Questions
This assessment task aims to develop your ability to apply the first three phases of the...

This assessment task aims to develop your ability to apply the first three phases of the clinical reasoning process, at an introductory level, to the patient scenario below.

You are a student nurse working with a school nurse (registered nurse) in a secondary school. You and your mentor are supervising a bubble soccer match this afternoon (26th March) which commenced at 1400 hrs. The match goes for 40 minutes with a 5-minute break in between the two halves. It is a hot and sunny day, the air temperature is 32 oC and the humidity is 45%.

https://www.youtube.com/watch?v=xQQo08CPGm8

After the match, your mentor asks you to perform a range of health assessments to make sure the students are fit to go home.

Jessie Lin is 16 years old and in Year 11.

It is now 1450 hours. You assess Jessie's vital signs and record the following results:

  • Temperature (tympanic) 38.5 oC
  • Pulse rate 140 beats/min
  • Respiratory rate (RR) 29 breaths/min
  • Blood pressure (BP) 130/70 mmHg


Jessie has flushed skin (see picture above) and her t-shirt is soaked. Her past medical history has not yet been documented in the school record as she is a new student and only enrolled in the school last week after moving from another state. She informs you that her mother is waiting for her in the car park, but she feels very hot and that her heart feels like it is beating very fast. She asks you for a bottle of cold water and a chair.


Jessie's previous observation records (on a clinical chart) are:

Date BP Pulse RR Temp
23rd March 2020 110/60 70 14 36.8
24th March 2020 112/60 74 12 36.6

What you need to do in your clinical reasoning report

  • Provide a concise summary of Jessie's situation as an introduction to your report (approximately 50 words) - what pertinent information would someone reading your report need to know about who Jessie is and the context of this scenario?
  • List the objective and subjective data (cues) that you have gathered from reviewing the information provided above (approx. 50 words)
  • Analyze and interpret the identified cues and explain the assessment findings in relation to Jessie's context (approx. 450 words)

    To do this successfully, you should:
    • categorize the cues and identify what elements are normal or abnormal, and
    • compare the current situation and vital signs with previous health information known about Jessie, and
    • recall and apply knowledge of anatomy and principles of physiology (including concepts of homeostasis and the body's responses to physical activity) to explain her vital signs and other cues.
  • Then propose what further cues you want to collect and explain why these are relevant and important to the situation (approx. 450 words)

    To do this successfully, you will need to form a logical opinion about what the further cues should be, when you would undertake the assessments to collect these cues (e.g. after some immediate actions for Jessie) and why these cues should be assessed. Relate your justification to Jessie's situation AND to the principles of anatomy and normal physiology (focusing on homeostasis).

Suggestions for structuring your clinical reasoning report

There is no set template for how you have to structure your report as long as the sequence of the information that you present flows logically and the reader can follow your clinical reasoning as it unfolds.

The following suggestions are based on answers to frequently asked questions:

  • Section headings can be a helpful signpost for how you have applied the clinical reasoning process.
    You may choose to use some of the keywords from the phases of the clinical reasoning cycle (e.g. Patient Situation, Cue Collection and Processing Information, Further Cue Collection) or any other headings are also fine.
  • You may use a table to present the objective and subjective cues that you have gathered and which elements are normal or abnormal if you wish. In this particular assignment, information included in a table will contribute to the overall word count.
  • The majority of your report will need to be sentences organised into paragraphs, not just a list of dot points. When explaining something, such as the assessment findings, you need to make the reasons for how they came to be the way they are clear to the reader. Paragraphs will allow you to make the relationships between things evident, whereas a dot point format can sometimes appear as a list of facts without the necessary connections for explaining something.
  • As you are the student nurse in the scenario, you may write your report using 'first person' tense. This would be useful in the section of your report where you propose what further cues you want to collect and when you would undertake the assessments e.g. "I would ask Jessie...". Writing in first person is not mandatory so if you are more comfortable writing objectively in the 'third person' (removing personal pronouns from your writing), then you can do so as long as it flows logically!
  • You may use accepted clinical abbreviations in your report, but be sure to introduce all abbreviations the first time that you use them e.g. blood pressure (BP), heart rate (HR), respiratory rate (RR)  

Criterion 1: Apply a beginner’s level of clinical reasoning to assess and interpret health information in relation to the patient’s context.

Criterion 2: Apply knowledge of anatomy and principles of physiology to explain assessment findings in relation to the patient’s context.

Criterion 3: Apply a beginner’s level of clinical reasoning to propose and justify further cues that are to be collected in relation to the patient’s context

Criterion 4: Communicate using academic writing conventions with references to scholarly sources of information that conform to the Harvard referencing style.

Your written report should be approximately 1000 words (+/- 10%)

In: Nursing

Instructions: In this assignment, you use linear regression to calculate the expected after exercising heart rate....

Instructions: In this assignment, you use linear regression to calculate the expected after exercising heart rate.

Steps:

1. Open the Heart Rate database and identify the X-variable (resting) and the Y-variable (after exercise).

2. Use the Scatter Plot function in the Insert Charts section of Excel to create a scatter plot of the X and Y variables

3. Add a trendline to the scatter plot (Find and View a YouTube video on how to do this if you need help)

4. Use the Data Analysis tools in Excel to perform regression analysis on the X and Y variables

In a Word document, describe the relationship between the X-variable (rest heart rate) and the Y-Variable (after exercise). Make certain you include the estimates for the intercept and the slope coefficients.

Heart Database:

