Questions
Stock Inc. has two sites in Pittsburgh that are four miles apart. Each site consists of...

Stock Inc. has two sites in Pittsburgh that are four miles apart. Each site consists of a large factory with office space for 25 users at the front of the factory and up to 50 workstations in two work cells on each factory floor. All office users need access to an inventory database that runs on a server at the Allegheny Street location; they also need access to a billing application with data residing on a server at the Monongahela site. All factory floor users also need access to the inventory database at the Allegheny Street location. Office space is permanently configured, but the manufacturing space must be reconfigured before each new manufacturing run begins. Wiring closets are available in the office space. Nothing but a concrete floor and overhead girders stay the same in the work cell areas. The computers must share sensitive data and control access to files. Aside from the two databases, which run on the two servers, office computers must run standard word-processing and spreadsheet programs. Work cell machines are used strictly for updating inventory and quality control information for the Allegheny Street inventory database. Workstations in the manufacturing cells are switched on only when they’re in use, which might occur during different phases of a manufacturing run. Seldom is a machine in use constantly on the factory floor. Use the following write-on lines to evaluate the requirements for this network. After you finish, determine the best network topology or topology combination for the company. On a blank piece of paper, sketch the network design you think best suits ENorm, Inc.’s needs.

● Will the network be peer to peer or server-based?

● How many computers will be attached to the network?

● What topology works best for the offices, given the availability of wiring closets? What topology works best for the factory floor, given its need for constant reconfiguration?

In: Computer Science

An automobile manufacturer claims that their van has a 45.945.9 miles/gallon (MPG) rating. An independent testing...

An automobile manufacturer claims that their van has a 45.945.9 miles/gallon (MPG) rating. An independent testing firm has been contracted to test the MPG for this van. After testing 1111 vans they found a mean MPG of 45.745.7 with a variance of 2.892.89. Is there sufficient evidence at the 0.0250.025 level that the vans underperform the manufacturer's MPG rating? Assume the population distribution is approximately normal.

Step 1 of 5:

State the null and alternative hypotheses.

Step 2 of 5:

Find the value of the test statistic. Round your answer to three decimal places.

Step 3 of 5:

Specify if the test is one-tailed or two-tailed.

Step 4 of 5:

Determine the decision rule for rejecting the null hypothesis. Round your answer to three decimal places.

Step 5 of 5:

Make the decision to reject or fail to reject the null hypothesis.

In: Statistics and Probability

Lon Timur is an accounting major at a midwestern state university located approximately 60 miles from...

Lon Timur is an accounting major at a midwestern state university located approximately 60 miles from a major city. Many of the students attending the university are from the metropolitan area and visit their homes regularly on the weekends. Lon, an entrepreneur at heart, realizes that few good commuting alternatives are available for students doing weekend travel. He believes that a weekend commuting service could be organized and run profitably from several suburban and downtown shopping mall locations. Lon has gathered the following investment information.

1.Five used vans would cost a total of $75,920 to purchase and would have a 3-year useful life with negligible salvage value. Lon plans to use straight-line depreciation.

2.Ten drivers would have to be employed at a total payroll expense of $48,700.

3.Other annual out-of-pocket expenses associated with running the commuter service would include Gasoline $16,100, Maintenance $3,200, Repairs $4,300, Insurance $4,000, and Advertising $2,500.

4.Lon has visited several financial institutions to discuss funding. The best interest rate he has been able to negotiate is 15%. Use this rate for cost of capital.

5.Lon expects each van to make ten round trips weekly and carry an average of six students each trip. The service is expected to operate 30 weeks each year, and each student will be charged $12 for a round-trip ticket.

a. Determine the annual (1) net income and (2) net annual cash flows for the commuter service. (Round answers to 0 decimal places, e.g. 125.)

b. Compute (1) the cash payback period and (2) the annual rate of return. (Round answers to 2 decimal places, e.g. 10.50.)

c. Compute the net present value of the commuter service. (Round answer to 0 decimal places, e.g. 125.)

In: Accounting

Stock Inc. has two sites in Pittsburgh that are four miles apart. Each site consists of...

