Hyundai Automobile U.S.A. is sponsoring a charity golf tournament to raise monies for a children's hospital in Birmingham. Hyundai budgets $5,400 in costs for administration and marketing for the event. The band will cost a fixed amount of $2,100. Tickets to this local community event will be $350 per person. All proceeds from the event will be donated to the children's hospital. There are two possible venues:
RTJ Golf Resort at Prattville, which has a fixed rental cost of $10,220. The hotel provides for meals and waiters and waitresses to serve drinks and finger foods at $65 per person. The green fees and cart for each person will be $40.
Wynlakes Golf & Country Club, which has a fixed rental cost of $2,300 plus a charge of $110 per person for its own catering of meals and serving of drinks and finger foods. The green fees and cart for each person will be $50.
(a) Compute the break-even point for each venue in terms of tickets sold.
The break-even point for tickets sold from RTJ Golf Resort at Prattville is:
A.
68
B.
70
C.
85
D.
73
The break-even point for tickets sold from Wynlakes Golf & Country Club is:
A.
52
B.
45
C.
61
D.
50
(b) At what level of tickets sold will the two venues have the same operating income?
The two venues will have the same operating income with ticket sales at:
A.
146
B.
134
C.
123
D.
144
In: Economics
John and Eric are childhood friends who went to school and university together. After graduation, John moved to Spain where he joined his family and started a business exporting authentic Spanish Artwork to clients around the World. Eric operates a retail store in Brazil, and the two friends agreed to start a business together. John would send artwork to Eric who would sell it in his store at a reasonable price. John shipped the Artwork by mail to ensure quick, timely delivery. Eric verbally agreed to pay John 30 days after shipment and they would split the profits equally, with each party getting 50 percent. 45 days after shipment, John contacted Eric to see how things were progressing. Eric informed John that the Artwork had not sold. He indicated some potential buyers had shown interest but thought the art was priced too high. A month later, John called Erik to follow up and collect funds. Eric mentioned he had no cash on hand and his financial situation made it impossible to make any payments for the moment. Eric gave John the option to either take the frames back or sell them at cost. John is unable to obtain assistance from any of his friends and lawyers as there are no written contractual agreements signed. 4 months later, John followed up one last time. Eric mentioned he sold the frames for 25 percent of the asking price, and he did not transfer any funds for payment of artwork and additional costs. John lost $9,000 worth of goods and a friend that he trusted.
Note: No Plagiarism, Each answer minimum of 100 words.
1. What mistakes did John make during his negotiation that led to this loss? *
2.Is there anything John can legally do now to minimize his loss in this transaction? *
3. How would you negotiate differently in a similar future transaction to avoid this situation at the end? *
In: Accounting
Assume the following model of the expenditure sector:
C = 1000 +.7 (Y-T) Consumption Function
T = 300+ .2985 Y Tax Function
I = 500 – 50 r Investment Function
G = 2000 Government Expenditures
NX = - 1500 Net Exports
Md/P = .5 Y -50 r Demand for Money
Ms/P = 1000 Money Supply
a- Calculate the multiplier for this economy. (Use two decimal
points)
b- Drive the “IS” and “LM” equations for this economy.
c- Fiscal policy authorities decided to use the expansionary Fiscal
Policy by increasing
the G by $500. As result of this action
i- What would be the new interest rate and real GDP
equilibrium?
ii- What would be the amount of the crowding out as result of the
policy?
In: Economics
| gpa | studyweek | sleepnight | gender |
| 3.89 | 50 | 6 | female |
| 3.9 | 15 | 6 | female |
| 3.75 | 15 | 7 | female |
| 3.6 | 10 | 6 | male |
| 4 | 25 | 7 | female |
| 3.15 | 20 | 7 | male |
| 3.25 | 15 | 6 | female |
| 3.925 | 10 | 8 | female |
| 3.428 | 12 | 8 | female |
| 3.8 | 2 | 8 | male |
| 3.9 | 10 | 8 | female |
| 2.9 | 30 | 6 | female |
| 3.925 | 30 | 7 | female |
| 3.65 | 21 | 9 | female |
| 3.75 | 10 | 8.5 | female |
| 4.67 | 14 | 6.5 | male |
| 3.1 | 12 | 7.5 | male |
A sample of 17 students is selected. Data is collected on the students’ GPA, the # of hours studying per week, the # of hours sleeping per night and gender. using excel to calculate:
a) Decide at the level of significance of 5% if there is any difference between the average GPA of females and males.
b) Decide at the level of significance of 5% if there is any difference between the average # of hours studying per week of females and males.
c) Decide at the level of significance of 5% if there is any difference between the average # of hours sleeping per night of females and males
In: Statistics and Probability
Matching
Match the ocular term in Column I with the definition in Column II.