Heart rate before and after exercise
M=0 F=1 Resting After Exercise
0 85.9 87.5
0 67.7 79.4
0 80.3 93.4
0 85.2 97.7
0 86.3 99.7
0 76.6 83.7
0 94.4 101.9
0 86.4 100.6
0 83.4 97.4
0 89.8 97.4
0 88.7 97.1
0 78.4 87.2
0 71.3 79.9
0 92.6 104.7
0 86.2 95.9
0 83.9 93.9
0 78.1 90.1
0 64.0 70.7
0 72.8 86.7
0 72.7 81.2
0 80.2 83.3
0 78.2 86.0
0 70.6 90.2
0 75.5 84.4
0 82.7 94.2
0 87.7 95.1
0 80.0 88.7
0 73.4 82.7
0 89.5 94.6
0 77.6 84.6
0 76.6 86.4
0 85.6 96.2
0 74.2 82.1
0 79.0 91.6
0 74.6 86.7
0 88.8 98.8
0 82.1 85.6
0 77.6 80.6
0 77.9 83.8
0 88.1 93.9
0 81.6 90.3
0 91.2 100.6
0 80.3 88.0
0 76.7 91.8
0 88.4 103.0
0 75.2 86.5
0 75.2 84.9
0 73.1 71.9
0 77.0 84.7
0 59.0 68.2
0 84.9 96.0
0 87.5 105.9
0 75.6 84.3
0 84.0 90.4
0 78.2 94.0
0 86.6 90.6
0 84.9 95.1
0 78.8 90.4
0 69.4 82.6
0 78.3 91.1
0 76.9 92.3
0 84.2 87.9
0 76.3 85.9
0 86.3 99.7
0 72.3 80.9
0 81.8 93.8
0 92.8 99.8
0 74.8 90.2
0 91.7 99.2
0 71.0 87.0
0 96.1 100.2
0 82.5 95.1
0 81.9 97.5
0 89.7 94.8
0 81.4 100.9
0 74.8 94.0
0 88.1 102.1
0 69.2 81.4
0 78.8 90.9
0 85.3 94.2
0 74.8 81.3
0 77.7 89.9
0 78.0 89.8
0 80.5 95.3
0 75.4 84.8
0 81.5 84.2
0 73.9 85.2
0 69.4 74.1
0 89.4 96.7
0 70.9 82.0
0 82.9 90.2
0 89.6 106.7
0 74.5 75.6
0 92.3 102.2
0 87.7 98.0
0 78.9 89.7
0 79.8 81.5
0 85.5 97.4
0 87.3 94.1
0 77.8 97.8
0 71.0 80.1
0 82.5 90.7
0 74.8 83.7
0 69.2 79.4
0 80.5 87.4
0 89.4 99.2
0 74.5 88.0
0 85.5 92.0
1 76.6 88.2
1 79.2 90.4
1 80.6 101.3
1 75.5 93.1
1 83.9 90.5
1 73.9 89.1
1 76.8 90.8
1 85.2 93.5
1 82.1 93.5
1 76.3 87.0
1 97.0 104.5
1 81.5 86.5
1 65.3 86.3
1 80.8 86.7
1 78.5 89.9
1 86.3 97.6
1 89.8 92.9
1 87.8 98.5
1 76.2 89.9
1 74.2 88.8
1 67.4 78.8
1 75.5 80.2
1 80.0 90.2
1 76.4 88.0
1 94.9 95.7
1 89.2 96.9
1 83.3 87.7
1 85.8 90.4
1 75.3 84.1
1 77.9 99.0
1 70.0 83.0
1 88.0 94.2
1 86.9 95.0
1 87.1 95.9
1 79.3 82.7
1 81.2 90.7
1 82.9 91.9
1 87.4 103.6
1 83.0 90.0
1 76.8 83.3
1 76.9 87.7
1 79.8 88.2
1 83.2 93.0
1 79.5 88.6
1 82.4 89.3
1 80.8 84.2
1 83.2 94.5
1 71.6 81.5
1 82.8 93.1
1 76.8 92.8
1 93.2 100.4
1 91.4 100.9
1 97.3 103.3
1 88.3 90.1
1 80.6 85.2
1 87.4 91.7
1 96.5 99.3
1 77.9 91.6
1 76.1 84.1
1 85.2 89.7
1 68.6 72.8
1 79.4 92.0
1 85.2 99.2
1 74.3 85.6
1 74.3 89.2
1 78.5 98.5
1 80.4 90.8
1 82.9 85.9
1 78.9 90.7
1 78.6 87.0
1 87.5 93.9
1 78.9 91.4
1 80.0 89.1
1 80.4 89.2
1 88.3 93.5
1 80.6 95.9
1 85.8 90.5
1 84.6 93.0
1 80.5 91.8
1 92.4 101.2
1 84.4 96.7
1 82.3 86.9
1 77.2 85.8
1 83.3 82.1
1 86.2 98.9
1 81.3 97.7
1 90.2 96.4
1 78.4 85.5
1 84.7 101.6
1 89.7 94.3
1 78.4 88.0
1 79.9 88.5

In: Statistics and Probability

Please state which function of money is being used by each of the following activities: Unit...

Please state which function of money is being used by each of the following activities: Unit of Account (Standard of Value, Medium of Exchange or Store of Value.  Please explain the reasoning behind each answer.

(a) Brenda puts $600 into her cookie jar for a rainy day.

(b) Brenda records the money she has spent on gasoline this year.   

(c) Brenda buys a $100 Savings Bond.

(d) Brenda uses $2,400 to pay her rent.

  1. (4 points)

(a) Please state what assets are part of the money measurement called M1.

(b) Please state what assets are part of the money measurement called M2

  1. (8 points) Explain what impact each of the following actions has on M1 and M2 both.

Please give the reasoning for each answer.

(a) Mary puts $400 in cash into her Savings Account.

(b) Sam transfers $40 from his Checking Account into his Savings Account.

(c) Chen takes $60 out of his Savings Account at the ATM machine.

(d) Brenda puts $50 in cash into her cookie jar at home for a rainy day.

  1. (3 points)

(a) Assume that a one year bond that has no interest coupon payment with a maturity value (face value) of $2,000 sold for $1,700. Show the interest rate that this bond will pay when it matures.

(b) If the prices of similar bonds are selling next month for $1,900, show the interest rate that these bonds pay when they mature.

(c) Based on your answers in (a) and (b) above, describe the relationship between the price of bonds and the interest rate.

  1. (10 points)

Your friend owns a cabin in the mountains in Big Bear California that he inherited from his mother. Your friend likes to visit that cabin during the year whenever he wants to. Thus, he leaves it vacant when he is not there. Your friend says that it is an inexpensive way to have short vacations: visit a place he owns.

Please explain why your friend is wrong in stating that this is an inexpensive way to have short vacations.

  1. (3 points)

(a) Please provide a description of Bank Runs.

(b) Explain the main cause of Bank Runs.

(c) Why do you think we no longer see many Bank Runs today.

  1. (10 points)

Please explain what backing U.S. Federal Reserve Notes have today and why people accept them for payment for goods and services.

  1. (Question 8 has two parts)

Part 1 of Question 8 (12 points)

Below is the Balance Sheet for the Bank of Upland as of October 1, 2017. The required reserve ratio is 5%. Using this information and the Balance Sheet below answer the following questions.

Bank of Upland

Assets

Liabilities

$50 million Home Loans

$900 million Demand Deposits

$200 million Treasury Bonds

$70 million Car Loans

$80 million Business Loans

$100 million Credit Card Loans

$360 million On Deposit at the Fed

$40 million in Vault Cash

$900 million Total Assets

$900 million Total Liabilities



(a) Calculate the Bank of Upland’s Total Reserves as of October 1, 2017 (please show/explain how you got your answer)

b) Calculate the Bank of Upland’s Required Reserves as of October 1, 2017 (please show/explain how you got your answer).

c) Calculate the Bank of Upland’s Excess Reserves as of October 1, 2017 (please show/explain how you got your answer).

d) Determine the amount of Bank of Upland’s Total Reserves which can legally be loaned out as of October 1, 2017 (please show/explain how you got your answer).

e) Calculate the Bank of Upland’s Money Creating Potential throughout the entire Banking System as of October 1, 2017 (please show/explain how you got your answer).




