900.000 |
| 3 | 33 | 2 | 99 | 218 | 271.724 |
| 5 | 139 | 2 | 100 | 130 | 495.000 |
| 5 | 50 | 2 | 100 | 180 | 517.729 |
| 2 | 25 | 2 | 100 | 150 | 60.000 |
| 5 | 181 | 3 | 100 | 187 | 1.143.850 |
| 5 | 119 | 3 | 100 | 150 | 600.000 |
| 4 | 9 | 3 | 100 | 180 | |
| 5 | 174 | 3 | 102 | 211 | 2.500.000 |
| 5 | 124 | 3 | 103 | 160 | 1.103.939 |
| 5 | 330 | 2 | 112 | 240 | 434.237 |
| 4 | 324 | 2 | 112 | 211 | 1.800.000 |
| 4 | 161 | 3 | 112 | 213 | 1.370.968 |
| 5 | 306 | 2 | 113 | 235 | 2.074.000 |
| 5 | 261 | 3 | 119 | 211 | 3.000.000 |
| 5 | 204 | 1 | 131 | 225 | 2.460.634 |
| 4 | 34 | 2 | 133 | 218 | 96.619 |
| 4 | 27 | 2 | 180 | 250 | 51.000 |
| 4 | 12 | 2 | 215 | 265 | 45.000 |
In: Statistics and Probability
4. Suppose a monopolist faces two markets with the following
demand curves: Market 1: ?1(?1) = 400 − 2?1
Market 2: ?2(?2) = 1000 − 4?2
Let the marginal cost be $20 per unit in both markets.
If the monopolist can price discriminate, what should be ?1 and ?2 to maximize the monopolist’s profit?
In: Economics
What is the only possible value of mℓ for an electron in an s orbital?Express your answer numerically.
2.
Which of the following set of quantum numbers (ordered n, ℓ, mℓ, ms) are possible for an electron in an atom?
Check all that apply.
| -1, 0, 0, -1/2 | |
| 3, 2, 2, -1/2 | |
| 3, 1, 0, -1/2 | |
| 4, 3, -4, -1/2 | |
| 3, 2, 0, -1/2 | |
| 2, 1, 3, 1/2 | |
| 2, 1, 0, -1 | |
| 3, 3, 1, -1/2 |
In: Chemistry
Following are cost terms, concepts, and classifications of a
metal toy car model manufacturer:
1. Product costs
2. Period costs
3. Direct material costs
4. Direct labor costs
5. Manufacturing overhead costs
6. Fixed costs
7. Variable costs
Match the above are cost terms, concepts, and classifications to
the respective costs items:
1. Metal used in manufacturing of the metal toy car models.
1, 3, 4
2, 7
1, 3, 7
2, 3, 6
2. Depreciation of factory machineries.
1, 3, 6
2, 6
1, 5, 6
1, 3, 7
3. Sales commissions earned by salesman.
1, 3, 6
2, 7
1, 5, 6
1, 3, 7
4. Factory supervisor salaries.
1, 5, 6
2, 7
2, 5, 6
1, 3, 7
5. Factory assembly line worker.
1, 5, 6
2, 7
2, 5, 6
1, 4, 7
In: Accounting
Complete the following recursively defined functions.
Base case ?(0)=3
Recursive case ?(?) = 3?(? − 1) + 7 for n ≥ 1.
?(1) = ______
f(2) = _______
f(3) = ______
f(4) = ______
Base case ?(0)=1, ?(1)=2
Recursive case ?(?) = ?(? − 1)?(? − 2) for n ≥ 2.
g(2) = ______
g(3) = ______
g(4) = ______
g(5) = ______
In: Computer Science
Calculate the population mean and median based on the numerical values of Satisfaction Level, and then interpret those at the nominal level.
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TABLE C6-2: Customer Satisfaction |
|||||
|
Customer Number |
Customer Name |
Satisfaction Level |
Level No. |
||
|
1 |
Anderson |
Very high |
4 |
||
|
7 |
Hetfield |
very high |
4 |
||
|
14 |
Luo |
very high |
4 |
||
|
15 |
Madras |
very high |
4 |
||
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19 |
Nickens |
very high |
4 |
||
|
20 |
Poteau |
very high |
4 |
||
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2 |
Angero |
high |
3 |
||
|
5 |
Chontos |
high |
3 |
||
|
9 |
Jamesson |
high |
3 |
||
|
11 |
Lehmann |
high |
3 |
||
|
12 |
Lee |
high |
3 |
||
|
22 |
Scully |
high |
3 |
||
|
23 |
Singh |
high |
3 |
||
|
24 |
Skinner |
high |
3 |
||
|
27 |
Vu'oto |
high |
3 |
||
|
29 |
Yap |
high |
3 |
||
|
3 |
Ball |
medium |
2 |
||
|
8 |
Iruja |
medium |
2 |
||
|
10 |
Kemp |
medium |
2 |
||
|
17 |
Mulder |
medium |
2 |
||
|
21 |
Sakomoto |
medium |
2 |
||
|
26 |
Tang |
medium |
2 |
||
|
28 |
Walker |
medium |
2 |
||
|
4 |
Bobak |
low |
1 |
||
|
13 |
Lewins |
low |
1 |
||
|
16 |
Morris |
low |
1 |
||
|
18 |
Ngozichi |
low |
1 |
||
|
25 |
Suzuki |
low |
1 |
||
|
6 |
Detley |
very low |
0 |
||
|
30 |
Zindermanelino |
very low |
0 |
||
|
Very High |
4 |
||||
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High |
3 |
||||
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Medium |
2 |
||||
|
Low |
1 |
||||
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Very Low |
0 |
||||
In: Statistics and Probability