Stock Inc. has two sites in Pittsburgh that are four miles apart. Each site consists of a large factory with office space for 25 users at the front of the factory and up to 50 workstations in two work cells on each factory floor. All office users need access to an inventory database that runs on a server at the Allegheny Street location; they also need access to a billing application with data residing on a server at the Monongahela site. All factory floor users also need access to the inventory database at the Allegheny Street location. Office space is permanently configured, but the manufacturing space must be reconfigured before each new manufacturing run begins. Wiring closets are available in the office space. Nothing but a concrete floor and overhead girders stay the same in the work cell areas. The computers must share sensitive data and control access to files. Aside from the two databases, which run on the two servers, office computers must run standard word-processing and spreadsheet programs. Work cell machines are used strictly for updating inventory and quality control information for the Allegheny Street inventory database. Workstations in the manufacturing cells are switched on only when they’re in use, which might occur during different phases of a manufacturing run. Seldom is a machine in use constantly on the factory floor. Use the following write-on lines to evaluate the requirements for this network. After you finish, determine the best network topology or topology combination for the company. On a blank piece of paper, sketch the network design you think best suits ENorm, Inc.’s needs.

● Will the network be peer to peer or server-based?

● How many computers will be attached to the network?

● What topology works best for the offices, given the availability of wiring closets? What topology works best for the factory floor, given its need for constant reconfiguration?

can i also have the network design please

In: Computer Science

Distance (air miles) Fare (dollars) An air travel service is interested in the relationship between distance...

Distance (air miles) Fare (dollars) An air travel service is interested in the relationship between distance and airfare. Using distance as the independent variable and an alpha level of .05 answer the following: 636 109 2395 252 2176 221 605 151 403 138 1258 209 264 254 627 259 2342 215 177 128 2521 348 1050 224 441 175 1021 256 336 121 752 252 1333 206 1460 167 2350 308 621 152 737 175 853 191 1894 231 2465 251 1891 291 1028 260 545 123 1489 211 452 139 969 243 a. Write the regression equation. b. Interpret the regression constant and coefficient. c. Forecast a value for the airfare. d. Test the significance of the regression model. e. Test the significance of the regression coefficient. f. Interpret the coefficient of determination. g. Are there any violations of the general linear model?

In: Statistics and Probability

Lon Timur is an accounting major at a midwestern state university located approximately 60 miles from...

Lon Timur is an accounting major at a midwestern state university located approximately 60 miles from a major city. Many of the students attending the university are from the metropolitan area and visit their homes regularly on the weekends. Lon, an entrepreneur at heart, realizes that few good commuting alternatives are available for students doing weekend travel. He believes that a weekend commuting service could be organized and run profitably from several suburban and downtown shopping mall locations. Lon has gathered the following investment information.

1. Five used vans would cost a total of $74,538 to purchase and would have a 3-year useful life with negligible salvage value. Lon plans to use straight-line depreciation.
2. Ten drivers would have to be employed at a total payroll expense of $48,200.
3. Other annual out-of-pocket expenses associated with running the commuter service would include Gasoline $15,700, Maintenance $3,000, Repairs $4,100, Insurance $4,500, and Advertising $2,200.
4. Lon has visited several financial institutions to discuss funding. The best interest rate he has been able to negotiate is 15%. Use this rate for cost of capital.
5. Lon expects each van to make ten round trips weekly and carry an average of six students each trip. The service is expected to operate 30 weeks each year, and each student will be charged $12 for a round-trip ticket.


Click here to view PV table.

(a)

Determine the annual (1) net income and (2) net annual cash flows for the commuter service. (Round answers to 0 decimal places, e.g. 125.)

Net income $
Net annual cash flows $


(b)

Compute (1) the cash payback period and (2) the annual rate of return. (Round answers to 2 decimal places, e.g. 10.50.)

Cash payback period years
Annual rate of return %


(c)

Compute the net present value of the commuter service. (Round answer to 0 decimal places, e.g. 125. If the net present value is negative, use either a negative sign preceding the number eg -45 or parentheses eg (45). For calculation purposes, use 5 decimal places as displayed in the factor table provided.)

Net present value

In: Accounting

7. Obtain the following summaries for Miles and Miles_1. [Go to stat, Summary Stats, Columns, Select...

7. Obtain the following summaries for Miles and Miles_1.

[Go to stat, Summary Stats, Columns, Select columns, choose Statistics, Compute.]

Variable

N

Mean

Std

Median

Q1

Q3

Min

Max

Range

IQR

Miles

Miles_1

Note you should notice that Mean ‘Miles’ is much larger than the Mean ‘Miles_1’, and Median ‘Miles’ is similar to ‘Median ‘Miles_1’. This justifies your results in Q3.

(a) Compute an estimate of standard deviation, s, for Miles_1 using Range/6 = _______________.

How close is this estimated s to the actual standard deviation of Miles_1:

Estimate s.d./Actual s.d. = _____________

Suppose a student has the Distance of 40. Use the Empirical rule based on the information of ‘Miles_1 variable to decide if this is an unusual Distance or not.

