hotel built 1880s 0.3-0.8 miles park 1940s theater 0.2-0.7 miles questions

Questions

A financial institution has the following portfolio of over-the-counter options on sterling: Type Position Delta of...

A financial institution has the following portfolio of over-the-counter options on sterling:

Type	Position	Delta of Option	Gamma of Option	Vega of Option
Call	-2,000	0.5	2.2	1.8
Call	-1000	0.8	0.6	0.2
Put	-4,000	-0.40	1.3	0.7
Call	-1000	0.70	1.8	1.4

A traded option is available with a delta of 0.6, a gamma of 1.5, and a vega of 0.8.

Is it possible to find a position in the traded option and in sterling that make the portfolio gamma neutral, vega neutral and delta neutral? Explain.

In: Finance

A financial institution has the following portfolio of over-the-counter options on sterling: Type, Position, Delta of...

A financial institution has the following portfolio of over-the-counter options on sterling: Type, Position, Delta of Option, Gamma of Option, Vega of Option ,Call -2,000 ,0.5, 2.2, 1.8; Call -1000, 0.8, 0.6 ,0.2 ;Put -4,000 ,-0.40, 1.3, 0.7 ;Call -1000 ,0.70, 1.8, 1.4;

A traded option is available with a delta of 0.6, a gamma of 1.5, and a vega of 0.8.

a. Is it possible to find a position in the traded option and in sterling that make the portfolio gamma neutral, vega neutral and delta neutral? Explain.

In: Finance

Recent research indicates that the effectiveness of antidepressant medication is directly related to the severity of...

Recent research indicates that the effectiveness of antidepressant medication is directly related to the severity of the depression (Khan, Brodhead, Kolts & Brown, 2005). Based on pretreatment depression scores, patients were divided into four groups based on their level of depression. After receiving the antidepressant medication, depression scores were measured again and the amount of improvement was recorded for each patient. The following data are similar to the results of the study.

Low Moderate	High Moderate	Moderately Severe	Severe
3.3	0.7	2	2.8
0	2.7	2.3	3.2
3.2	4	1.1	1.9
2.6	1.4	1	4.2
0.8	2.8	2.7	1.4
2.9	2.5	3.3	1.7
1.1	0	1.8	1.1
2.9	2.6	1.8	3.2
4.5	2	4.7	3.5
1.6	0.3	1.5	1.5
3.3	1.6	0.7	3.4
1	1.5	3	3.2
0.6	2.2	1.8	2.1
2.3	2.6	2.7	1.4
3.7	1.9	1.1	2.1
2.8	4.7	1.9	1.5
1.7	1.2	1.5	2.6
1.6	0.9	0	4.1
1.8	3.4	1.4	3.6
2.1	2	1.4	2.3
2.1	0.2	2.4	0.7
2.4	1.1	2.1	1.9
3.3	3.4	2.2	2.4
0.1	0.3	2.2	2.6
4.5	2.5	1.1	3.5
2.6	1.9	3.7	3.1
2.7	1.3	3.1	2.5
1.9	2.5	1.1	2.6
1.7	2	1.7	3.8
1.3	2.5	2.9	2.5
1.5	1.5	2.2	3.3
2.5	4.2	1.6	3.2
4.2	3.3	2.1	3.4
2.1	1.4	3.3	2.1
1.5	2.7	0.4	1.5
1.2	3	1.4	1.5
1.9	1	1.7	3.8
1.1	1.5	2.8	2.6
3.4	1.5	1.5	1.1
1.2	2.5	1.3	2.5
3.5	1.8	0	1.9
1.1	3.7	0.2	2.5
2.8	1.5	0.9	2.5
1.2	0.7	3.7	0
1.1	1.5	1.3	3.4
3.2	2.5	2.7	1.9
0.3	1.2	1.3	3.1
0.4	1.9	3.8	2.1
1.6	2.8	2.5	4.1
2.2	2.2	2	4.1
3.5	2.6	0.3	2.1
2	3.9	4	3.8
2.4	1.6	2	4.1
0	1.3	1.4	3.6
3.7	2	2.8	2.5
0.8	1.5	2.4	1.5
4.4	0.5	2.2	3.2
2.8	2.1	1.8	1.5
3	3.1	2.4	1.8
1.6	0.7	1	2.6
1.7	1.8	3.7	3.9

