The home run percentage is the number of home runs per 100 times at bat. A random sample of 43 professional baseball players gave the following data for home run percentages. 1.6 2.4 1.2 6.6 2.3 0.0 1.8 2.5 6.5 1.8 2.7 2.0 1.9 1.3 2.7 1.7 1.3 2.1 2.8 1.4 3.8 2.1 3.4 1.3 1.5 2.9 2.6 0.0 4.1 2.9 1.9 2.4 0.0 1.8 3.1 3.8 3.2 1.6 4.2 0.0 1.2 1.8 2.4 (a) Use a calculator with mean and standard deviation keys to find x and s. (Round your answers to two decimal places.) x = % s = % (b) Compute a 90% confidence interval for the population mean μ of home run percentages for all professional baseball players. Hint: If you use the Student's t distribution table, be sure to use the closest d.f. that is smaller. (Round your answers to two decimal places.) lower limit % upper limit % (c) Compute a 99% confidence interval for the population mean μ of home run percentages for all professional baseball players. (Round your answers to two decimal places.) lower limit % upper limit % (d) The home run percentages for three professional players are below. Player A, 2.5 Player B, 2.0 Player C, 3.8 Examine your confidence intervals and describe how the home run percentages for these players compare to the population average. We can say Player A falls close to the average, Player B is above average, and Player C is below average. We can say Player A falls close to the average, Player B is below average, and Player C is above average. We can say Player A and Player B fall close to the average, while Player C is above average. We can say Player A and Player B fall close to the average, while Player C is below average. (e) In previous problems, we assumed the x distribution was normal or approximately normal. Do we need to make such an assumption in this problem? Why or why not? Hint: Use the central limit theorem. Yes. According to the central limit theorem, when n ≥ 30, the x distribution is approximately normal. Yes. According to the central limit theorem, when n ≤ 30, the x distribution is approximately normal. No. According to the central limit theorem, when n ≥ 30, the x distribution is approximately normal. No. According to the central limit theorem, when n ≤ 30, the x distribution is approximately normal.

The home run percentage is the number of home runs per 100 times at bat. A random sample of 43 professional baseball players gave the following data for home run percentages.

(a) Use a calculator with mean and standard deviation keys to find x and s. (Round your answers to two decimal places.)

(b) Compute a 90% confidence interval for the population mean μ of home run percentages for all professional baseball players. Hint: If you use the Student's t distribution table, be sure to use the closest d.f. that is smaller. (Round your answers to two decimal places.)

(c) Compute a 99% confidence interval for the population mean μ of home run percentages for all professional baseball players. (Round your answers to two decimal places.)

(d) The home run percentages for three professional players are below.

Examine your confidence intervals and describe how the home run percentages for these players compare to the population average.

A.) We can say Player A falls close to the average, Player B is above average, and Player C is below average.

B.) We can say Player A falls close to the average, Player B is below average, and Player C is above average.    

C.) We can say Player A and Player B fall close to the average, while Player C is above average.

D.) We can say Player A and Player B fall close to the average, while Player C is below average.

(e) In previous problems, we assumed the x distribution was normal or approximately normal. Do we need to make such an assumption in this problem? Why or why not? Hint: Use the central limit theorem.

A.) Yes. According to the central limit theorem, when n ≥ 30, the x distribution is approximately normal.

B.) Yes. According to the central limit theorem, when n ≤ 30, the x distribution is approximately normal.    

C.) No. According to the central limit theorem, when n ≥ 30, the x distribution is approximately normal.

D.) No. According to the central limit theorem, when n ≤ 30, the x distribution is approximately normal.

A subway has good service 70% of the time and runs less frequently 30% of the time because of signal problems. When there are signal problems, the amount of time in minutes that you have to wait at the platform is described by the pdf probability density function with signal problems = pT|SP(t) = .1e^(−.1t). But when there is good service, the amount of time you have to wait at the platform is probability density function with good service = pT|Good(t) = .3e^(−.3t) You arrive at the subway platform and you do not know if the train has signal problems or running with good service, so there is a 30% chance the train is having signal problems. (a) After 1 minute of waiting on the platform, you decide to re-calculate the probability that the train is having signal problems based on the fact that your wait will be at least 1 minute long. What is that new probability? (b) After 5 minutes of waiting, still no train. You re-calculate again. What is the new probability? (c) After 10 minutes of waiting, still no train. You re-calculate again. What is the new probability?