Part 2 of Question 8 (17 points)

Start with the same Balance Sheet and required reserve ratio found in Part 1 above, and using the fact that the Federal Reserve had just sold $120 million worth of Treasury Bonds (T-bonds) to the Bank of Upland at the end of business on October 1, 2017 (no other transaction occurred at the Bank of Upland on October 1, 2017), answer the following questions.

a) Fill in the Bank of Upland’s Balance Sheet numbers as of the start of business on October 2, 2017 for the categories found below. Start with the numbers in Part 1 above and incorporate the fact that the Federal Reserve (using Open Market Operations) had just sold $120 million worth of Treasury Bonds (T-bonds) to the Bank of Upland. Using a Word Table might help.

Bank of Upland

Home Loans

Demand Deposits

Treasury Bonds

Car Loans

Business Loans

Credit Card Loans

On Deposit at the Fed

Vault Cash

Total Assets

Total Liabilities

b) Calculate the Bank of Upland’s Total Reserves as of October 2, 2017 (please show/explain how you got your answer).

c) Calculate the Bank of Upland’s Required Reserves as of October 2, 2017 (please show/explain how you got your answer).

d) Calculate the Bank of Upland’s Excess Reserves as of October 2, 2017 (please show/explain how you got your answer).

e) Calculate the Bank of Upland’s Money Creating Potential throughout the entire Banking System as of October 2, 2017 (please show/explain how you got your answer).

f) Explain the reason the Federal Reserve would Sell these T-bonds to the Bank of Upland and explain what the Federal Reserve is worried about. (In other words, what economic condition is the Fed trying to avoid and how would the bond purchase help the Fed to avoid this economic condition.)You must use numbers that you calculated above to support your answer to receive credit.

g) Explain how the Fed would use two other monetary tools to help support its Open Market Operation above. Explain how these tools would be used and how they would have an impact on the Marcoeconomy.

In: Economics

Instructions:: In this assignment,you will calculate confidence intervals for the quantitative variables in the Heart Rate...

Instructions:: In this assignment,you will calculate confidence intervals for the quantitative variables in the Heart Rate database.

Steps:

1. Open the Heart Rate database in Excel and identify the quantitative variables

2. Make sure the data is sorted by category, e.g., male at-rest, female at-rest, etc.

3. Use the Data Analysis tools to construct 95% and 99% confidence intervals for all of the sorted quantitative variables. Please note that the statistic being used is the confidence interval of the means, which requires the use of the Standard Error of the mean (not the standard deviation of the mean)

4. Create a Word document, using your calculated Excel results, to describe the expected value and range for each of the variables. Make certain you note and explain any differences in the means of the variables, and any effect of changing the level of confidence.

Heart Rate Database

Heart rate before and after exercise
M=0 F=1 Resting After Exercise
0 85.9 87.5
0 67.7 79.4
0 80.3 93.4
0 85.2 97.7
0 86.3 99.7
0 76.6 83.7
0 94.4 101.9
0 86.4 100.6
0 83.4 97.4
0 89.8 97.4
0 88.7 97.1
0 78.4 87.2
0 71.3 79.9
0 92.6 104.7
0 86.2 95.9
0 83.9 93.9
0 78.1 90.1
0 64.0 70.7
0 72.8 86.7
0 72.7 81.2
0 80.2 83.3
0 78.2 86.0
0 70.6 90.2
0 75.5 84.4
0 82.7 94.2
0 87.7 95.1
0 80.0 88.7
0 73.4 82.7
0 89.5 94.6
0 77.6 84.6
0 76.6 86.4
0 85.6 96.2
0 74.2 82.1
0 79.0 91.6
0 74.6 86.7
0 88.8 98.8
0 82.1 85.6
0 77.6 80.6
0 77.9 83.8
0 88.1 93.9
0 81.6 90.3
0 91.2 100.6
0 80.3 88.0
0 76.7 91.8
0 88.4 103.0
0 75.2 86.5
0 75.2 84.9
0 73.1 71.9
0 77.0 84.7
0 59.0 68.2
0 84.9 96.0
0 87.5 105.9
0 75.6 84.3
0 84.0 90.4
0 78.2 94.0
0 86.6 90.6
0 84.9 95.1
0 78.8 90.4
0 69.4 82.6
0 78.3 91.1
0 76.9 92.3
0 84.2 87.9
0 76.3 85.9
0 86.3 99.7
0 72.3 80.9
0 81.8 93.8
0 92.8 99.8
0 74.8 90.2
0 91.7 99.2
0 71.0 87.0
0 96.1 100.2
0 82.5 95.1
0 81.9 97.5
0 89.7 94.8
0 81.4 100.9
0 74.8 94.0
0 88.1 102.1
0 69.2 81.4
0 78.8 90.9
0 85.3 94.2
0 74.8 81.3
0 77.7 89.9
0 78.0 89.8
0 80.5 95.3
0 75.4 84.8
0 81.5 84.2
0 73.9 85.2
0 69.4 74.1
0 89.4 96.7
0 70.9 82.0
0 82.9 90.2
0 89.6 106.7
0 74.5 75.6
0 92.3 102.2
0 87.7 98.0
0 78.9 89.7
0 79.8 81.5
0 85.5 97.4
0 87.3 94.1
0 77.8 97.8
0 71.0 80.1
0 82.5 90.7
0 74.8 83.7
0 69.2 79.4
0 80.5 87.4
0 89.4 99.2
0 74.5 88.0
0 85.5 92.0
1 76.6 88.2
1 79.2 90.4
1 80.6 101.3
1 75.5 93.1
1 83.9 90.5
1 73.9 89.1
1 76.8 90.8
1 85.2 93.5
1 82.1 93.5
1 76.3 87.0
1 97.0 104.5
1 81.5 86.5
1 65.3 86.3
1 80.8 86.7
1 78.5 89.9
1 86.3 97.6
1 89.8 92.9
1 87.8 98.5
1 76.2 89.9
1 74.2 88.8
1 67.4 78.8
1 75.5 80.2
1 80.0 90.2
1 76.4 88.0
1 94.9 95.7
1 89.2 96.9
1 83.3 87.7
1 85.8 90.4
1 75.3 84.1
1 77.9 99.0
1 70.0 83.0
1 88.0 94.2
1 86.9 95.0
1 87.1 95.9
1 79.3 82.7
1 81.2 90.7
1 82.9 91.9
1 87.4 103.6
1 83.0 90.0
1 76.8 83.3
1 76.9 87.7
1 79.8 88.2
1 83.2 93.0
1 79.5 88.6
1 82.4 89.3
1 80.8 84.2
1 83.2 94.5
1 71.6 81.5
1 82.8 93.1
1 76.8 92.8
1 93.2 100.4
1 91.4 100.9
1 97.3 103.3
1 88.3 90.1
1 80.6 85.2
1 87.4 91.7
1 96.5 99.3
1 77.9 91.6
1 76.1 84.1
1 85.2 89.7
1 68.6 72.8
1 79.4 92.0
1 85.2 99.2
1 74.3 85.6
1 74.3 89.2
1 78.5 98.5
1 80.4 90.8
1 82.9 85.9
1 78.9 90.7
1 78.6 87.0
1 87.5 93.9
1 78.9 91.4
1 80.0 89.1
1 80.4 89.2
1 88.3 93.5
1 80.6 95.9
1 85.8 90.5
1 84.6 93.0
1 80.5 91.8
1 92.4 101.2
1 84.4 96.7
1 82.3 86.9
1 77.2 85.8
1 83.3 82.1
1 86.2 98.9
1 81.3 97.7
1 90.2 96.4
1 78.4 85.5
1 84.7 101.6
1 89.7 94.3
1 78.4 88.0
1 79.9