[Note: since the distribution of Miles_1 is not mounded-shaped, Empirical Rule does not work well. However, we can use Empirical rule to identify unusual cases.]

(e) Suppose a student has the Distance of 300. Compute the corresponding Z-score and using the Empirical rule to decide if this is an unusually far distance away from home or not.

User_type Gender Grade Miles Region U_size Area Right_Distance Expense Reputation Friends Scholarship Friendly Size Small_Community Right_University In_State Recommendation Alumni
student female sophomore 140 mw 20000_30000 rural 1 1 1 0 1 0 0 0 0 0 0 0
student female freshman 57 mw 10000_20000 rural 1 0 0 0 0 1 1 0 0 1 0 0
student male sophomore 72 mw 20000_30000 rural 1 1 1 1 0 1 0 0 1 0 0 0
student female junior 275 mw 10000_20000 rural 0 0 0 0 1 1 1 0 0 0 0 0
student male junior 100 mw 20000_30000 rural 1 0 0 0 0 1 0 0 0 0 1 0
student male junior 125 mw 20000_30000 rural 1 0 1 0 0 0 0 0 0 0 1 0
student male junior 200 se 10000_20000 rural 1 1 1 0 0 1 1 0 0 0 0 0
student female sophomore 123 mw 20000_30000 rural 1 0 0 0 0 0 0 0 0 0 0 0
student female senior 150 mw 10000_20000 rural 1 0 0 0 0 1 1 0 1 1 0 0
student male junior 65 mw 10000_20000 rural 1 0 0 0 1 0 1 0 0 0 1 0
student male sophomore 170 mw 20000_30000 rural 1 0 0 0 0 1 1 0 0 0 1 1
student male freshman 120 wc 10000_20000 rural 1 0 1 0 0 1 0 0 0 1 1 0
student male sophomore 375 mw 10000_20000 rural 1 0 0 0 1 0 0 0 0 0 0 0
student male junior 10 mw 10000_20000 rural 0 1 0 0 0 0 0 0 0 0 1 1
student male sophomore 62 mw 10000_20000 rural 1 0 0 0 0 0 0 0 0 0 0 0
student female graduate 20 mw 20000_30000 rural 1 0 0 1 0 0 0 0 0 1 0 0
student female senior 142 mw 20000_30000 rural 0 0 0 0 1 0 1 0 0 0 0 1
student male junior 151 mw 20000_30000 rural 1 0 1 0 0 0 0 0 0 0 0 0
student female sophomore 200 mw 10000_20000 rural 0 0 1 1 0 1 1 0 0 0 0 0
student male junior 132 mw 20000_30000 rural 0 0 1 0 0 1 0 0 0 0 1 1
student female junior 41.6 mw 10000_20000 rural 1 0 1 0 0 0 0 0 0 0 0 1
student female other 200 se 20000_30000 rural 1 1 1 0 0 1 1 0 0 0 1 0
student female senior 33 mw 20000_30000 rural 1 0 1 0 0 0 0 0 0 1 0 1
student male sophomore 20 mw 10000_20000 rural 1 0 0 1 1 0 0 0 0 1 0 1
student male sophomore 328 ne 10000_20000 urban 0 0 0 0 0 0 0 0 0 0 1 0
student male freshman 9000 mw 20000_30000 rural 0 0 0 1 0 0 0 0 0 0 0 0
student female senior 130 se 10000_20000 urban 0 1 1 0 0 0 0 0 0 1 0 0
student female freshman 180 mw 20000_30000 rural 0 0 1 0 1 1 1 0 0 0 0 1
student male sophomore 40 mw 10000_20000 rural 0 0 1 1 0 1 1 0 0 1 1 0
student female junior 100 mw 10000_20000 rural 1 1 1 1 1 1 0 0 0 0 1 0
student female sophomore 210 mw 20000_30000 rural 0 0 1 0 0 0 0 0 0 1 1 0
student male junior 200 mw 20000_30000 rural 0 0 1 0 0 1 0 0 0 1 1 0
student male junior 100 ne 10000_20000 urban 1 0 0 0 1 0 0 0 0 0 0 0
student male senior 150 mw 20000_30000 rural 0 1 0 0 0 0 0 0 0 1 0 1