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Match the auditory term in Column I with the definition in Column II.
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Column II |
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In: Anatomy and Physiology
A trucking company determined that the distance traveled per truck per year is normally distributed, with a mean of 60 thousand miles and a standard deviation of 10 thousand miles. Complete parts (a) through (d) below.
a. What proportion of trucks can be expected to travel between 48 and 60 thousand miles in a year?
b. What percentage of trucks can be expected to travel either less than 40 or more than 75 thousand miles in a year?
c. How many miles will be traveled by at least 85% of the trucks?
d. What are your answers to parts (a) through (c) if the standard deviation is 8 thousand miles? I
f the standard deviation is 8 thousand miles, the proportion of trucks that can be expected to travel between 48 and 60 thousand miles in a year is . (Round to four decimal places as needed.)
If the standard deviation is 8 thousand miles, the percentage of trucks that can be expected to travel either less than 40 or more than 75 thousand miles in a year is . (Round to two decimal places as needed.)
If the standard deviation is 8 thousand miles, the number of miles that will be traveled by at least 85% of the trucks is . (Round to the nearest mile as needed.)
In: Statistics and Probability
10.45 Is there a difference in the variance of the satisfaction rating of traditional cellphone providers who bill for service at the end of a month (often under contract) and prepaid cellphone service providers who bill in advance without a contract? The file CellphoneProviders contains the satisfaction rating for 10 traditional cellphone providers and 13 prepaid cellphone service providers.
| CellPhone Provider | Type | Rating | |
| Consumer Cellular | Traditional | 89 | |
| Ting | Traditional | 88 | |
| Grat Cell/Jitterbug | Traditional | 79 | |
| Credo Mobile | Traditional | 78 | |
| Virgin Mobile | Traditional | 76 | |
| U. S. Cellular | Traditional | 73 | |
| T-Mobile | Traditional | 73 | |
| Verizon Wireless | Traditional | 70 | |
| AT&T | Traditional | 68 | |
| Sprint | Traditional | 67 | |
| Republic Wireless | PrePaid | 87 | |
| Cricket | PrePaid | 85 | |
| Page Plus Cellular | PrePaid | 84 | |
| Straight Talk | PrePaid | 80 | |
| TracFone | PrePaid | 79 | |
| MetroPCS | PrePaid | 78 | |
| Virgin Mobile | PrePaid | 76 | |
| Net10 | PrePaid | 76 | |
| Boost Mobile | PrePaid | 75 | |
| T-Mobile | PrePaid | 74 | |
| Verizon Wireless | PrePaid | 70 | |
| AT&T | PrePaid | 70 | |
| Sprint | PrePaid | 66 |
In: Statistics and Probability
Ferry Services Incorporated (FSI) is a public company that has
three divisions. The first division provides coastal ferry services
on the West and East coasts of Canada. The second division designs
and builds ferries for their own use as well as for external
customers. The third division operates and manages ferry terminal
buildings.
In 2011, FSI anticipates a taxable loss of $20 million due to a
major hurricane that sunk one of their ferry ships and caused
extensive damage to one of their terminal buildings. For the past
three years they have had taxable income of 2008 - $5 million; 2009
- $10 million; and 2010 - $8 million.
FSI has a number of long-term bank loans with Canadian Big Bank. In
2011, they obtained additional financing to recover from the costs
associated with the hurricane. The bank requires annual audited
financial statements. The new loan has a financial covenant
requiring that FSI maintain a certain current ratio, as well as
dividend distribution is restricted until the loan is paid
off.
You have recently been hired to develop new accounting policies for
FSI’s Dec 31 year-end. You have been asked by the Board to discuss
alternatives and provide recommendations on the appropriate
accounting policies for events that have occurred during 2011.
Where possible you have been asked to quantify the impact of the
accounting policies. The incremental borrowing rate for FSI is 8%.
The tax rates for the last few years were: 2008 (40%), 2009 (38%),
and 2010 (38%). The tax rate for 2011 is 40%.
1) A major hurricane hit the Eastern Coast in the fall of 2011.
This hurricane was tracking to miss the Eastern Seaboard but had a
sudden change in direction. FSI was caught off guard and one of
their ferries as well as a ferry terminal was in the direct path of
the hurricane. Unfortunately, FSI found out that their insurance
did not cover hurricane damage. To cover the costs associated with
the damages FSI obtained a new five year bank loan of $25 million
with quarterly interest payments. Their cost of borrowing was 8% a
year. To obtain the loan FSI had to pay $1 million of transaction
costs.