This is the summary table for the ANOVA test:

	S.S.	d.f.	M.S.
Between	14.348360655737	3	4.7827868852458
Within	260.6737704918	240	1.0861407103825
TOTAL	275.02213114754	243

From this table, you obtain the necessary statistics for the ANOVA:
F-ratio: 4.4034689424001
p-value: 0.00489
η2=η2= 0.052171658316617

What is your final conclusion? Use a significance level of α=0.02α=0.02.

There is a significant difference between treatments
These data do not provide evidence of a difference between the treatments

Explain what this tells us about the equality of mean?

Let's look at the boxplot for each treatment:

012345Depression ScoresLow ModerateHigh ModerateModerately SevereSevere

How could boxplots refine our conclusion in an ANOVA test? Your answer should address this specific problem.

Edit

Insert

Formats

In: Statistics and Probability

Recent research indicates that the effectiveness of antidepressant medication is directly related to the severity of...

Recent research indicates that the effectiveness of antidepressant medication is directly related to the severity of the depression (Khan, Brodhead, Kolts & Brown, 2005). Based on pretreatment depression scores, patients were divided into four groups based on their level of depression. After receiving the antidepressant medication, depression scores were measured again and the amount of improvement was recorded for each patient. The following data are similar to the results of the study.

Low Moderate	High Moderate	Moderately Severe	Severe
3.3	0.7	2	2.8
0	2.7	2.3	3.2
3.2	4	1.1	1.9
2.6	1.4	1	4.2
0.8	2.8	2.7	1.4
2.9	2.5	3.3	1.7
1.1	0	1.8	1.1
2.9	2.6	1.8	3.2
4.5	2	4.7	3.5
1.6	0.3	1.5	1.5
3.3	1.6	0.7	3.4
1	1.5	3	3.2
0.6	2.2	1.8	2.1
2.3	2.6	2.7	1.4
3.7	1.9	1.1	2.1
2.8	4.7	1.9	1.5
1.7	1.2	1.5	2.6
1.6	0.9	0	4.1
1.8	3.4	1.4	3.6
2.1	2	1.4	2.3
2.1	0.2	2.4	0.7
2.4	1.1	2.1	1.9
3.3	3.4	2.2	2.4
0.1	0.3	2.2	2.6
4.5	2.5	1.1	3.5
2.6	1.9	3.7	3.1
2.7	1.3	3.1	2.5
1.9	2.5	1.1	2.6
1.7	2	1.7	3.8
1.3	2.5	2.9	2.5
1.5	1.5	2.2	3.3
2.5	4.2	1.6	3.2
4.2	3.3	2.1	3.4
2.1	1.4	3.3	2.1
1.5	2.7	0.4	1.5
1.2	3	1.4	1.5
1.9	1	1.7	3.8
1.1	1.5	2.8	2.6
3.4	1.5	1.5	1.1
1.2	2.5	1.3	2.5
3.5	1.8	0	1.9
1.1	3.7	0.2	2.5
2.8	1.5	0.9	2.5
1.2	0.7	3.7	0
1.1	1.5	1.3	3.4
3.2	2.5	2.7	1.9
0.3	1.2	1.3	3.1
0.4	1.9	3.8	2.1
1.6	2.8	2.5	4.1
2.2	2.2	2	4.1
3.5	2.6	0.3	2.1
2	3.9	4	3.8
2.4	1.6	2	4.1
0	1.3	1.4	3.6
3.7	2	2.8	2.5
0.8	1.5	2.4	1.5
4.4	0.5	2.2	3.2
2.8	2.1	1.8	1.5
3	3.1	2.4	1.8
1.6	0.7	1	2.6
1.7	1.8	3.7	3.9

This is the summary table for the ANOVA test:

	S.S.	d.f.	M.S.
Between	14.348360655737	3	4.7827868852458
Within	260.6737704918	240	1.0861407103825
TOTAL	275.02213114754	243

From this table, you obtain the necessary statistics for the ANOVA:
F-ratio: 4.4034689424001
p-value: 0.00489
η2=η2= 0.052171658316617

What is your final conclusion? Use a significance level of α=0.02α=0.02.