student male senior 103 mw 20000_30000 rural 0 0 1 0 0 0 0 0 0 0 0 0
student male sophomore 143 mw 20000_30000 rural 1 0 0 0 0 0 0 0 1 1 0 0
student female junior 550 mw 10000_20000 rural 0 0 1 0 0 0 0 0 0 0 0 0
student male sophomore 140 mw 10000_20000 rural 0 0 0 1 0 0 1 0 0 0 0 1
student male graduate 136 mw 10000_20000 rural 0 0 0 0 0 0 0 0 0 0 0 1
student female freshman 171 mw 20000_30000 rural 1 0 0 0 1 0 0 0 0 0 0 0
student male graduate 4.1 mw 20000_30000 rural 1 0 1 0 0 1 1 1 0 1 0 0
student male senior 8 mw 10000_20000 urban 1 0 0 0 0 0 1 1 0 1 0 0
student male junior 200 mw 20000_30000 rural 1 1 1 1 0 0 1 1 1 0 0 1
student male junior 140 mw 10000_20000 rural 1 0 0 1 0 1 1 0 0 1 0 0
student female sophomore 130 mw 10000_20000 rural 1 0 0 0 0 0 1 0 0 0 0 0
student male junior 65 mw 20000_30000 rural 0 1 1 0 0 0 0 0 0 1 0 0
student male freshman 137 mw 10000_20000 rural 1 0 1 0 0 0 0 0 1 0 0 0
student male junior 140 mw 20000_30000 rural 1 0 0 0 0 0 0 0 0 0 0 0
student male junior 10 mw 10000_20000 rural 0 0 1 0 1 0 0 0 0 0 0 1
student female junior 100 mw 10000_20000 rural 0 1 0 0 0 1 1 1 0 0 0 0
student female senior 150 mw 10000_20000 rural 0 0 1 0 1 0 0 0 0 0 0 0
student male freshman 8.7 mw 20000_30000 rural 0 0 0 0 1 0 0 0 0 0 0 0
student male junior 200 mw 10000_20000 null 1 0 1 1 0 1 1 0 1 1 0 0
student male sophomore 50 mw 10000_20000 rural 1 0 0 0 1 0 0 0 0 0 0 0
student male junior 120 mw 20000_30000 rural 0 1 1 0 0 0 1 1 1 0 0 1
student female sophomore 56 mw 10000_20000 rural 1 0 0 0 0 0 0 0 1 0 0 1
student male senior 2 ne 20000_30000 rural 0 0 0 0 0 0 0 0 0 1 0 0
student female junior 170 mw 10000_20000 rural 1 1 0 0 1 0 0 0 0 0 0 0
student male freshman 133 mw 20000_30000 rural 1 1 0 0 1 0 1 0 0 0 0 0
student male sophomore 125 mw 20000_30000 rural 1 0 0 0 0 0 1 1 0 0 0 0
student male junior 163 ne 10000_20000 rural 1 0 0 0 0 0 0 0 0 0 0 1
student male junior 90 mw 20000_30000 rural 1 1 0 0 0 0 1 1 1 0 1 1
instructor female senior 150 mw 20000_30000 rural 0 0 0 0 1 0 1 0 0 0 0 0
student male senior 45 mw 10000_20000 rural 1 0 0 0 0 0 0 0 0 1 0 0
student female sophomore 139 mw 20000_30000 rural 1 0 0 1 1 1 0 0 0 1 0 0
student male sophomore 160 mw 20000_30000 rural 1 0 0 1 1 0 1 0 0 0 0 0
student male sophomore 100 mw 10000_20000 rural 1 0 0 1 0 0 0 0 1 0 0 0
student male sophomore 50 mw 10000_20000 rural 0 0 0 0 1 0 0 0 0 0 0 0
student male graduate 115 mw 10000_20000 rural 0 0 0 1 0 0 0 0 0 0 0 1
student male senior 30 mw 20000_30000 rural 0 0 1 0 0 0 0 0 0 0 0 0
student male junior 40 mw 20000_30000 rural 0 0 0 0 1 0 0 0 0 0 0 0
student male junior 0 mw 20000_30000 rural 0 0 0 1 0 0 0 0 1 1 0 0
student male junior 2100 mw 20000_30000 rural 0 0 0 0 1 0 0 0 0 0 0 0
student female junior 45 mw 10000_20000 rural 1 0 0 1 1 1 1 1 0 0 0 1
student male junior 8 mw 10000_20000 rural 0 1 1 0 1 1 1 0 1 0 0 0
student female senior 125 mw 20000_30000 rural 1 1 0 1 1 0 1 0 0 1 0 0