2) The ferry was one of their older ferries with a carrying amount
of $2 million dollars. The costs to recover the ferry are
approximately $3 million and it is anticipated they will receive
$0.5 million worth of salvaged material. The ferry will need to be
replaced and construction was initiated in December 2011. The
estimated construction costs are $20 million since the ferry will
be state of the art with a new weather warning software system.
Construction is expected to be completed in the spring of 2013.
Until that time a ferry was brought out of retirement. The ferry
had been retired due to extensive renovations required to meet
environmental legislation. These renovations cost FSI $2 million in
2011.
Page 2
3) The damage to the terminal was $7 million. FSI leases all of
their terminals from Leasing Incorporated (LI). This lease has a
remaining lease term of 2 years. Due to the terms of the lease
agreement FSI is required to pay a large penalty of $5 million
dollars for repairs to the terminal. This cost far exceeds the
remaining benefits of the lease agreement.
4) A lawsuit was launched in December 2011 against FSI due to the
tragedy of the sinking of the ferry. FSI decided that they want to
settle quickly out of court to avoid negative publicity. They have
offered $5 million to the families. Their lawyers have not
responded to this offer.
5) Passengers can purchase their ferry tickets on-line through
Tickets.com. To encourage use of the ferry FSI provides passengers
free parking if they purchase an annual pass. Otherwise passengers
pay a daily rate to park their vehicle.
6) Some of the ferries contain asbestos. Changes in government
legislation in 2011 require FSI to remove the asbestos in 2016. The
anticipated cost of removal is $5 million.
7) FSI leases their ferry terminals from Leasing Incorporated. In
2011, FSI obtained the rights to operate a ferry on a new route.
They entered into a lease agreement for a newly constructed
terminal and the land. The lease term is for 60 years with a 20
year bargain renewal term.
8) In 2011, FSI issued $10,000,000 of 8% convertible bonds at the
option of FSI into common shares. These bonds mature in five years
and are convertible at that time by FSI into common shares at a
rate of 50 shares for each $1,000 bond.
In: Accounting
| SALARY | EDUC | EXPER | TIME |
| 39000 | 12 | 0 | 1 |
| 40200 | 10 | 44 | 7 |
| 42900 | 12 | 5 | 30 |
| 43800 | 8 | 6 | 7 |
| 43800 | 8 | 8 | 6 |
| 43800 | 12 | 0 | 7 |
| 43800 | 12 | 0 | 10 |
| 43800 | 12 | 5 | 6 |
| 44400 | 15 | 75 | 2 |
| 45000 | 8 | 52 | 3 |
| 45000 | 12 | 8 | 19 |
| 46200 | 12 | 52 | 3 |
| 48000 | 8 | 70 | 20 |
| 48000 | 12 | 6 | 23 |
| 48000 | 12 | 11 | 12 |
| 48000 | 12 | 11 | 17 |
| 48000 | 12 | 63 | 22 |
| 48000 | 12 | 144 | 24 |
| 48000 | 12 | 163 | 12 |
| 48000 | 12 | 228 | 26 |
| 48000 | 12 | 381 | 1 |
| 48000 | 16 | 214 | 15 |
| 49800 | 8 | 318 | 25 |
| 51000 | 8 | 96 | 33 |
| 51000 | 12 | 36 | 15 |
| 51000 | 12 | 59 | 14 |
| 51000 | 15 | 115 | 1 |
| 51000 | 15 | 165 | 4 |
| 51000 | 16 | 123 | 12 |
| 51600 | 12 | 18 | 12 |
| 52200 | 8 | 102 | 29 |
| 52200 | 12 | 127 | 29 |
| 52800 | 8 | 90 | 11 |
| 52800 | 8 | 190 | 1 |
| 52800 | 12 | 107 | 11 |
| 54000 | 8 | 173 | 34 |
| 54000 | 8 | 228 | 33 |
| 54000 | 12 | 26 | 11 |
| 54000 | 12 | 36 | 33 |
| 54000 | 12 | 38 | 22 |