88.5

In: Statistics and Probability

When the Law of Supply and Demand Isn’t Fair By Richard Thaler For an economist, one...

When the Law of Supply and Demand Isn’t Fair

By Richard Thaler

For an economist, one of the most jarring sights during the early weeks of the coronavirus crisis in the United States was the spectacle of bare shelves in sections of the supermarket.

There was no toilet paper or hand sanitizer. Pasta, flour and even yeast could be hard to find in the early weeks of social distancing, as many people decided to take up baking. Of far greater concern, hospitals could not buy enough of the masks, gowns and ventilators required to safely treat Covid-19 patients.

What happened to the laws of supply and demand? Why didn’t prices rise enough to clear the market, as economic models predict?

A paper that I wrote with my friends Daniel Kahneman, a psychologist, and Jack Knetsch, an economist, explored this problem. We found that the answer may be summed up with a single word, one you won’t find in the standard supply-and-demand models: fairness. Basically, it just isn’t socially acceptable to raise prices in an emergency.

We asked people questions about the actions of hypothetical firms. For example: “A hardware store has been selling snow shovels for $15. The morning after a blizzard the store raises the price of snow shovels to $20.”

Fully 82 percent of our respondents judged this to be unfair. The respondents were Canadians, known for their politeness, but the general findings have now been replicated and confirmed in studies around the world.

Most companies implicitly understand that abiding by the social norms of fairness should be part of their business model. In the current crisis, large retail chains have responded to the shortages of toilet paper not by raising the price but by limiting the amount each customer can buy. And Amazon and eBay prohibited what was viewed as price gouging on their sites.

We have seen similar behavior after hurricanes. As soon as a storm ends, there is typically enormous demand for goods like bottled water and plywood. Big retailers like Home Depot and Walmart anticipate this, sending trucks loaded with supplies to regions just outside the danger zone, ready to be deployed. Then, when it is safe, the stores provide water for free and sell the plywood at the list price or lower.

At the same time, some “entrepreneurs” are likely to behave differently. They see a disaster as an opportunity and so will fill up trucks with plywood near their homes, drive to the storm site and sell their goods for whatever price they can get.

It is not that large retailers are intrinsically more ethical than the entrepreneurs; it is simply that they have different time horizons. The large companies are playing a long game, and by behaving “fairly” they are hoping to retain customer loyalty after the emergency. The entrepreneurs are just interested in a quick buck.

Fairness norms help explain the breakdown of supply chains of medical equipment in the coronavirus crisis. Hospitals normally use buying associations that make long-term deals with wholesalers to provide essential supplies. The wholesalers generally want to preserve these relationships and realize that now would not be a good time to raise prices. Often, they are contractually obligated to supply items at prices negotiated before a spike in demand.

One current example is the N95 face mask. At the onset of the pandemic, hospitals had long-term contracts to buy them for about 35 cents each, an executive at a New York hospital told me. When the need for the masks surged, these suppliers were not allowed to raise the price, even if inclined to do so.

But others along the supply chain could make big profits by diverting masks to anyone willing to pay top dollar. That left hospitals in a bind. As the coronavirus spread in New York, the executive’s hospital searched frantically for masks, eventually paying an overseas supplier $6 each, for hundreds of thousands of them, when the regular stock was desperately short.

When anyone tries to reap big profits in an emergency like this, it can look ugly. Consider the case of two brothers who began buying hand sanitizer, masks and other scarce commodities on March 1, the day of the first announcement of a Covid-19 death in the United States. After they sold some of their merchandise at big markups on Amazon and eBay, these outlets cut them off. Eventually, after considerable adverse publicity, the brothers decided to donate their supplies.

Notice that the brothers were making markets more “efficient,” by buying low and selling high. If instead of arbitraging coronavirus supplies they had sold shares of airline and hotel companies and bought shares of Netflix and Zoom, they would simply have been considered smart traders. But while smart trading may be fine for investments, it is not considered fair when it involves essential goods during a pandemic.

One can argue that this social norm is harmful in that it prevents markets from doing their magic. For example, Tyler Cowen, the George Mason University economist, has said he wishes it were OK to raise prices for coronavirus essentials.

“Higher prices discourage panic buying and increase the chance that the people who truly need particular goods and services have a greater chance of getting them,” he wrote.

But which people “truly need” N95 masks? What is the right allocation of masks among well-endowed research hospitals, poorly funded municipal facilities, nursing homes and food processing plants? Supply and demand would tell us that the masks should simply go to the buyer who was willing and able to pay the most for them. But fairness tells us this can’t be the only consideration.

As a practical matter for businesses, big and small, that want to keep operating for the long haul, it makes good sense to obey the law of fairness. If the next shortage is meat and a store owner realizes that there is only one package of pork chops left, it would be unwise sell it at auction to the highest bidder.

Richard H. Thaler is a professor of economics and behavioral science at the Booth School of Business at the University of Chicago. Follow him on Twitter: @R_Thaler

Economic Concepts:

scarcity implies competition

ethics

allocation mechanisms

trade-offs

COMMENT

In: Economics

Write the following java program: Desc Output the name and time of the runner who came...

