According to a report of COVID-19 death rates in the United States from CDC as of April 6th 2020, New York has around 21.2 per 100,000 people for the death rate, which is the state with the highest number of COVID-19 cases.

a) Obtain a point estimate for the population proportion of Americans who have died from COVID-19 in New York state.

b) Verify that the requirements for constructing a confidence interval about p are satisfied.

c) Construct a 90% confidence interval for the population proportion of Americans who have died in New York since the COVID-19 pandemic.

d) Interpret the interval.

8. Purchasing-power parity

Using data from The Economist's Big Mac Index for 2016, the following table shows the local currency price of a Big Mac in several countries as well as the actual exchange rate between each country and the United States. At the time of the data collection, a Big Mac would have cost you $4.93 in the United States and GBP 2.89 in the United Kingdom. The actual exchange rate between the British pound and the U.S. dollar was $1.63 per pound. The dollar price of a Big Mac purchased in the United Kingdom was, therefore, computed as follows:

For the price you paid for a Big Mac in the United States, you could have purchased a Big Mac in the United Kingdom and had some change left over for fries!

Complete the final column of the table by computing the dollar price of a Big Mac for the countries where this amount is not given.

Note: Round your answers to the nearest cent.

Source: “Currency Comparison, To Go,” The Economist, last modified January 7, 2016, accessed July 8, 2016, http://www.economist.com/blogs/graphicdetail/2016/01/daily-chart-7.

Purchasing-power parity (PPP) theory states that exchange rates would need to equalize the prices of goods in any two countries. For the dollar price of a Big Mac to be the same in both countries, a U.S. citizen would need to be able to convert $4.93 into exactly GBP 2.89. To find the exchange rate at which hamburger purchasing power is the same in both countries, divide the price in the United States by the price in the United Kingdom:

The exchange rate that would have equalized the dollar price of a Big Mac in the United States and the Eurozone (that is, the PPP exchange rate for Big Macs) is   . This change would mean that the euro had   against the dollar.

If Big Macs were a durable good that could be costlessly transported between countries, which of the following would present an arbitrage opportunity? Check all that apply.

Exporting Big Macs from Switzerland to China

Exporting Big Macs from the Eurozone to the United States

Exporting Big Macs from the United Kingdom to Poland

Outline three possible arguments for not recognising internally generated Goodwill as an intangible asset in accordance with NZ IAS 38.

(b) As of 30 June 2020, Rezar Ltd has the following intangible assets to report in the financial statements.

(i) The company has acquired patents on 1 July 2016 for $45,000. This patent allows the production of 300,000 units. During the year ended 30 June 2020, the company produced 36,000 units.

(ii) Externally acquired Goodwill as at 1 July 2019 was $85,000. Goodwill has been impaired by $10,000 during the current year.

(iii) On 1 October 2019, the company acquired a franchise for $27,000 for 5 years. There is great demand for this franchise in the current market, and it has a fair value of $23,000 as of 30 June 2020.

Required: Explain how each of the above intangible assets should be measured in accordance with NZ IAS 38 as of 30 June 2020. Your answer should include the most appropriate model or models available to Rezar Ltd to measure above intangible assets, amortisation (if any), impairments (if any) and the closing balances as at 30 June 2020. Show all calculations. No journal entries required.

The National Sleep Foundation surveyed representative samples of adults in six different countries to ask questions about sleeping habits.† Each person in a representative sample of 250 adults in each of these countries was asked how much sleep they get on a typical work night. For the United States, the sample mean was 391 minutes, and for Mexico the sample mean was 426 minutes. Suppose that the sample standard deviations were 21 minutes for the U.S. sample and 47 minutes for the Mexico sample. The report concludes that on average, adults in the United States get less sleep on work nights than adults in Mexico. Is this a reasonable conclusion? Support your answer with an appropriate hypothesis test. (Use α = 0.05.)

Use μ₁ for Mexico and μ₂ for the United States.)

State the appropriate null and alternative hypotheses.

