A project consists of two tasks. Task A is scheduled to begin at the start of Week 1 and finish at the end of Week 4. Task B is scheduled to begin at the start of Week 2 and finish at the end of Week 3. The budgeted cost for Task A is $80,000, and for Task B is $40,000.
1. Creat a cost loaded for this project:
Round the number to the closest integer number and input it without "$" and ',' signs.
Cost at Week 1:
Cost at Week 2:
Cost at Week 3:
Cost at Week 4:
2. At the end of the second week Task A is 50% complete, and Task B is 25% complete. Calculate the following items:
BCWS :
BCWP :
3. What is the schedule performance index for the project at the end of the second week (Round decimal numbers to 2 decimal places. If it is less than 1, write it in the following format: 0.xx)?
4. The actual cost of the work performed at the end of the second week is $40,000. Determine the cost performance index for the project (Round decimal numbers to 2 decimal places. If it is less than 1, write it in the following format: 0.xx).
In: Operations Management
8.2 The Law of One Price implies that financial instruments with the same risk and the same cash flows at the same time should have the same price.
You are given the following table containing incomplete information on four different bonds. Assume that all these bonds have the same risk, and any coupon payments are paid annually.
(20 marks total)
a. What is the yield to maturity on Bond #1?
b. What is the price of Bond #3?
c. You are considering two investments from the bonds listed in the table.
Portfolio 1: 60 units of Bond #1 + 1060 units of Bond #2
Portfolio 2: 1000 units of Bond #3
Show that the future cash flow from these two portfolios would be identical, in amount and timing.
d. Based on the information in the given table,
i. What would it cost to buy 1000 units of Bond #3? (1 mark)
ii. What would it cost to buy 60 units of Bond #1? (1 mark)
iii. From part c. above and your answers in part d.i and ii, infer the value of 1060 units of Bond #2.
iv. What is the value of one unit of Bond #2? (1 mark)
v. What is the implied yield of Bond #2?
e. How many units of Bond #1 and #2 would you need to replicate the future cash flows of 1000 units of Bond #4?
f. Using your answer to part e above, determine the following
i. What’s the value of 1000 units of Bond #4?
ii. What’s the yield of Bond 4?
g. Fill in the missing information in the given table: (1 mark)
Bond # 1 2 3 4
| 1 - year strip bond | 2 - year strip bond | 2-year 6% coupon bond | 2-year 7% coupon bond | ||
| Purchase price ($xxxx.xx) | -950.00 | ||||
| Time 1 cash flow | +1,000.00 | +60.00 | +70.00 | ||
| Time 2 cash flow | 0 | +1,000.00 | +1,060.00 | +1070.00 | |
| Yield to maturity (xx.xx% | 5.50% | ||||
In: Accounting
A pharmaceutical company is testing a new cold medicine to determine if the drug has side affects. To test the drug, 8 patients are given the drug and 9 patients are given a placebo (sugar pill). The change in blood pressure after taking the pill was as follows:
Given drug: 3 4 5 1 -2 3 5 6
Given placebo: 1 -1 2 7 2 3 0 3 4
Test to determine if the drug raises patients’ blood pressure more than the placebo using α = 0.01
In: Statistics and Probability
2. Why don’t we just measure populations? Why do we use samples to infer about populations?
3. Ten people were asked how many siblings they have. Below is the data:
2, 4, 1, 2, 1, 3, 5, 0, 1, 3, 0
4. Create a frequency distribution table.
5. Add on a cumulative frequency column and compute the cumulative frequencies.
6. Add on a relative frequency column and compute the relative frequencies.
In: Statistics and Probability
You assume that students are more likely to miss a standardized test scheduled in April than December. You ask 11 professors from 11 different schools who all teach a full year course to keep track of the number of students who are ill during the testing period for each term. The table shows you how many students missed a test for each testing period for the 11 different schools:
| class | Dec | April | + - | RANK-Dec | RANK-April | D | D2 |
| 1 | 4 | 7 | - | 3 | 4 | -1 | 1 |
| 2 | 3 | 8 | - | 2 | 5 | -3 | 9 |
| 3 | 11 | 12 | - | 9 | 9 | 0 | 0 |
| 4 | 13 | 16 | - | 10 | 11 | -1 | 1 |
| 5 | 8 | 6 | + | 7 | 2.5 | 4.5 | 20.25 |
| 6 | 5 | 9 | - | 5 | 6 | -1 | 1 |
| 7 | 7 | 10 | - | 6 | 7 | -1 | 1 |
| 8 | 5 | 6 | - | 4 | 2.5 | 1.5 | 2.25 |
| 9 | 2 | 2 | T | 1 | 1 | 0 | 0 |
| 10 | 9 | 11 | - | 8 | 8 | 0 | 0 |
| 11 | 14 | 15 | - | 11 | 10 | 1 | 1 |
| SUM | 81 | 102 | 66 | 66 | 0 | 36.5 | |
| St Dev | 4.03 | 4.13 | 3.32 | 3.31 | 1.91 | 6.16 |
What are the rules of this analysis? What would you calculate for your value? What is your decision? What is your conclusion?