Write the following java program:
Desc Output the name and time of the runner who came in first, as well as the name and time of
the runner who came in last in a marathon race (assuming there are no ties).
Input A text file named marathon.txt containing the name and time of each participant in the
following format (the file has at least 1 participant, name is just 1 word with no space, and name
and time are separated by tabs, blanks, and newlines):
John 2:40
Paul 3:20
Carl 2:10
Output The name and time of the runner who came in first, as well as the name and time of the
runner who came in last printed to the screen.

You must define a class called Runner. Here is the API of Runner:
A Runner object stores the name of a runner (String) and his raceTime (Time24).
Methods:
a. Usage: Runner()
Post: The Runner object initialized with name="unknown" and raceTime=0:0.
b. Usage: Runner (String s, Time24 t)
Post: The Runner object initialized with name=s and raceTime=t.
c. Usage: String getName()
Return: The name of the Runner object
d. Usage: Time24 getRaceTime()
Return: The raceTime of the Runner object.
e. Usage: void setName(String s)
Post: The Runner object's name set to s
f. Usage: void setRaceTime(Time24 t)
Post: The Runner object's raceTime set to t
g. Usage: void read(Scanner f)
Pre: f has a line in the following format ready to be read:

name hh:mm
where name is a String and hh, mm are integers. The token delimiters of f have
been set to white space characters and the colon by the caller.
Post: The line read in from f, the name and the time stored in the Runner object
h. Usage: int compareTo(Runner r)
Desc: Compare 2 Runner objects based on raceTime
Return: 1 if current object's raceTime > r's raceTime
0 if current object's raceTime == r's raceTime
-1 if current object's raceTime < r's raceTime

i. Usage: String toString()
Return: A String object in the form "name hh:mm"

Note:
 It is not necessary to save all the runners in an array or a vector (you only need to find the minimum
time and the maximum time).
Hand in:
 Marathon.java with 2 classes: Runner, and Marathon (use class Time24).

//Time24.java

import java.util.StringTokenizer;

import java.text.DecimalFormat;

/**

A data structure that stores integer values for hour (0..23) and minute (0..59) to represent the time of day in a 24-hour clock

*/

public class Time24

{

private int hour;

private int minute;

//Post: Sets the hour value in the range 0 to 23 and the minute value in the range 0 to 59

    private void normalizeTime()

    {

       int extraHours = minute / 60;

       minute %= 60;

       hour = (hour + extraHours) % 24;

    }

/**

Desc:Initializes this Time24 object

Post:hour and minute of this Time24 object both initialized to 0

*/

public Time24()

     {

         this(0,0); //calls the 2-argument constructor of class Time24

     }

/**

Desc:Initializes this Time24 object

Pre:h and m cannot be negative

Post:hour and minute of this Time24 object initialized to h and m

respectively. This operation will normalize the time if necessary (e.g.

9:75 is stored as 10:15).

Throw:IllegalArgumentException if h or m is negative

*/

public Time24(int h, int m)

    {

       setTime(h, m);

   }

/**

Desc:Sets the hour and minute of this Time24 object to a particular time

Pre:h and m cannot be negative

Post:hour and minute of this Time24 object set to h and m

respectively. This operation will normalize the time if necessary (e.g.

9:75 is stored as 10:15).

Throw:IllegalArgumentException if h or m is negative

*/

public void setTime(int h, int m)

    {

if (h < 0 || m < 0)

          throw new IllegalArgumentException("Time24.setTime: argument"

+ " must not be negative");

       this.hour = h;

      this.minute = m;

normalizeTime();

    }

/**

Desc:Adds minutes to this Time24 object

Pre:m cannot be negative

Post:This Time24 object set to m minutes later. This operation will

normalize the time if necessary (e.g. 9:75 is stored as 10:15).

Throw:IllegalArgumentException if m is negative

*/

public void addTime(int m)

    {

       if (m < 0)

          throw new IllegalArgumentException("Time24.addTime: argument"

+ " must not be negative");

       minute += m;

       normalizeTime();

    }

/**

Desc:Measures the interval from this Time24 object to another time

Return:The interval from this Time24 object to t as a Time24

*/

public Time24 interval(Time24 t)

    {

int currTime = hour * 60 + minute;

       int tTime = t.hour * 60 + t.minute;

if (tTime < currTime) tTime += 24 * 60;

return new Time24(0, tTime-currTime);

    }

/**

Desc:Gets the hour value of this Time24 object

Return:The hour value of this Time24 object

*/

public int getHour()

    {

return hour;

}

/**

Desc:Gets the minute value of this Time24 object

Return:The minute value of this Time24 object

*/

public int getMinute()

    {

return minute;

}

/**

Desc:Converts this Time24 object to a string

Return:This Time24 object as a String in the form "hh:mm"

*/

public String toString()

    {

DecimalFormat f = new DecimalFormat("00");

return hour + ":" + f.format(minute);

    }

/**

Desc:Convert a String to a Time24

Pre:s must be in the form "hh:mm" where hh and mm are positive integers

Return:A Time24 object that corresponds to s

*/

public static Time24 parseTime(String s)

    {

StringTokenizer t = new StringTokenizer(s, ":");

int h = Integer.parseInt(t.nextToken());

int m = Integer.parseInt(t.nextToken());

return new Time24(h, m);

}

}


Hint:
class Runner
{
private String name;
private Time24 raceTime;
public Runner()
{
name="unknown";
raceTime=new Time24(0,0);

}
public Runner(String s, Time24 t)
{
name=s;

raceTime=new Time24(t.getHour(), t.getMinute());

}
public String getName()
{

return name;
}
public Time24 getRaceTime()
{

return new Time24(raceTime.getHour(), raceTime.getMinute());
}



}
class Marathon
{
public static void main(String[] args) throws FileNotFoundException
{


.
}
}

In: Computer Science

INTD 5064/OCCT 5023 - Applied Statistics for Health Care Practitioners Magnets and Pain Relief Data Set...

INTD 5064/OCCT 5023 - Applied Statistics for Health Care Practitioners
Magnets and Pain Relief Data Set
Magnet Treatment Group Placebo Group
Subject Before After Subject Before After
AM 10 10 LL 8 4
AA 10 4 LM 10 7
BC 8 7 MD 10 5
BR 10 0 MN 10 8
CM 10 4 JJ 9 8
FW 10 2 JA 10 6
GM 10 5 CR 9 8
GD 10 5 WT 10 10
HB 9 3 GJ 10 10
MG 10 10 BD 7 6
PD 9 2 EG 10 10
RW 10 2 RB 8 8
SF 10 3 DO 10 10
TS 10 4 DS 10 10
WA 10 10 NP 10 10
SH 8 4 GE 10 10
WK 10 3 DY 9 9
MR 10 0 KU 10 9
MS 8 2 UT 10 10
AR 8 7 AX 10 10
TN

INTD 5064 – Applied Statistics for Health Care Practitioners

t-test Homework

For the items below, download the data set Magnets and Pain Relief Data Set. These data are a subset of data in a study by Vallbona, C., et al. Response of pain to static magnetic fields in postpolio patients: A double blind pilot study. Archives of Physical Medicine and Rehabilitation, (78), 1200-1203.