student male graduate 19 mw 20000_30000 rural 0 0 1 1 0 1 1 0 0 1 0 1
student female junior 110 mw 10000_20000 rural 1 0 1 0 0 0 0 0 0 1 0 0
student female junior 60 ne 20000_30000 rural 1 0 0 0 1 0 1 0 0 1 0 1
student male junior 85 mw 20000_30000 urban 1 1 1 1 0 1 0 0 1 1 0 0
student female sophomore 72 mw 20000_30000 rural 1 1 0 0 1 1 0 0 0 1 0 0
student male graduate 145 mw 20000_30000 rural 0 0 1 1 1 1 1 1 0 0 0 0
instructor male other 50 mw 20000_30000 rural 0 0 0 0 0 0 0 0 0 0 0 0
student female sophomore 9999.99 mw 20000_30000 rural 0 0 0 0 1 0 0 0 0 0 0 0
student female junior 15 mw 20000_30000 rural 0 0 0 0 0 0 0 0 0 0 0 1
student male sophomore 145 mw 10000_20000 rural 1 0 0 0 0 0 1 0 1 0 0 0
student male sophomore 155 mw 20000_30000 rural 1 1 1 1 0 0 1 0 0 1 0 1
student female other 125 mw 20000_30000 rural 0 0 1 0 0 0 0 0 0 0 0 0
student male sophomore 120 mw 10000_20000 rural 1 0 1 0 0 1 0 0 1 0 0 0
student male junior 160 mw 20000_30000 rural 1 1 1 0 0 1 1 0 0 0 0 0
student male sophomore 130 mw 10000_20000 rural 1 1 1 1 0 1 1 1 0 0 1 1
student female senior 0 mw 20000_30000 rural 0 0 0 0 0 0 0 0 0 0 0 0
student female freshman 120 mw 20000_30000 rural 1 0 0 1 1 1 1 0 0 1 0 1
student male freshman 170 mw 20000_30000 urban 1 0 0 0 1 1 0 0 0 1 0 0
student male junior 5 mw 10000_20000 rural 0 1 0 1 1 0 0 0 0 1 0 0
student male junior 120 mw 20000_30000 rural 1 1 0 0 0 0 1 1 0 1 0 0
student female junior 150 mw 10000_20000 rural 1 1 0 1 0 1 1 1 1 0 0 0
student male sophomore 70 mw 20000_30000 rural 0 1 1 1 0 0 1 0 0 0 0 0
student female junior 86.8 mw 10000_20000 rural 1 1 1 0 1 1 1 0 0 1 0 0
student female sophomore 105 mw 10000_20000 rural 0 0 0 0 1 0 0 0 0 0 0 0
student female freshman 8000 ne 5000_10000 rural 0 0 0 0 0 0 1 0 0 0 0 0
student male senior 996 se 20000_30000 rural 0 1 1 0 0 0 0 0 0 0 0 1
student male freshman 80 mw 20000_30000 rural 1 1 1 0 1 1 0 0 0 0 0 0
student female sophomore 124 mw 20000_30000 rural 1 1 1 0 1 1 0 0 0 0 0 0
student male senior 155 mw 20000_30000 rural 0 0 0 0 0 0 1 1 0 0 0 0
student male junior 50 mw 20000_30000 urban 1 0 1 1 0 1 0 0 0 1 1 0
student female sophomore 70 mw 10000_20000 urban 0 0 1 1 1 1 1 1 0 1 0 0
student male senior 55 mw 10000_20000 rural 0 1 0 0 0 0 1 0 1 1 0 0
student male sophomore 150 mw 20000_30000 rural 1 1 1 1 1 1 0 0 0 1 0 1
student female senior 80 mw 20000_30000 rural 1 1 1 0 0 0 1 1 0 1 0 0
student male junior 112 mw 20000_30000 rural 1 1 1 1 0 0 0 0 0 0 0 0
student female senior 150 mw 20000_30000 rural 1 0 1 0 0 1 1 1 0 1 0 0
student female sophomore 160 ne 10000_20000 rural 1 1 1 0 1 1 1 0 0 1 0 0
student male freshman 168 mw 20000_30000 rural 0 0 0 0 0 0 0 0 0 0 0 0
student female freshman 67.7 mw 20000_30000 rural 0 1 1 0 0 1 0 1 0 0 0 0
student male junior 125 mw 10000_20000 rural 0 0 1 0 0 0 0 0 0 0 1 0
student male freshman 9999.99 mw 20000_30000 rural 0 1 0 0 1 1 0 0 1 0 0 0