There is a significant difference between treatments
These data do not provide evidence of a difference between the treatments

Explain what this tells us about the equality of mean?

Let's look at the boxplot for each treatment:

012345Depression ScoresLow ModerateHigh ModerateModerately SevereSevere

How could boxplots refine our conclusion in an ANOVA test? Your answer should address this specific problem.

Edit

Insert

Formats

In: Statistics and Probability

(1). Use the Wilcoxon matched-pairs signed rank test (small sample size) to determine whether there is...

(1). Use the Wilcoxon matched-pairs signed rank test (small sample size) to determine whether there is a significant difference between the related populations represented by the matched pairs given here. Assume a = .05 (Written).

Group1	Group2	d
5.6	6.4	-0.8
1.3	1.5	-0.2
4.7	4.6	0.1
3.8	4.3	-0.5
2.4	2.1	0.3
5.5	6	-0.5
5.1	5.2	-0.1
4.6	4.5	0.1
3.7	4.5	-0.8

In: Statistics and Probability

If x is a binomial random variable, use the binomial probability table to find the probabilities...

If x is a binomial random variable, use the binomial probability table to find the probabilities below.

a. P(x=3) for n=10, p=0.5

b. P(x≤4) for n=15, p=0.3

c. P(x>1) for n=5, p=0.2

d. P(x<6) for n=15, p=0.8

e. P(x≥14) for n=25, p=0.8

f. P(x=3) for n=20, p=0.1

In: Statistics and Probability

Imagine you are a pipeline company trying to sell a new project to a shipper of...

Imagine you are a pipeline company trying to sell a new project to a shipper of oil for a new refinery.

Pipeline Length: 266 miles (16,853,760 inches)

The refinery is scheduled to take 300,000 barrels per day of Bakken Crude at typical temperatures. Temperature: 60 degrees Fahrenheit. Flow rate = 33687.5 in³/s. Kinematic viscosity: 3.337 centistokes or 0.0051723603 in²/s. Specific Gravity = 0.7

Calculate Reynold's number.

Friction Factor: 0.0275.

Calculate Pressure Drop.

Pipeline flows entirely through class I locations except for 10 miles located in a class IV location. You have the option of bypassing the class IV location by running the pipeline an additional 50 miles.

Pipe Diameter: 12 inches X-42 Schedule 20

Calculate Maximum Pressure

The inlet pressure of pumping stations should not fall below 400 psi.

Set distance between pumping stations optimally.

Calculate horsepower requirements

In: Mechanical Engineering

Question 3. - Please do c, d and e An engineer suspects that the surface finish...

Question 3. - Please do c, d and e

An engineer suspects that the surface finish of a metal part is influenced by the feed rate and the depth of cut of a particular manufacturing machine. An experiment is conducted and the data can be found in SurfaceFinish.jmp on eCampus.

a. State the two-way ANOVA model corresponding to this data. Be sure to define each term in your model and list any assumptions that are made.

b. Perform the test to determine if the model from part a) is significant.

c. Prepare a profile plot for the cell mean surface finish scores. Does it appear that any interaction effects are present? Explain.

d. Test whether or not interaction effects are present.

e. Given that low surface finish scores are desirable, which combination(s) of feed rate and depth of cut do you recommend?