In: Statistics and Probability
find the solution of the given initial value problem
1. y''+4y=t2+3et, y(0) =0, y'(0) =2
2. y''−2y'+y=tet +4, y(0) =1, y'(0) =1
In: Advanced Math
QA. What is beta of an asset for each scenario:
1) S&P return = 8%, σm = 5, σx = 5, market risk premium = 4%, ρxm = 0.67
2) Rx = 10%, market risk premium = 4%, t-bill rate = 4%
3) Risk free rate = 5%, σxm = 32, σm = 6, σx = 4
4) σm = 6, σx = 4, Rx = 10%, NIKKEI return = 12%, risk free rate = 2%
In: Accounting
|
Radius (m) |
Radial Magnetic Field (μT) |
Axial Magnetic Field (μT) |
|
0 |
3.0 + .2 |
31 + 2 |
|
0.01 |
2.5 + .1 |
32 + 2 |
|
0.02 |
1.3 + .07 |
33 + 2 |
|
0.03 |
2.4 + .1 |
34 + 2 |
|
0.04 |
-3.8 + .2 |
36 + 2 |
|
0.05 |
-5.0 + .3 |
34 + 2 |
|
0.06 |
-12.0 + .3 |
37 + 2 |
|
0.07 |
-17.0 + .9 |
44 + 2 |
|
0.08 |
-16.0 + .8 |
51 + 3 |
|
0.11 |
-30 + 2 |
-60 + 3 |
|
0.12 |
-8.0 + .4 |
-45 + 2 |
|
0.13 |
-8.0 + .4 |
-23 + 1 |
|
0.14 |
-7.6 + .4 |
-17 + 1 |
|
0.15 |
-6.0 + .3 |
-14 + 1 |
|
0.16 |
-3.0 + .2 |
-13 + 1 |
|
0.17 |
-1.8 + .1 |
-12 + 1 |
|
0.18 |
-4.0 + .2 |
-12 + 1 |
|
0.19 |
-4.0 + .2 |
-11 + 1 |
|
0.20 |
-4.7 + .2 |
-11 + 1 |
(Quick note: the plus signs should be plus or minus, to signify the uncertanties the values have)
In this experiment we are connecting a power supply to a coil. We are using the current I=0.3A and N=200. The procedure explains: "Measure B near the wire coil itself in the plane of the coil. Take data as a function of r (distance to the wire) both going toward the center of the loop and going away fom the axis. Does the equation B=µ0*N*I/2*pi*r give the correct magnitude for B? Over what range does B vary as 1/r?
The questions are: In one graph, plot axial and radial magnetic fields against radius. On the same graph, plot the theoretical prediction for the axial magnetic field using equation B=µ0*N*I/2*pi*r
+I am confused on how to plot the theoretical prediction for the axial magnetic field. This has to do with the fact that the signs of B reverse but when does that happen?
In: Physics
One of the questions in a study of marital satisfaction of dual-career couples was to rate the statement, "I'm pleased with the way we divide the responsibilities for childcare." The ratings went from 1 (strongly agree) to 5 (strongly disagree). The table below contains ten of the paired responses for husbands and wives. Conduct a hypothesis test at the 5% level to see if the mean difference in the husband's versus the wife's satisfaction level is negative (meaning that, within the partnership, the husband is happier than the wife). Wife's score 3, 4, 3, 3, 4, 2, 1, 1, 2, 4
Husband's score 2, 2, 2, 3, 2, 1, 1, 1, 2, 4
NOTE: If you are using a Student's t-distribution for the problem, including for paired data, you may assume that the underlying population is normally distributed. (In general, you must first prove that assumption, though.)
A) State the distribution to use for the test. (Enter your answer in the form z or tdf where df is the degrees of freedom.)
B) What is the test statistic? (If using the z distribution round your answer to two decimal places, and if using the t distribution round your answer to three decimal places.)
C) What is the p-value? (Round your answer to four decimal places.)
D) Sketch a picture of this situation. Label and scale the horizontal axis and shade the region(s) corresponding to the p-value.
E) Alpha (Enter an exact number as an integer, fraction, or
decimal.)