In the original study, the researchers sought to answer the question “Can chronic pain experienced by postpolio patients be relieved by magnetic fields applied directly over an identified pain trigger point?” Subjects in the Treatment Group had a magnetic device applied to the site of pain for 45 minutes. Subjects in the Placebo Group had a non-magnetic device applied for 45 minutes. All subjects reported their pain before and after the experiment using a 0 to 10 scale (0 was the least pain, and 10 was the greatest pain). The data consist of self-report pain scores recorded before and after the experiment.

This homework includes three opportunities to calculate obtained t values: 3.c., 5.e., and 7.b. Two of these items (3.c. and 5.e.) are highlighted. Choose one of the highlighted items to complete (3.c. OR 5.e.). All non-highlighted items are required (including 7.b.).

What is/are the dependent variable(s) in the study? the independent variable(s)? Include the scales of measurement.

Calculate appropriate measures of central tendency and variability for each variable you will need in this assignment, i.e., “before” and/or “after” pain scores for each group. Justify your choices.

You may use Excel to calculate measures of central tendency and variability. A link has been provided for support in doing so. However, you may calculate those by hand or with a scientific calculator as well.

The researchers anticipated that Magnet Treatment Group pain scores would be lower than Placebo Group pain scores at the end of the study. Write the null hypothesis, in prose and notation. (Pay close attention to the word “lower” in this exercise. Remember that lower scores indicate less pain and, thus, effectiveness of the magnets. What does this suggest for how the hypotheses are stated and for how the t distribution diagram is drawn?)

a.Is the null hypothesis stated above one-tailed or two-tailed?Justify your answer.

b.What type of test should be used to test the null hypothesis stated?Justify your answer.

      c.Using the A-B-C-D format, test the null hypothesis. (Use ? = .05)

The researchers wanted to know whether there was a difference in average pain levels for the Magnet Treatment Group and the Placebo Group at the beginning of the experiment. Why would it be reasonable and desirable to show that there were no differences?

a.Write the null and alternate hypotheses, in prose and notation.

b.Is the null hypothesis one-tailed or two-tailed?Justify your answer.

c.What conclusions would you draw if the null hypothesis were rejected?

d.What type of t test should be used to test the hypothesis?Justify your answer.

Murphy, another investigator who had used another type of magnet, obtained patterns of results that resembled Vallbona’s results. After the experiment with 21 subjects, Murphy’s treatment group’s mean pain score was 5.50, and the standard deviation was 2.50. Murphy wished to test whether his “After” mean was greater than Vallbona’s “After” mean.

Why would Murphy be interested in conducting this test? What information would this test provide?

Without testing any formal hypotheses, what do the data suggest about differences between Murphy’s “After” mean and Valbona’s “After” mean? Justify your answer.

Is the null hypothesis suggested above one-tailed or two-tailed? Justify your answer.

What type of inferential test should Murphy use to test the hypothesis? Justify your answer. HINT: In this case, Murphy chose to use Vallbona’s mean as a hypothesized value.

Using the A-B-C-D format demonstrated in class, test the null hypothesis that you stated in exercise 3d. (Use ? = .05)

Think of a research question that would be appropriate for an independent-samples t-test. Share:

The research question

Hypotheses in prose and notation.

The conclusion you would make if the null hypothesis were rejected.

Complete a t-test using the data collected during the first week of class (i.e., the question you asked classmates). You can compare groups via gender or major, depending on your hypothesis. For example, as I mentioned, last year an MLS student asked his classmates how many times they had seen Star Wars. He hypothesized that there was a significant difference between MLS and DEHS students, so he compared those two groups.

What type of inferential test should you use and why?

Using the A-B-C-D format demonstrated in class, test the null hypothesis. (Use ? = .05)

10 4 PW 10 9


In: Statistics and Probability

Managers tend to speak optimistically about the prospects of globalization, and for good reason. Globalization has...

Managers tend to speak optimistically about the prospects of globalization, and for good reason. Globalization has fostered an increasingly interconnected world, with more than $30 trillion in goods and services traded and more than $1 trillion in corporate investment each year. Advances in information technology and transportation have helped facilitate globalization—connecting developed and developing worlds, lifting some 400 million people out of poverty along the way.

Nations are now inextricably linked through global trade and investment. There is no turning back. Accordingly, managers often view globalization as a powerful and inevitable force, and they tend to treat it with reverence—speaking of it as if it were a breakthrough technology, the wave of the future that will change the world, if not their companies’ fortunes. And they tend to think of themselves as the champions of globalization, akin to explorers embarking on a mission to discover and conquer far-off, unexplored lands.

Managers express their optimism for globalization in terms of the profitability it can generate for their companies. They salivate at the potential for double-digit sales growth. They are seduced by opportunities that promise to slash costs by half or more, simply by shifting operations overseas. And they lead their companies on journeys to global markets in search of untapped and untold riches.

However, opportunity and reality do not always coincide. Although globalization certainly holds promise, it is also rife with hazards. It presents risks that managers fail to appreciate and that they often overlook. Sadly, in the high-stakes world of global strategy, companies regularly fail to convert potential into profits. Most companies are poorly positioned to capitalize on globalization’s potential, and many are spectacularly unsuccessful in their attempts to globalize.

China provides the setting for a classic cautionary tale about globalization. Given a population of more than 1.3 billion people and the market potential that goes hand in hand with a consumer base of that size, the prospect of expanding to China is enough to make any manager’s eyes light up. The potential is seemingly limitless.

But on further inspection, it becomes clear that China poses tremendous challenges for Western companies. The first obstacle is economic. Though China has made tremendous strides and enjoyed incredible growth since opening its markets to global trade and investment in 1979, the development of its economic institutions and its infrastructure has lagged behind that in the West. The second obstacle is cultural. Chinese consumers, for example, tend to be very different from those in the West, which makes it difficult for Western companies to appeal to local consumer tastes. The third obstacle is political. Western companies struggle to skillfully navigate China’s complex web of local and national political organizations. All of these factors led G.E.’s CEO Jeff Immelt to conclude: “China is big, but it is hard.”

Walmart has learned these lessons the hard way. Walmart’s ongoing troubles in China, since opening its first superstore in Shenzhen in 1996, reflect a fundamental misunderstanding of China’s political, economic, and cultural environments.

