ETHICAL RESPONSIBILITY ON MOUNT EVEREST
Many mountain climbers dream of scaling the highest mountain on Earth. It is a dangerous venture and some of them die in pursuit of this dream every year, including a 33-year-old Canadian woman in May 2012. The following describes one situation involving the ethics and responsibilities of climbers toward one another.

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In May 2006, several climbing parties passed by David Sharp, 34, who was near death at 28,000 feet on Mount Everest. He later died alone, without companionship in his final hours. He was one of 11 who perished during the 2006 climbing season and one of more than 200 who have died attempting to climb the mountain.

One climber to leave Sharp was Mark Inglis, 47, a New Zealander who was climbing the mountain on artificial legs. He and his party stopped to consider Sharp’s situation. He was in poor condition and near death, but was given oxygen. Rescue was not feasible as helicopters cannot operate at that altitude. The lives of Inglis’s party would likely have been endangered trying to move Sharp to a base camp.

It was disclosed that Sharp’s group was loosely organized without a leader. The members of the group appeared to be functioning independently according to an expedition outfitter. The outfitter said that Sharp’s group did not have sufficient oxygen and climbed without a Sherpa guide.

Discussion of the incident was extensive. One position presented was that climbers do not endanger themselves to save another. Furthermore, looking after another climber may jeopardize one’s own chance at climbing the mountain. Sir Edmund Hillary, who, with his Sherpa Tenzing Norgay, became the first to reach the summit of Mount Everest, said that human life is more important than conquering mountains. Others suggested that the incident was an example of a lack of sense of responsibility and caring for one another.

Questions
What ethical principles are involved in this situation?

Why blame Inglis?

Who is responsible?

Should the climbing of Mount Everest be regulated?

may i have the answers with relevant explanations please

Internal controls can be categorized using the following framework:

Following is a list of controls implemented by Waterfront, Inc.:

Identify the assertion or assertions to which each procedure pertains: (Existence/Occurrence, Completeness, Valuation/Allocation, Rights/Obligations, Presentation/Disclosure).

1. Each value in the data set is called a ? .

1. Variables whose values are determined by chance are called ? .

1. A Blank 1 consists of all subjects (human or otherwise) that are being studied.

1. A Blank 1 is a circle that is divided into sections or wedges according to the percentage of frequencies in each category of the distribution.

1. Tell whether Descriptive or Inferential Statistics has been used. In the upcoming election, it is predicted that candidate Murphy will get 52% of the votes and candidate Patterson will receive 46% of the votes.

   	1.	Descriptive
   	2.	Inferential

1. Tell whether Descriptive or Inferential Statistics has been used. Results of the election last week showed that candidate Patterson received 53% of the votes and candidate Murphy received 44% of the votes.

   	1.	Descriptive
   	2.	Inferential

1. Classify as nominal-level, ordinal-level, interval-level, or ratio-level data. Salaries of employees of the United Nations.

   	1.	Nominal
   	2.	Ordinal
   	3.	Interval
   	4.	Ratio

1. Classify as nominal-level, ordinal-level, interval-level, or ratio-level data. Temperatures of automobile engines.

   	1.	Nominal
   	2.	Ordinal
   	3.	Interval
   	4.	Ratio

1. Classify each variable as discrete or continuous. Capacity of water in automobile engines.

   	1.	Discrete
   	2.	Continuous

1. Classify each variable as discrete or continuous. Temperatures of airplane interiors at a given airport.

   	1.	Discrete
   	2.	Continuous

1. Classify each variable as qualitative or quantitative. Classification of a speaker as Excellent, Good, Fair, Poor, Very Poor.

   	1.	Qualitative
   	2.	Quantitative

1. Classify each variable as qualitative or quantitative. Number of cups of coffee sold by McDonald's in a day.

   	1.	Qualitative
   	2.	Quantitative

1. Identify which sampling technique was used to select the given sample. On a large University campus, students attending classes in 3 buildings on a Tuesday during the hours of 10am and 5PM were selected to complete a survey.