α =
E)
In: Statistics and Probability
9.13
Using the SHHS data in Table 2.10,fit all possible multiple regression models (without interactions) that predict the y variable serum total cholesterol from diastolic blood pressure,systolic blood pressure,alcohol,carbon monoxide and cotinine. Scrutinize your results to understand how the x variables act in conjuction.For these data,which is the "best " multiple regression model for cholesterol? What percentage of variation does it explain?
| Serum total cholesrerol (mmol/l) | Diastolic blood pressure (mmHg) | Systolic blood pressure (mmHg) | Alcohol (g/day) | Cigarettes (no./day) | Carbon monoxide(ppm) | Cotinine (ng/ml) | CHD (1=yes,2=no) |
| 5.75 | 80 | 121 | 5.4 | 0 | 6 | 13 | 2 |
| 6.76 | 83 | 139 | 64.6 | 0 | 4 | 3 | 2 |
| 6.47 | 76 | 113 | 21.5 | 20 | 21 | 284 | 2 |
| 7.11 | 79 | 124 | 8.2 | 40 | 57 | 395 | 2 |
| 5.42 | 100 | 127 | 24.4 | 20 | 29 | 283 | 2 |
| 7.04 | 79 | 148 | 13.6 | 0 | 3 | 0 | 2 |
| 5.75 | 79 | 124 | 54.6 | 0 | 3 | 1 | 2 |
| 7.14 | 100 | 127 | 6.2 | 0 | 1 | 0 | 2 |
| 6.1 | 79 | 138 | 0 | 0 | 1 | 3 | 2 |
| 6.55 | 85 | 133 | 2.4 | 0 | 2 | 0 | 2 |
| 6.29 | 92 | 141 | 0 | 0 | 7 | 0 | 2 |
| 5.98 | 100 | 183 | 21.5 | 20 | 55 | 245 | 1 |
| 5.71 | 78 | 119 | 50.2 | 0 | 14 | 424 | 2 |
| 6.89 | 90 | 143 | 16.7 | 0 | 4 | 0 | 1 |
| 4.9 | 85 | 132 | 40.6 | 4 | 7 | 82 | 2 |
| 6.23 | 88 | 139 | 16.7 | 25 | 24 | 324 | 2 |
| 7.71 | 109 | 154 | 7.2 | 1 | 3 | 11 | 1 |
| 5.73 | 93 | 136 | 10.8 | 0 | 2 | 0 | 1 |
| 6.54 | 100 | 149 | 26 | 0 | 3 | 0 | 2 |
| 7.16 | 73 | 107 | 2.9 | 25 | 29 | 315 | 1 |
| 6.13 | 92 | 132 | 23.9 | 0 | 2 | 2 | 2 |
| 6.25 | 87 | 123 | 31.1 | 0 | 7 | 10 | 2 |
| 5.19 | 97 | 141 | 12 | 0 | 3 | 4 | 1 |
| 6.05 | 74 | 118 | 23.9 | 0 | 3 | 0 | 2 |
| 7.12 | 85 | 133 | 24.4 | 0 | 2 | 0 | 2 |
| 5.71 | 88 | 121 | 45.4 | 0 | 8 | 2 | 2 |
| 6.19 | 69 | 129 | 24.8 | 15 | 40 | 367 | 1 |
| 6.73 | 98 | 129 | 52.6 | 15 | 21 | 233 | 2 |
| 5.34 | 70 | 123 | 38.3 | 1 | 2 | 7 | 2 |
| 4.79 | 82 | 127 | 23.9 | 0 | 2 | 1 | 2 |
| 6.78 | 74 | 104 | 4.8 | 0 | 4 | 7 | 2 |
| 6.1 | 88 | 123 | 86.1 | 0 | 3 | 1 | 1 |
| 4.35 | 88 | 128 | 15.5 | 20 | 11 | 554 | 2 |
| 7.1 | 79 | 136 | 7.4 | 10 | 9 | 189 | 1 |
| 5.85 | 102 | 150 | 4.1 | 0 | 6 | 0 | 2 |
| 6.74 | 68 | 109 | 1.2 | 15 | 15 | 230 | 2 |
| 7.55 | 80 | 135 | 92.1 | 25 | 29 | 472 | 2 |
| 7.86 | 78 | 131 | 23.9 | 6 | 55 | 407 | 1 |
| 6.92 | 101 | 137 | 2.5 | 0 | 3 | 0 | 2 |
| 6.64 | 97 | 139 | 119.6 | 40 | 16 | 298 | 2 |
| 6.46 | 76 | 142 | 62.2 | 40 | 31 | 404 | 1 |
| 5.99 | 73 | 108 | 0 | 0 | 2 | 4 | 2 |
| 5.39 | 77 | 112 | 11 | 30 | 11 | 251 | 2 |
| 6.35 | 81 | 133 | 16.2 | 0 | 3 | 0 | 2 |
| 5.86 | 88 | 147 | 88.5 | 0 | 3 | 0 | 2 |
| 5.64 | 65 | 111 | 0 | 20 | 16 | 271 | 2 |
| 6.6 | 102 | 149 | 65.8 | 0 | 3 | 1 | 2 |
| 6.76 | 75 | 140 | 12.4 | 0 | 2 | 0 | 2 |
| 5.51 | 75 | 125 | 0 | 25 | 16 | 441 | 2 |
| 7.15 | 92 | 131 | 31.1 | 20 | 36 | 434 | 1 |
In: Statistics and Probability