A runner of mass 61.0 kg runs around the edge of a horizontal turntable mounted on a vertical, frictionless axis through its center. The runner's velocity relative to the earth has magnitude 2.90 m/s . The turntable is rotating in the opposite direction with an angular velocity of magnitude 0.170 rad/s relative to the earth. The radius of the turntable is 2.60 m , and its moment of inertia about the axis of rotation is 83.0 kg⋅m^2 .

Find the final angular velocity of the system if the runner comes to rest relative to the turntable. (You can treat the runner as a particle.)

An opposing player charging the net runs into the goalie for your ice hockey team, and the goalie lays motionless on the ice. When you get to him, he is conscious and alert but complaining of not being able to move. He denies having any pain and is becoming very anxious and scared. He has no difficulty breathing. You complete your initial evaluation and find all vitals to be within normal limits, but the athlete does not respond to painful stimuli in his extremities and has no motor activity. You instruct the coach to contact the local EMS and decide to wait for the assistance of EMS personnel to stabilize the athlete on a spine board. While you are waiting, the athlete sates he is beginning to feel some stinging in his feet and can now move his fingers slightly.

Questions:
1.What condition do you think this athlete is suffering from?
2.What do you expect to see happen over the next several minutes?
3.What concerns do you have with the patient and scenario?
4.Describe your referral strategy.
5.What care would you render if the symptoms persist?
6.What would you do if, by the time the ambulance arrives, the athlete has fully recovered his sensation and motor function?

a car is traveling along a straight road when the car runs out of gas. the car has an acceleration a(t)=1.1m/s^2-.02m/s^3*t and has a velocity of 30.0m/s at t=0.

a) what is the displacement of the car between t=3.0 s and t=5.0 s?

b) at what time will the car become to rest?

c) what will be the total displacement of the car between t=0 and when it comes to rest?

Dave is a medical device distributor in Nevada and runs his business as a sole proprietor.

He therefore pays taxes on his business income as part of his individual income tax filing.

Currently his effective tax rate is 37.9% ( 35% federal income tax rate plus 2.9% Medicare tax

rate - there is no state income tax in Nevada which is why he moved there from California).

He has recently been made aware of a new technology that can be used during surgery that

more effectively controls blood loss. Deployment of this technology would require purchasing

additional equipment and employing a couple of technicians to use the equipment at local

hospitals. He is seeking your advice on whether he should adopt this technology from a

financial perspective. The initial investment in the equipment would be $900,000. The

machine would operate for eight years, after which the machine would be worthless and Dave

is expecting to retire. In each of those eight years, he expects to generate revenue of $900,000

and have an operating margin of 19% (employee expenses and materials would run 81% per

year). He would depreciate the machine for tax purposes using straight-line depreciation over

the eight years. There would also be an initial investment in working capital of $135,000

which would be fully recovered at the end of the eighth year.

If Dave makes this investment, his tax rate will be 37.9% and the required return will be 5%. What is the NPV of this project?

Dave is a medical device distributor in Nevada and runs his business as a sole proprietor.

He therefore pays taxes on his business income as part of his individual income tax filing.

Currently his effective tax rate is 43.4%

He has recently been made aware of a new technology that can be used during surgery that

more effectively controls blood loss. Deployment of this technology would require purchasing

additional equipment and employing a couple of technicians to use the equipment at local

hospitals. He is seeking your advice on whether he should adopt this technology from a

financial perspective. The initial investment in the equipment would be $900,000. The

machine would operate for eight years, after which the machine would be worthless and Dave

is expecting to retire. In each of those eight years, he expects to generate revenue of $900,000

and have an operating margin of 19% (employee expenses and materials would run 81% per

year). He would depreciate the machine for tax purposes using straight-line depreciation over

the eight years. There would also be an initial investment in working capital of $135,000

which would be fully recovered at the end of the eighth year.

If dave makes this investment his tax rate will be 43.4%, and the required return will be 5% what is the NPV?