| 54000 | 12 | 82 | 29 |
| 54000 | 12 | 169 | 27 |
| 54000 | 12 | 244 | 1 |
| 54000 | 15 | 24 | 13 |
| 54000 | 15 | 49 | 27 |
| 54000 | 15 | 51 | 21 |
| 54000 | 15 | 122 | 33 |
| 55200 | 12 | 97 | 17 |
| 55200 | 12 | 196 | 32 |
| 55800 | 12 | 133 | 30 |
| 56400 | 12 | 55 | 9 |
| 57000 | 12 | 90 | 23 |
| 57000 | 12 | 117 | 25 |
| 57000 | 15 | 51 | 17 |
| 57000 | 15 | 61 | 11 |
| 57000 | 15 | 241 | 34 |
| 60000 | 12 | 121 | 30 |
| 60000 | 15 | 79 | 13 |
| 61200 | 12 | 209 | 21 |
| 63000 | 12 | 87 | 33 |
| 63000 | 15 | 231 | 15 |
| 46200 | 12 | 12 | 22 |
| 50400 | 15 | 14 | 3 |
| 51000 | 12 | 180 | 15 |
| 51000 | 12 | 315 | 2 |
| 52200 | 12 | 29 | 14 |
| 54000 | 12 | 7 | 21 |
| 54000 | 12 | 38 | 11 |
| 54000 | 12 | 113 | 3 |
| 54000 | 15 | 18 | 8 |
| 54000 | 15 | 359 | 11 |
| 57000 | 15 | 36 | 5 |
| 60000 | 8 | 320 | 21 |
| 60000 | 12 | 24 | 2 |
| 60000 | 12 | 32 | 17 |
| 60000 | 12 | 49 | 8 |
| 60000 | 12 | 56 | 33 |
| 60000 | 12 | 252 | 11 |
| 60000 | 12 | 272 | 19 |
| 60000 | 15 | 25 | 13 |
| 60000 | 15 | 36 | 32 |
| 60000 | 15 | 56 | 12 |
| 60000 | 15 | 64 | 33 |
| 60000 | 15 | 108 | 16 |
| 60000 | 16 | 46 | 3 |
| 63000 | 15 | 72 | 17 |
| 66000 | 15 | 64 | 16 |
| 66000 | 15 | 84 | 33 |
| 66000 | 15 | 216 | 16 |
| 68400 | 15 | 42 | 7 |
| 69000 | 12 | 175 | 10 |
| 69000 | 15 | 132 | 24 |
| 81000 | 16 | 55 | 33 |
This data set was obtained by collecting information on a randomly selected sample of 93 employees working at a bank.
SALARY- starting annual salary at the time of hire
EDUC - number of years of schooling at the time of the hire
EXPER - number of months of previous work experience at the time of hire
TIME - number of months that the employee has been working at the bank until now
2. Use the least squares method to fit a simple linear model that relates the salary (dependent variable) toeducation (independent variable).
a) What is your model? State the hypothesis that is to be tested, the decision rule, the test statistic, and your decision, usinga level of significance of 5%.
b) What percentage of the variation in salary has been explained by the regression?
c) Provide a 95% confidence interval estimate for the true slope value.
d) Based on your model, what is the expected salary of a new hire with 12 years of education
e ) What is the 95% prediction interval for the salary of a new hire with 12 years of education? Use the fact that the distance value = 0.011286
In: Statistics and Probability
| SALARY | EDUC | EXPER | TIME |
| 39000 | 12 | 0 | 1 |
| 40200 | 10 | 44 | 7 |
| 42900 | 12 | 5 | 30 |
| 43800 | 8 | 6 | 7 |
| 43800 | 8 | 8 | 6 |
| 43800 | 12 | 0 | 7 |
| 43800 | 12 | 0 | 10 |
| 43800 | 12 | 5 | 6 |
| 44400 | 15 | 75 | 2 |
| 45000 | 8 | 52 | 3 |
| 45000 | 12 | 8 | 19 |
| 46200 | 12 | 52 | 3 |
| 48000 | 8 | 70 | 20 |
| 48000 | 12 | 6 | 23 |
| 48000 | 12 | 11 | 12 |
| 48000 | 12 | 11 | 17 |
| 48000 | 12 | 63 | 22 |
| 48000 | 12 | 144 | 24 |
| 48000 | 12 | 163 | 12 |
| 48000 | 12 | 228 | 26 |
| 48000 | 12 | 381 | 1 |
| 48000 | 16 | 214 | 15 |
| 49800 | 8 | 318 | 25 |
| 51000 | 8 | 96 | 33 |
| 51000 | 12 | 36 | 15 |
| 51000 | 12 | 59 | 14 |
| 51000 | 15 | 115 | 1 |
| 51000 | 15 | 165 | 4 |
| 51000 | 16 | 123 | 12 |
| 51600 | 12 | 18 | 12 |
| 52200 | 8 | 102 | 29 |
| 52200 | 12 | 127 | 29 |
| 52800 | 8 | 90 | 11 |
| 52800 | 8 | 190 | 1 |
| 52800 | 12 | 107 | 11 |
| 54000 | 8 | 173 | 34 |