   	1.	Random
   	2.	Systematic
   	3.	Stratified
   	4.	Cluster

1. Identify which sampling technique was used to select the given sample. On a large college campus, faculty were selected using random numbers to determine annual salaries.

   	1.	Random
   	2.	Systematic
   	3.	Stratified
   	4.	Cluster

A study by Lefèvre et al. (2010, PLoSONE 5: e9546) investigated whether alcohol consumption affected peoples' attractiveness to the mosquito, Anopheles gambiae, which is the primary vector for malaria in Africa. A total of 43 human participants were tested, and the attractiveness of each participant was tested twice. The first test collected a baseline attractiveness for each participant. The participants then drank either a liter of beer (n=25 participants) or a liter of water (n=18), and after 15 minutes, the test was repeated. The type of drink was randomly determined for each subject.

To estimate a person's attractiveness to A. gambiae, a vial of 50 mosquitos was released into the Y-tube apparatus shown in Figure 1. Participants were seated in a small tent, which was connected by an air hose to one of two mosquito traps. This allowed the mosquitos to detect and respond to olfactory cues from the participants, without exposing the participants to the mosquitos. The proportion of mosquitos that flew toward the participant was recorded as the response variable.

You can find the Lefèvre data on the website in the file lefevre_2010_mosquitos_and_beer.csv. Each row in in the data represents a single participant. The first column is an id code. The second column is a factor that indicates the subject’s treatment-level for drink (beer vs. water). The third column gives the proportion of mosquitos that flew in the participants' direction in the baseline measurement, and the fourth column gives the proportion after drinking. Column five is the change from baseline after drinking (i.e., afterDrink – beforeDrink).

I

In the following questions, we will use two different strategies to analyze the data. In Question 2, we will conduct two completely separate tests that compare attractiveness before drinking a beverage to attractiveness after drinking a beverage, and then compare the result that we get with water to the result with beer (if it helps, imagine two different research groups test the same question, but one uses water and one uses beer; afterward, they meet up and compare notes). In the second strategy (Question 4), we will directly analyze the difference in average change from baseline for beer versus water. One of these strategies is a much better approach to use in real life. Which one is better, and why?

Exercise and the Brain

It is well established that exercise is beneficial for our bodies. Recent studies appear to indicate that exercise can also do wonders for our brains, or, at least, the brains of mice. In a randomized experiment, one group of mice was given access to a running wheel while a second group of mice was kept sedentary. According to an article describing the study, "The brains of mice and rats that were allowed to run on wheels pulsed with vigorous, newly born neurons, and those animals then breezed through mazes and other tests of rodent IQ"¹ compared to the sedentary mice. Studies are examining the reasons for these beneficial effects of exercise on rodent (and perhaps human) intelligence. High levels of BMP (bone-morphogenetic protein) in the brain seem to make stem cells less active, which makes the brain slower and less nimble. Exercise seems to reduce the level of BMP in the brain. Additionally, exercise increases a brain protein called noggin, which improves the brain’s ability. Indeed, large doses of noggin turned mice into “little mouse geniuses”, according to Dr. Kessler, one of the lead authors of the study. While research is ongoing in determining how strong the effects are, all evidence points to the fact that exercise is good for the brain. Several tests involving these studies are described. In each case, state the null and alternative hypotheses. Your answers should be an expression composed of symbols:

¹Reynolds G., "Phys Ed: Your Brain on Exercise," The New York Times, July 7, 2010.

(a) Testing to see if there is evidence that mice allowed to exercise have lower levels of BMP in the brain on average than sedentary mice.

Let group 1 be the exercising mice and let group 2 be the sedentary mice.

(b) Testing to see if there is evidence that mice allowed to exercise have higher levels of noggin in the brain on average than sedentary mice.

Let group 1 be the exercising mice and let group 2 be the sedentary mice.

(c) Testing to see if there is evidence of a negative correlation between the level of BMP and the level of noggin in the brains of mice.

Assume that X has a normal distribution, and find the indicated probability.