student male sophomore 113 so 20000_30000 rural 1 0 1 1 1 1 0 0 0 0 0 0
student male sophomore 120 mw 10000_20000 rural 1 0 0 0 0 1 1 0 0 0 1 1
student male sophomore 2184 wc 20000_30000 rural 0 0 0 1 0 1 0 0 1 0 0 0
student female junior 153 se 10000_20000 rural 1 0 0 1 0 1 1 0 0 1 0 0
student female sophomore 55 ne 10000_20000 rural 1 1 1 1 1 0 1 1 0 1 1 0
student female sophomore 2 mw 10000_20000 rural 0 0 1 0 0 1 0 0 0 0 1 0
student male senior 25 mw 10000_20000 rural 1 0 0 0 0 0 1 0 0 0 0 0
student male junior 22 ne 20000_30000 rural 1 1 1 0 0 1 0 0 0 1 1 0
student male senior 150 se 10000_20000 rural 0 1 1 0 0 0 0 0 0 0 0 0
student male junior 73 mw 10000_20000 rural 0 1 0 0 1 1 1 1 0 0 0 1
student male senior 65 mw 20000_30000 rural 0 1 0 0 0 0 1 1 0 0 0 0
student female freshman 3 mw 10000_20000 rural 0 0 0 0 0 0 0 0 0 0 0 0
student male junior 100 null 20000_30000 rural 1 0 0 0 0 0 0 0 1 0 0 0
student male junior 90 mw 20000_30000 rural 1 1 0 1 0 0 0 0 0 1 0 0
student female senior 30 mw 20000_30000 rural 0 0 0 0 0 0 0 0 0 0 1 0
student female sophomore 238 mw 20000_30000 rural 1 0 0 0 0 0 0 0 1 0 0 1
student male freshman 9000 ne 20000_30000 rural 0 0 0 0 0 0 1 1 0 0 0 0
student male senior 110 so 10000_20000 rural 0 0 0 1 0 1 1 0 0 1 0 1
student female freshman 45 mw 20000_30000 rural 1 0 1 0 1 1 0 0 0 1 0 0
student male junior 155 mw 20000_30000 rural 1 1 0 1 0 1 1 1 0 0 1 0
student female senior 15 mw 10000_20000 rural 0 1 0 0 1 1 0 1 0 1 0 1
student male sophomore 20 mw 5000_10000 rural 1 0 1 1 0 0 0 0 1 0 0 0
student male graduate 5 mw 20000_30000 rural 1 0 1 0 0 1 0 0 0 0 0 0
student female graduate 1.5 mw 20000_30000 rural 0 0 0 0 0 0 1 0 0 0 0 0
student female graduate 12 mw 20000_30000 rural 0 1 0 0 0 0 0 0 0 0 0 0
student female sophomore 140 mw 10000_20000 rural 1 1 1 0 1 1 1 0 0 0 1 0
student male sophomore 61 mw 10000_20000 rural 1 1 0 0 0 0 1 1 0 0 0 1
student female senior 47 mw 10000_20000 rural 0 0 0 0 1 0 0 0 0 0 0 0
student male senior 132 mw 20000_30000 rural 0 0 0 0 0 0 1 0 0 0 0 0
student male sophomore 130 mw 20000_30000 rural 1 1 1 1 0 1 0 1 0 0 1 0
student male junior 120 mw 10000_20000 rural 0 0 1 1 0 0 0 0 0 0 0 0
student male junior 45 mw 20000_30000 urban 1 0 0 0 1 0 0 0 0 0 0 0
student male junior 35 mw 20000_30000 rural 0 1 1 0 1 1 0 0 0 0 1 0
student female junior 85 ne 10000_20000 rural 1 1 0 1 0 0 0 0 0 1 0 0
student male junior 110 ne 10000_20000 rural 0 1 0 0 1 0 0 0 0 0 0 0
student female sophomore 110 mw 10000_20000 rural 1 0 0 0 0 0 0 0 0 0 0 0
student female junior 100 mw 10000_20000 rural 1 1 1 0 1 0 0 0 0 1 0 1
student female junior 110 mw 20000_30000 rural 1 1 0 0 0 1 0 0 0 0 0 0
student female junior 105 mw 20000_30000 rural 1 0 0 0 1 1 0 0 0 1 1 0
student male sophomore 120 mw 20000_30000 rural 0 1 0 1 0 0 0 0 0 0 0 0
student male junior 8 mw 20000_30000 rural 0 1 0 0 0 0 0 0 0 0 0 0