The American retailer has struggled to understand Chinese consumers and Chinese culture. Chinese consumers, unlike those in the U.S., differ widely from city to city in their needs. Walmart therefore struggles to find the right product mix to offer in the 117 cities and 25 provinces in which it operates. This makes it challenging to sell a core set of products nationwide.

Walmart has also suffered from troubled relationships with politicians—both local and national. The company has had its fair share of run-ins with the law. On one occasion the Chinese government fined Walmart for violating local and national laws and even forced it to close stores temporarily for purported product violations. Walmart paid the fines, even though the company believed the claims to be unfounded.

Although China has led the gobe in infrastructure investment over the last several years, outside of its largest cities (e.g., Shanghai, Beijing, Tianjin, Guangzhou, and Shenzhen), its infrastructure remains more than problematic. The efficient transport of goods from one region to another is a challenge because of China’s sheer physical size, and because its air, ground, and rail infrastructure does not meet developed country standards. Not surprisingly, Walmart’s China business has struggled to generate profits, and it has consistently underperformed in this huge and potentially lucrative market.

The lesson in all of this is that, when it comes to globalization, managers are not just optimists; all too often, they are unbridled optimists. They habitually overestimate the benefits of globalization and underestimate its costs. In evaluating globalization opportunities, managers often forget the other side of the opportunity equation: risk. Risk goes hand in hand with opportunity, and managers fail to accurately account for the risks they face in global markets.

Managers often make dangerous assumptions about what it takes to succeed in global markets. They tend to assume that their current business model, one they successfully and profitably exploit in their home country, will translate simply and effectively to other countries, yielding similar levels of profitability. These same managers fail to account for real and salient differences between nations, and fail to consider how those differences generate operational risks that may negatively impact their business. Unfortunately, they end up learning the hard way that the risk borne out of cross-country differences can overwhelm even the best-laid globalization plans. And Walmart is no exception.

To improve the practice of global business and to make better global expansion decisions, managers need a more sophisticated understanding of the economic, political, and cultural environments in the countries in which they intend to operate. They must appreciate how nations differ economically, politically, and culturally, and how those differences manifest as increasing risks (and costs). They then need to incorporate those risks into their existing strategy and financial decision models.

Robert Salomon is a professor of International Management and Faculty Scholar at NYU’s Stern School of Business and has researched globalization and global strategy for nearly 20 years. This article is excerpted from his book, Global Vision: How Companies Can Overcome the Pitfalls of Globalization. Published by Palgrave Macmillan; reproduced by permission.
Question
from the above case study it has been required that identify challenges wallmart need to overcome affecting their implemation of international strategy. write answer in between 200 to 300 word

In: Accounting

Data Set 3 --Buena School District Bus Data Bus Number Maintenance Age Miles Type Bus-Mfg Passenger...

Data Set 3 --Buena School District Bus Data
Bus Number Maintenance Age Miles Type Bus-Mfg Passenger
X1 X2 X3 X4 X5 X6 X7
135 329 7 853 Diesel Bluebird 55 Passenger
200 505 10 822 Diesel Bluebird 55 Passenger
40 466 10 865 Gasoline Bluebird 55 Passenger
387 422 8 869 Gasoline Bluebird 55 Passenger
326 433 9 848 Diesel Bluebird 55 Passenger
861 474 10 845 Gasoline Bluebird 55 Passenger
122 558 10 885 Gasoline Bluebird 55 Passenger
887 357 8 760 Diesel Bluebird 6 Passenger
686 329 3 741 Diesel Bluebird 55 Passenger
490 497 10 859 Gasoline Bluebird 55 Passenger
464 355 3 806 Gasoline Bluebird 55 Passenger
875 489 9 858 Diesel Bluebird 55 Passenger
883 436 2 785 Gasoline Bluebird 55 Passenger
57 455 7 828 Diesel Bluebird 55 Passenger
482 514 11 980 Gasoline Bluebird 55 Passenger
704 503 8 857 Diesel Bluebird 55 Passenger
731 432 6 819 Diesel Bluebird 42 Passenger
75 478 6 821 Diesel Bluebird 55 Passenger
600 493 10 1008 Diesel Bluebird 55 Passenger
358 461 6 849 Diesel Bluebird 55 Passenger
692 469 8 812 Diesel Bluebird 55 Passenger
43 439 9 832 Gasoline Bluebird 55 Passenger
500 369 5 842 Gasoline Bluebird 55 Passenger
279 390 2 792 Diesel Bluebird 55 Passenger
884 381 9 882 Diesel Bluebird 55 Passenger
977 501 7 874 Diesel Bluebird 55 Passenger
725 392 5 774 Diesel Bluebird 55 Passenger
982 441 1 823 Diesel Bluebird 55 Passenger
39 411 6 804 Gasoline Bluebird 55 Passenger
418 504 9 842 Diesel Bluebird 55 Passenger
984 392 8 851 Diesel Bluebird 55 Passenger
953 423 10 835 Diesel Bluebird 55 Passenger
507 410 7 866 Diesel Bluebird 55 Passenger
540 529 4 846 Gasoline Bluebird 55 Passenger
695 477 2 802 Diesel Bluebird 55 Passenger
321 450 6 856 Diesel Bluebird 6 Passenger
918 390 5 799 Diesel Bluebird 55 Passenger
101 424 4 827 Diesel Bluebird 55 Passenger
714 433 7 817 Diesel Bluebird 42 Passenger
768 494 7 815 Diesel Bluebird 42 Passenger
29 396 6 784 Gasoline Bluebird 55 Passenger
554 458 4 817 Diesel Bluebird 14 Passenger
699 475 9 816 Gasoline Bluebird 55 Passenger
954 476 10 827 Diesel Bluebird 42 Passenger
660 337 6 819 Gasoline Bluebird 55 Passenger
520 492 10 836 Diesel Bluebird 55 Passenger
814 426 4 757 Diesel Bluebird 55 Passenger
120 503 10 883 Diesel Keiser 42 Passenger
427 359 7 751 Gasoline Keiser 55 Passenger
759 546 8 870 Diesel Keiser 55 Passenger
10 427 5 780 Gasoline Keiser 14 Passenger
880 474 9 857 Gasoline Keiser 55 Passenger
481 382 3 818 Gasoline Keiser 6 Passenger
370 459 8 826 Gasoline Keiser 55 Passenger
989 380 9 803 Diesel Keiser 55 Passenger
162 406 3 798 Gasoline Keiser 55 Passenger
732 471 9 815 Diesel Keiser 42 Passenger
751 444 2 757 Diesel Keiser 14 Passenger
948 452 9 831 Diesel Keiser 42 Passenger
61 442 9 809 Diesel Keiser 55 Passenger
9 414 4 864 Gasoline Keiser 55 Passenger
365 462 6 799 Diesel Keiser 55 Passenger
693 469 9 775 Gasoline Keiser 55 Passenger
38 432 6 837 Gasoline Keiser 14 Passenger
724 448 8 790 Diesel Keiser 42 Passenger
603 468 4 800 Diesel Keiser 14 Passenger
45 478 6 830 Diesel Keiser 55 Passenger
754 515 14 895 Diesel Keiser 14 Passenger
678 428 7 842 Diesel Keiser 55 Passenger
767 493 6 816 Diesel Keiser 55 Passenger
705 403 4 806 Diesel Keiser 42 Passenger
353 449 4 817 Gasoline Keiser 55 Passenger
156 561 12 838 Diesel Thompson 55 Passenger
833 496 8 839 Diesel Thompson 55 Passenger
314 459 11 859 Diesel Thompson 6 Passenger
396 457 2 815 Diesel Thompson 55 Passenger
398 570 9 844 Diesel Thompson 14 Passenger
168 467 7 827 Gasoline Thompson 55 Passenger
671 504 8 866 Gasoline Thompson 55 Passenger
193 540 11 847 Diesel Thompson 55 Passenger