1. The mean is  = 85.0 and the standard deviation is s = 12.0.  Find the probability that X is greater than 101.8.
   1. 0.0808                          b.   0.9192                    c.   0.7881                     d.   0.2119
2. The mean is  = 42 and the standard deviation is s = 6.  Find the probability that X is less than 51.
   1. 0.0668                          b.   0.9901                    c.    0.9332                    d.   0.0099
3. The mean is  = 120 and the standard deviation is s = 13.2.  Find P(138  140).
   1. 0.8488                          b.   0.0226                    c.   0.1512                     d.   0.9774

Find the indicated Probability.

4. A bank’s loan office uses credit scores in their application process. The credit scores are normally distributed with a mean of 705 and a standard deviation of 55. If an applicant is randomly selected, find the probability of a rating that is between 760 and 820.

4. 1. 0.1404                          b.   0.6404                    c.   0.8596                                 d. 0.8413
5. A bank’s loan office uses credit scores in their application process. The credit scores are normally distributed with a mean of 705 and a standard deviation of 55. Applicants are offered loans if their credit scores are above 670. Find the probability that a randomly selected applicant will be offered a loan.

5. 1. 0.2611                          b.   0.3811                    c.   0.7389                     d.  0.0703
6. Scores on a test are normally distributed with a mean of 72.5 and a standard deviation of 9.1. Find , the test score which separates the bottom 80% from the top 20%. Round to the nearest tenth.

1. 51.3                             b.   64.9                         c.   80.1                        d. 93.7

7. In one region, the September energy consumption levels for single-family homes are found to be normally distributed with a mean of 990 kWh and a standard deviation of 198 kWh. For a randomly selected home, find the probability that the September energy consumption level is between 1100 kWh and 1250 kWh.

1. 0.1926                          b.   0.3828                    c.   0.6178                     d. 0.8074

8. The lengths of human pregnancies are normally distributed with a mean of 268 days and a standard deviation of 15 days. What is the probability that a pregnancy lasts less than 270 days?

1. 0.4813                          b.   0.5517                    c.   0.50            d.  0.4483

you manage an algorithmic trading operation where computers are trading in the stock market Suppose automatically without human intervention using algorithms. Suppose that your algorithm called “Shining Star” (SS) makes an average profit of $6000 each trading hour in the stock market. However, your gut instinct is that the algorithm’s performance has decreased recently. We have provided a random sample of 75 of the more recent hours of trading performance.

Hourly Profit

$ (1,622.29)

$    2,916.77

$       356.03

$    3,204.53

$    3,829.72

$    1,166.44

$ (1,144.88)

$       (21.88)

$    3,563.70

$ (2,817.08)

$    1,593.21

$     (672.84)

$    2,064.04

$    2,129.55

$    4,572.09

$       146.06

$ (2,651.18)

$ (3,332.17)

$    4,434.95

$    2,231.24

$       (93.29)

$     (533.28)

$     (961.39)

$ (3,137.56)

$    1,035.10

$    6,026.95

$ (2,362.77)

$     (774.82)

$ (2,479.09)

$    1,123.78

$     (664.86)

$    4,432.62

$    2,451.76

$    4,621.02

$     (862.48)

$    1,334.23

$    4,927.53

$       483.45

$       312.57

$    6,140.44

$    3,231.92

$       716.18

$    1,673.86

$    3,421.32

$    3,338.60

$ (2,571.67)

$ (2,493.93)

$       639.48

$       540.53

$ (1,960.74)

$ (1,223.31)

$    4,068.08

$    5,288.04

$     (358.20)

$    2,121.62

$       552.09

$    2,735.47

$    1,287.17

$    2,086.94

$     (593.27)

$    5,812.52

$    4,292.32

$ (3,891.48)

$    3,250.49

$    1,532.81

$    3,014.27

$    4,116.66

$       515.98

$ (1,520.46)

$       680.54

$    1,031.76

$    2,116.75

$ (1,983.71)

$       318.83

$    3,205.22

PARTS

Write down a hypothesis test for checking if the performance has decreased. Suppose your significance level is 0.01 .

a) Write down the test statistic.

b) What is the name of the model/distribution that would be appropriate to use for the probability distribution of the test statistic? Also, please state your assumptions for picking that distribution.



c) Please provide as much information as you can about the relevant parameters for the distribution (e.g., mean and standard deviation) under the status quo or null.

a) What is your p-value for this test?

b) What is the critical threshold for your test statistic?

b) Has the performance of your SS algorithm decreased? Why or why not?