Depth of Cut (in) = 0.15 0.15 0.15 0.18 0.18 0.18 0.2 0.2 0.2 0.25 0.25 0.25 0.15 0.15 0.15 0.18 0.18 0.18 0.2 0.2 0.2 0.25 0.25 0.25 0.15 0.15 0.15 0.18 0.18 0.18 0.2 0.2 0.2 0.25 0.25 0.25

Feed Rate (in/min) = 0.2 0.2 0.2 0.2 0.2 0.2 0.2 0.2 0.2 0.2 0.2 0.2 0.25 0.25 0.25 0.25 0.25 0.25 0.25 0.25 0.25 0.25 0.25 0.25 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3

Surface Finsih Score = 74 64 60 79 68 73 82 88 92 99 104 96 92 86 88 98 104 88 99 108 95 104 110 99 99 98 102 104 99 95 108 110 99 114 107 111

Depth of Cut (in)

Feed Rate (in/min)

Surface Finish Score

0.15

0.2

74

0.15

0.2

64

0.15

0.2

60

0.18

0.2

79

0.18

0.2

68

0.18

0.2

73

0.2

82

0.2

88

0.2

92

0.25

0.2

99

0.25

0.2

104

0.25

0.2

96

0.15

0.25

92

0.15

0.25

86

0.15

0.25

88

0.18

0.25

98

0.18

0.25

104

0.18

0.25

88

0.2

0.25

99

0.2

0.25

108

0.2

0.25

95

0.25

104

0.25

110

0.25

99

0.15

0.3

99

0.15

0.3

98

0.15

0.3

102

0.18

0.3

104

0.18

0.3

99

0.18

0.3

95

0.2

0.3

108

0.2

0.3

110

0.2

0.3

99

0.25

0.3

114

0.25

0.3

107

0.25

0.3

111

In: Statistics and Probability

Q4Y4 Q1Y5 Q2Y5 Q3Y5 Q4Y5 Total Budgeted Sales (Actual for Q4Y4) 10000 11000 14000 15000 17000...

Q4Y4	Q1Y5	Q2Y5	Q3Y5	Q4Y5	Total
Budgeted Sales (Actual for Q4Y4)	10000	11000	14000	15000	17000	57000
Selling Price/per unit	9	9	9	9	9	9
Sale Collection
In quarter of sale	0.8
In following quarter	0.2
Desired ending finished goods inventory		2500	2200	2400	2100	2100
Raw Materials/per unit	5	5	5	5	5	5
Desired Ending raw material inventory Inventory	5000	8000	7000	6000	5000	5000
Raw material price/per unit	2	2	2	2	2	2
Accounts payable
In quarter of purchase	0.7
In following quarter	0.3
Q4Y4 raw material cost	100000

REQUIRED:

Sale Budget	Year 5 Quarters
	1	2	3	4	Year

Production Budget

Material Budget

Cash Receipts

Cash Payments

In: Accounting

Almost all U.S. light-rail systems use electric cars that run on tracks built at street level....

Almost all U.S. light-rail systems use electric cars that run on tracks built at street level. The Federal Transit Administration claims light-rail is one of the safest modes of travel, with an accident rate of .99 accidents per million passenger miles as compared to 2.29 for buses. The following data show the miles of track and the weekday ridership in thousands of passengers for six light-rail systems.

City	Miles of Track	Ridership (1000s)
Cleveland	13	16
Denver	15	36
Portland	36	82
Sacramento	19	32
San Diego	45	76
San Jose	29	31
St. Louis	32	43

Use these data to develop an estimated regression equation that could be used to predict the ridership given the miles of track.

Compute b₀ and b₁ (to 2 decimals).
b₁
b₀

Complete the estimated regression equation (to 2 decimals).
y =  +  x
Compute the following (to 1 decimal):

SSE

SST

SSR

MSE
What is the coefficient of determination (to 3 decimals)? Note: report r² between 0 and 1.

Does the estimated regression equation provide a good fit?
SelectYes, it even provides an excellent fitYes, it provides a good fitNo, it does not provide a good fitItem 10
Develop a 95% confidence interval for the mean weekday ridership for all light-rail systems with 30 miles of track (to 1 decimal).
( , )
Suppose that Charlotte is considering construction of a light-rail system with 30 miles of track. Develop a 95% prediction interval for the weekday ridership for the Charlotte system (to 1 decimal).
( , )

Do you think that the prediction interval you developed would be of value to Charlotte planners in anticipating the number of weekday riders for their new light-rail system?

In: Statistics and Probability

SSE
SST
SSR
MSE