The attached MS-Excel file contains data on the contains data the bus fleet of the Buena School district. Download the file and analyze the characteristics of the Buena Bus fleet.

  1. Sort the data by type of Bus Manufacturer and calculate the Average Cost of Maintenance for each Manufacturer
  2. Sort the data by Fuel Type and calculate the cost of Maintenance and the Average Mileage by each fuel type of fuel
  3. Present your results in a table and a chart. Cut and paste your chart and table into MS-Word and attach your results.

In: Accounting

Assignment 4 You will be writing an inventory system that is backed by JSON data and...

Assignment 4 You will be writing an inventory system that is backed by JSON data and will be working with a starter file that contains a JSON string. The code you write will need to follow the following guidelines.

You’re at work one day and your boss asks you about that fancy programming language you’ve been learning, Python. She asks you if you can use it to read JSON data from a supplier and build an inventory. “Of course!” you say. She tells you that your parts supplier, Midwest Widget Co, has sent the company JSON data that needs to be loaded and then checked against orders. You’ll need to load the JSON data, and then take input from a user to order new parts. If the part is not in stock, or the number of parts is greater than the available inventory, you need to alert the user and show them that its either out of stock or that there are less available than requested. Once the user is done entering in their order, you’ll need to package up their order in JSON format, since that’s what Midwestern Widget Co uses after all!

The JSON data is comprised of a few nested dictionaries. In the top level, there is a key called “parts” that maps to a list that contains all the parts available for ordering. Each of those parts is also a key into the dictionary. That key maps to dictionary that has two values, quantity and price. The quantity maps to an integer with the number of parts available for order, the price maps to a float with the price of the part. A sample JSON object is provided below:

{

"parts":[

"widget",

"sprocket",

"thing-a-ma-bob"

],

"widget":{

"price":0.99,

"quantity":74

},

"sprocket":{

"price":3.99,

"quantity":123

},

"thing-a-ma-bob":{

"price":1.78,

"quantity":57

}

}

The strings in the list in parts are the keys for the rest of the data in the dictionary. Those keys map to separate dictionaries with the prices and quantities. The json string is provided in the code, it is called supplier_data.

The ordering system will work like this:

Prompt the user for input, and indicate they can enter in the word “quit” to quit. The user should enter in a part and then the quantity on two separate lines (so you’ll need two input statements). After both pieces of information have been entered in, check if the order is allowed or not, and display an error message with the appropriate information (part doesn’t exist, part exists but not enough quantity). If the order is valid, store it and continue. Once the user enters quit, print out an order summary showing the part, number ordered, the price per part and total per part with a grand total at the end. The order data MUST be stored in a dictionary. You must also allow the user to order a part more than once and validate that both orders are not exceeding the total amount available!

Sample Output:

Your program should produce output that is very similar if not identical to this. Major deviations from the formatting will result in points lost. The error handling behavior should be the same.

Welcome to the parts ordering system, please enter in a part name, followed by a quantity

Parts for order are:

sprocket

gizmo

widget

dodad

Please enter in a part name, or quit to exit: blargh

Error, part does not exist, try again

Please enter in a part name, or quit to exit: quit

Your order Total: $0

Thank you for using the parts ordering system!

And another run with an actual order

Welcome to the parts ordering system, please enter in a part name, followed by a quantity

Parts for order are:

sprocket

gizmo

widget

dodad

Please enter in a part name, or quit to exit: gizmo

Please enter in a quantity to order: 1000

Error, only 2 of gizmo are available!

Please enter in a part name, or quit to exit: gizmo

Please enter in a quantity to order: 1

Please enter in a part name, or quit to exit: sprocket

Please enter in a quantity to order: 15

Please enter in a part name, or quit to exit: widget

Please enter in a quantity to order: 1

Please enter in a part name, or quit to exit: quit

Your order

gizmo - 1 @ 7.98 = 7.98

sprocket - 15 @ 3.99 = 59.85

widget - 1 @ 14.32 = 14.32

Total: $82.15

Thank you for using the parts ordering system!

Another run with multiple orders for a single part

Welcome to the parts ordering system, please enter in a part name, followed by a quantity

Parts for order are:

sprocket

gizmo

widget

dodad

Please enter in a part name, or quit to exit: gizmo

Please enter in a quantity to order: 2

Please enter in a part name, or quit to exit: gizmo

Please enter in a quantity to order: 2

Error, only 0 of gizmo are available!

Please enter in a part name, or quit to exit: quit

Your order

gizmo - 2 @ 7.98 = 15.96

Total: $15.96

Thank you for using the parts ordering system!

Tips and Hints 1. Start on something small and get it working before moving on. Don’t try and tackle it all at once! 2. You’ll need to validate the input between inputs 3. You can use print() with no arguments to print out extra blank lines 4. A while loop is ideal for the main program loop 5. You’ll need to check if a part has already been ordered before checking if sufficient quantity is available. If it has been ordered, you’ll need to account for that when checking the inventory levels 6. supplier_data in the provided code is a JSON string. You need to convert it to a dict with json.loads

**CODE TEMPLATE**

# Program header goes here
#
#
#


supplier_data = '{"parts": ["sprocket", "gizmo", "widget", "dodad"], "sprocket": {"price": 3.99, "quantity": 32}, "gizmo": {"price": 7.98, "quantity": 2}, "widget": {"price": 14.32, "quantity": 4}, "dodad": {"price": 0.5, "quantity": 0}}'


# Your code goes here

In: Computer Science