[
a) Now write down a hypothesis test for checking if the performance has increased. Suppose your significance level is 0.01 .

b) What is your p-value for this test?

c) Has the performance of your SS algorithm increased? Why or why not?

The long-term care center has 225 beds and provides the highest level of patient care, according to on- going Department of Health Services annual surveys. The Director of the long-term center has the overall responsibility of ensuring the continuing high level of quality outcomes while also concurrently keeping the facility as risk free as practical. You and the Director have just returned from an annual Long-Term Care Association symposium where you were both introduced to some new groundbreaking initiatives regarding the differences between risk management and quality improvement.

Earlier in the week, the Director called for a meeting of the center’s department managers, including the Quality Assurance Nurse and the Manager of Risk Management. After briefing them on the symposium talking points, your Director asks you to come up with a working plan and strategy for how the facili-
ty will use both of the concepts you have introduced to arrive at a more centralized and standardized approach. Overall, the desired outcomes focus on adopting a new approach to higher quality with fewer risk factors for the organization.

Later that week, the Manager of Risk Management, the Manager of Nursing Quality Assurance, and a representative from Human Resources met to formulate a new plan to reduce the litigation exposure while concurrently increasing the quality of patient outcomes. They set about the complex set of tasks with the expectation that you, as the Director’s designated facilitator, will be closely reviewing their final recommendations.

Provide a 250-word executive summary of the research project and recommended plan of action that you will provide to the Director.

Address the following:

Questions:

What is the necessary background information needed to complete your executive summary?Who

are the stakeholders?

How do the facility’s current Continuous Quality Improvement (CQI) outcomes correspond with the current litigation prevention systems?

What factors within the nursing units are the most critical to consider when examining higher quality outcomes?

What factors within the nursing units are the most critical to consider when examining lower litigation adverse actions and operational impact?

What future steps must be taken to accomplish this directive?

5. Doogie lives for four periods. He has just completed the first period of his life (by getting his

high school diploma). Doogie is trying to decide on his future career path. He’s very good at

opening things up and fixing them, so he has narrowed his options to two possible paths. He will

either become an auto mechanic or a brain surgeon.

•If Doogie becomes an auto mechanic, he will earn $25,000 as an apprentice in

period 2, $50,000 as a solo mechanic in period 3, and $75,000 as a master

mechanic (with apprentice) in

period 4.

•If Doogie becomes a brain surgeon, he will pay $50,000 to attend college in

period 2, another $75,000 to attend medical school in period 3, and will earn

$300,000 in period 4.

Doogie must make all tuition payments at the beginning of each period, he is paid at the end of

every period, and he can borrow and lend at a rate of 8% per period.

a. What is the present discounted value (PDV) of Doogie’s possible career paths? If Doogie wants to maximize the PDV of his lifetime earnings, which career should he choose?

b. Would Doogie’s choice change if he was making his decision at birth? Would the PDV (present discounted value) of his earnings streams be different at birth? Would Doogie’s evaluation of this investment change if he started life with a trust fund of $1 million? Explain. (Assume that Doogie’s high school education in period 1 is necessary for both career paths and is costless.)

c. How would your answer change if Doogie could work for an additional 10 periods after period 4? How would your answer change if the discount rate decreased? (Answer intuitively in terms of whether the surgery track becomes relatively more or less attractive).

d. The actual lifetime earnings of brain surgeons are much higher than those of auto mechanics, yet we observe that the number of auto mechanics is much greater than the number of brain surgeons. How can the human capital model explain these patterns?