| 54000 | 8 | 228 | 33 |
| 54000 | 12 | 26 | 11 |
| 54000 | 12 | 36 | 33 |
| 54000 | 12 | 38 | 22 |
| 54000 | 12 | 82 | 29 |
| 54000 | 12 | 169 | 27 |
| 54000 | 12 | 244 | 1 |
| 54000 | 15 | 24 | 13 |
| 54000 | 15 | 49 | 27 |
| 54000 | 15 | 51 | 21 |
| 54000 | 15 | 122 | 33 |
| 55200 | 12 | 97 | 17 |
| 55200 | 12 | 196 | 32 |
| 55800 | 12 | 133 | 30 |
| 56400 | 12 | 55 | 9 |
| 57000 | 12 | 90 | 23 |
| 57000 | 12 | 117 | 25 |
| 57000 | 15 | 51 | 17 |
| 57000 | 15 | 61 | 11 |
| 57000 | 15 | 241 | 34 |
| 60000 | 12 | 121 | 30 |
| 60000 | 15 | 79 | 13 |
| 61200 | 12 | 209 | 21 |
| 63000 | 12 | 87 | 33 |
| 63000 | 15 | 231 | 15 |
| 46200 | 12 | 12 | 22 |
| 50400 | 15 | 14 | 3 |
| 51000 | 12 | 180 | 15 |
| 51000 | 12 | 315 | 2 |
| 52200 | 12 | 29 | 14 |
| 54000 | 12 | 7 | 21 |
| 54000 | 12 | 38 | 11 |
| 54000 | 12 | 113 | 3 |
| 54000 | 15 | 18 | 8 |
| 54000 | 15 | 359 | 11 |
| 57000 | 15 | 36 | 5 |
| 60000 | 8 | 320 | 21 |
| 60000 | 12 | 24 | 2 |
| 60000 | 12 | 32 | 17 |
| 60000 | 12 | 49 | 8 |
| 60000 | 12 | 56 | 33 |
| 60000 | 12 | 252 | 11 |
| 60000 | 12 | 272 | 19 |
| 60000 | 15 | 25 | 13 |
| 60000 | 15 | 36 | 32 |
| 60000 | 15 | 56 | 12 |
| 60000 | 15 | 64 | 33 |
| 60000 | 15 | 108 | 16 |
| 60000 | 16 | 46 | 3 |
| 63000 | 15 | 72 | 17 |
| 66000 | 15 | 64 | 16 |
| 66000 | 15 | 84 | 33 |
| 66000 | 15 | 216 | 16 |
| 68400 | 15 | 42 | 7 |
| 69000 | 12 | 175 | 10 |
| 69000 | 15 | 132 | 24 |
| 81000 | 16 | 55 |
| SUMMARY OUTPUT | ||||||||
| Regression Statistics | ||||||||
| Multiple R | 0.41198516 | |||||||
| R Square | 0.16973178 | |||||||
| Adjusted R Square | 0.16060795 | |||||||
| Standard Error | 6501.12045 | |||||||
| Observations | 93 | |||||||
| ANOVA | ||||||||
| df | SS | MS | F | Significance F | ||||
| Regression | 1 | 786253429 | 786253429 | 18.60313 | 4.08E-05 | |||
| Residual | 91 | 3.85E+09 | 42264567.1 | |||||
| Total | 92 | 4.63E+09 | ||||||
| Coefficients | Standard Error | t Stat | P-value | Lower 95% | Upper 95% | Lower 95.0% | Upper 95.0% | |
| Intercept | 38185.5979 | 3774.3766 | 10.117061 | 1.45E-16 | 30688.26252 | 45682.93 | 30688.26 | 45682.93 |
| X Variable 1 | 1280.85932 | 296.96712 | 4.31313512 | 4.08E-05 | 690.9706164 | 1870.748 | 690.9706 | 1870.748 |
This data set was obtained by collecting information on a randomly selected sample of 93 employees working at a bank.
SALARY- starting annual salary at the time of hire
EDUC - number of years of schooling at the time of the hire
EXPER - number of months of previous work experience at the time of hire
TIME - number of months that the employee has been working at the bank until now
2. Use the least squares method to fit a simple linear model that relates the salary (dependent variable) to education (independent variable).
a- What is your model? State the hypothesis that is to be tested, the decision rule, the test statistic, and your decision, using a level of significance of 5%.
b – What percentage of the variation in salary has been explained by the regression?
c – Provide a 95% confidence interval estimate for the true slope value.
d - Based on your model, what is the expected salary of a new hire with 12 years of education?
e – What is the 95% prediction interval for the salary of a new hire with 12 years of education? Use the fact that the distance value = 0.011286
In: Statistics and Probability