student male senior 1 mw 20000_30000 rural 0 0 1 1 0 1 0 0 0 0 1 1
student male senior 250 mw 10000_20000 rural 1 1 0 0 1 1 0 0 0 0 0 0
student male senior 40 ne 20000_30000 rural 1 0 1 1 1 0 1 0 0 0 0 1
student male senior 65 mw 20000_30000 rural 0 1 0 0 0 0 1 0 0 0 0 0
student male senior 12 se 5000_10000 rural 0 1 1 0 0 1 0 1 0 1 1 0
student male senior 160 mw 20000_30000 rural 1 1 1 0 1 0 0 0 0 0 0 0
student female junior 122 mw 20000_30000 rural 1 0 0 0 1 0 0 0 0 0 0 0
student male senior 130 mw 20000_30000 rural 0 1 1 1 0 1 1 1 0 1 0 0
student female sophomore 250 mw 10000_20000 rural 0 0 1 0 0 1 0 0 0 0 1 1
student female freshman 6 mw 20000_30000 urban 1 0 0 0 0 0 0 0 0 0 0 1
student male sophomore 130 mw 20000_30000 rural 1 1 0 0 0 1 1 0 0 0 0 0
student male sophomore 130 mw 10000_20000 rural 0 0 0 0 0 0 1 0 0 0 0 0
student male sophomore 154 mw 20000_30000 rural 1 1 1 1 1 1 0 0 0 0 1 0
student female sophomore 150 mw 20000_30000 rural 1 0 0 1 1 1 1 0 0 0 1 1
student male junior 100 mw 20000_30000 rural 1 0 1 0 1 1 0 0 0 0 0 0
student male junior 280 mw 10000_20000 rural 0 0 0 0 0 0 1 0 0 0 0 0
student male sophomore 121 mw 20000_30000 rural 1 0 1 0 0 1 0 0 0 1 0 0
student female junior 60 ne 20000_30000 rural 1 0 0 0 0 0 0 0 1 0 0 0
student male junior 150 mw 20000_30000 rural 1 1 0 0 0 0 0 0 0 0 0 0
student male junior 5 ne 10000_20000 urban 0 0 0 0 0 0 0 0 0 0 1 0
student female sophomore 93 mw 10000_20000 rural 0 0 1 0 1 0 0 0 0 1 0 0
student female junior 26 mw 20000_30000 rural 1 0 1 0 1 0 0 0 0 0 0 1
student male senior 65 mw 10000_20000 rural 1 0 0 0 0 0 0 0 0 0 0 1
student male sophomore 155 mw 20000_30000 rural 1 0 0 0 0 1 1 0 1 1 1 0
student female junior 160 se 20000_30000 rural 1 1 1 0 0 0 1 0 0 0 0 0
student male senior 30 mw 20000_30000 rural 1 0 0 0 1 0 0 0 0 0 0 0
student male sophomore 100 mw 10000_20000 rural 1 0 1 0 0 0 1 0 0 1 1 0
student male sophomore 60 mw 10000_20000 rural 0 0 1 1 0 0 0 0 0 0 0 1
student female sophomore 150 mw 10000_20000 rural 1 1 1 1 0 0 0 0 0 0 0 0
student female sophomore 2 mw 20000_30000 rural 0 0 1 1 0 0 0 0 0 1 0 1
student female junior 0 mw 10000_20000 rural 0 0 0 1 0 0 0 0 0 1 0 1
student male sophomore 100 mw 20000_30000 urban 1 1 1 0 1 1 1 0 0 0 0 0
student female senior 63 ne 20000_30000 rural 1 1 0 0 1 0 1 0 0 0 0 0
student male junior 90 mw 20000_30000 rural 1 1 0 0 0 0 1 1 0 1 0 0
student female junior 160 mw 20000_30000 rural 1 0 1 0 0 0 1 0 0 0 0 0
student male senior 100 mw 10000_20000 rural 1 1 0 1 0 1 0 0 0 0 0 1
student female senior 143 mw 20000_30000 rural 0 0 0 0 0 1 1 0 0 0 0 0
student female sophomore 85 mw 20000_30000 rural 1 0 0 0 0 0 0 0 0 0 0 1
student female senior 50 ne 20000_30000 urban 1 0 1 1 0 0 0 0 0 0 0 0
student female graduate 15 mw 10000_20000 rural 1 1 1 1 1 1 1 0 0 1 0 0
student female senior 1490 so 20000_30000 rural 0 0 0 0 1 0 0 0 0 0 0 0
student male sophomore 75 mw 20000_30000 rural 1 1 0 0 1 0 1 0 0 1 1 0

In: Statistics and Probability

Lon Timur is an accounting major at a midwestern state university located approximately 60 miles from...

Lon Timur is an accounting major at a midwestern state university located approximately 60 miles from a major city. Many of the students attending the university are from the metropolitan area and visit their homes regularly on the weekends. Lon, an entrepreneur at heart, realizes that few good commuting alternatives are available for students doing weekend travel. He believes that a weekend commuting service could be organized and run profitably from several suburban and downtown shopping mall locations. Lon has gathered the following investment information.

1. Five used vans would cost a total of $75,000 to purchase and would have a 3-year useful life with negligible salvage value. Lon plans to use straight-line depreciation.
2. Ten drivers would have to be employed at a total payroll expense of $47,990.
3. Other annual out-of-pocket expenses associated with running the commuter service would include Gasoline $15,990, Maintenance $3,300, Repairs $4,010, Insurance $4,200, and Advertising $2,500.
4. Lon has visited several financial institutions to discuss funding. The best interest rate he has been able to negotiate is 15%. Use this rate for cost of capital.
5. Lon expects each van to make ten round trips weekly and carry an average of six students each trip. The service is expected to operate 30 weeks each year, and each student will be charged $12.05 for a round-trip ticket.


Click here to view PV table.

(a)

Determine the annual (1) net income and (2) net annual cash flows for the commuter service. (Round answers to 0 decimal places, e.g. 125.)

Net income $
Net annual cash flows $


(b)

Compute (1) the cash payback period and (2) the annual rate of return. (Round answers to 2 decimal places, e.g. 10.50.)

Cash payback period years
Annual rate of return %


(c)

Compute the net present value of the commuter service. (Round answer to 0 decimal places, e.g. 125. If the net present value is negative, use either a negative sign preceding the number eg -45 or parentheses eg (45). For calculation purposes, use 5 decimal places as displayed in the factor table provided.)

Net present value

In: Accounting

Jeremy is a 25-year-old man training for an ultramarathon race of 50 miles. He is 5...

Jeremy is a 25-year-old man training for an ultramarathon race of 50 miles. He is 5 feet, 10 inches tall and currently weighs 170 lb. During his long runs of more than 3 hours, he drinks water, approximately 30 oz., and consumes one GU (an energy supplement containing 100 kcal from simple sugar) at the 2-hour mark. Jeremy is coming to you for advice because he is becoming increasingly weak and nauseated toward the end of his runs. He reports feeling light-headed and irritable on his long training days. Jeremy states that he is eating an egg salad sandwich with two hard-boiled eggs mixed with 3 tbsp. of mayonnaise on whole wheat bread about 20 minutes before his run.

Questions for Analysis

  1. What sources of fuel is Jeremy predominately using in this type of exercise?
  2. How much fluid should Jeremy be consuming during a 3-hour run?
  3. Based on his weight, how many calories and grams of carbohydrate should he consume during his run?
  4. On what time schedule would you recommend he consume his fluid and carbohydrate?
  5. What would you recommend regarding his pre-exercise meal?

In: Nursing

You are the manager of a new primary care clinic located about twenty five (25) miles...

You are the manager of a new primary care clinic located about twenty five (25) miles outside of a small city (population of 50,000). With five (5) family physicians, two (2) nurse practitioners, two (2) physicians’ assistants (PAs), and twenty (20) clinical support staff consisting of RNs, LPNs, and CMAs, the clinic provides primary care services to a diverse community of people living and working outside the city limits. Originally a rural area, the community has been growing and now includes promising opportunities in employment, education, and comfortable living spaces for young families. However, there are still many residents who struggle to make ends meet with older farms that have belonged to families for generations.   

The central city includes two (2) large acute care facilities, and one (1) tertiary care facility that is known for its excellent pulmonary care. Both acute care hospitals provide the usual services such as labor and delivery, outpatient surgery, chronic diseases care, etc. and have fully equipped ancillary departments, such as lab and radiology. Up until this point, the residents have used the facilities’ emergency departments for routine illnesses and conditions when their private physicians were not readily available.

Write a five to seven (5-7) page paper in which you:

Analyze some of the key social, political, and economic factors that have led to the proliferation of urgent care facilities and primary care practices over the last 20-30 years.

Create a comprehensive mission statement for the clinic, and discuss how it will facilitate the provision of quality services.

Analyze and discuss one (1) or more directions the clinic might take to grow its business. Determine what factors you would consider when deciding what services to provide in-house and which ones to affiliate with other institutions.

Decide how you will determine if the clinic is meeting its goals. Identify three (3) performance measurements you could use to evaluate the success of the clinic’s services. Begin by naming a goal, and then identify a quantifiable measurement you could use for each to determine if you are coming close or falling short of the goal.

Determine how you would then address whatever opportunities for improvement seem to exist and what processes you would put in place.

Use at least three (3) quality resources in this assignment. Note: Wikipedia and similar Websites do not qualify as quality resources.

Format your assignment according to the following formatting requirements:

Typed, double spaced, using Times New Roman font (size 12), with one-inch margins on all sides.

In: Nursing