H₀: μ₁ − μ₂ = 0

H_a: μ₁ − μ₂ ≠ 0

H₀: μ₁ − μ₂ ≠ 0

H_a: μ₁ − μ₂ = 0

H₀: μ₁ − μ₂ = 0

H_a: μ₁ − μ₂ > 0

H₀: μ₁ − μ₂ > 0

H_a: μ₁ − μ₂ = 0

H₀: μ₁ − μ₂ < 0

H_a: μ₁ − μ₂ > 0

Find the test statistic and P-value. (Use a table or technology. Round your test statistic to one decimal place and your P-value to three decimal places.)

t=

P-value=

State the conclusion in the problem context.

We reject H₀. It is reasonable to conclude that on average, adults in the United States get less sleep on work nights than adults in Mexico.

We fail to reject H₀. It is not reasonable to conclude that on average, adults in the United States get less sleep on work nights than adults in Mexico.    

We fail to reject H₀. It is reasonable to conclude that on average, adults in the United States get less sleep on work nights than adults in Mexico.

We reject H₀. It is not reasonable to conclude that on average, adults in the United States get less sleep on work nights than adults in Mexico.

Researchers interviewed street prostitutes in Canada and the United States. The mean age of the 100 Canadian prostitutes upon entering prostitution was 18 with a standard deviation of seven. The mean age of the 130 United States prostitutes upon entering prostitution was 20 with a standard deviation of nine. Is the mean age of entering prostitution in Canada lower than the mean age in the United States? Test at a 1% significance level.

NOTE: If you are using a Student's t-distribution for the problem, including for paired data, you may assume that the underlying population is normally distributed. (In general, you must first prove that assumption, though.)

Part (d)
State the distribution to use for the test. (Enter your answer in the form z or tdf where df is the degrees of freedom. Round your answer to two decimal places.)
  

Part (e)
What is the test statistic? (If using the z distribution round your answer to two decimal places, and if using the t distribution round your answer to three decimal places.)
Part (f)
What is the p-value? (Round your answer to four decimal places.)


(f part 2)Explain what the p-value means for this problem.

• If H0 is true, then there is a chance equal to the p-value that the sample mean age of entering prostitution in Canada is at least 2 less than the sample mean age of entering prostitution in the United States.

• If H0 is false, then there is a chance equal to the p-value that the sample mean age of entering prostitution in Canada is at least 2 more than the sample mean age of entering prostitution in the United States.    

• If H0 is true, then there is a chance equal to the p-value that the sample mean age of entering prostitution in Canada is at least 2 more than the sample mean age of entering prostitution in the United States.

• If H0 is false, then there is a chance equal to the p-value that the sample mean age of entering prostitution in Canada is at least 2 less than the sample mean age of entering prostitution in the United States.

1. Identify and explain how two rules of the United States electoral system act as obstacles to minor party candidates winning elections
2. Minor parties make important contributions to the United States political system in spite of the institutional obstacles to their candidates’ success. Please identify a minor party and describe some of the contributions it has made

A major example of using a procedural definition of equality is the concept of equality of opportunity when applied to the economy. What does this concept mean? Is the United States really a land of equal opportunity? What are the obstacles to equality of opportunity in the United States? Should the government do more or do less, or is it doing the right amount to reduce these obstacles?

The United States has a low trade level compared to a country like Japan. If countries could not trade, what would happen to the living standards in those countries with low trade levels, like the United States, as well as in countries with high trade levels such as Japan?  Cite at least one current example in your discussion.

Sugar production is highly protected in the United States. Sugar importers must pay such high tariffs that it is hardly profitable for them to sell any sugar in the United States. Who are the inners and losers from such protectionism? Is the resulting market economically efficient? Why? If not, why would the government continue import restrictions that promote economic efficiency?  

Problem 9 - PYTHON

There is a CSV-formatted file called olympics2.csv. Write code that creates a dictionary named country_olympians where the keys are country names and the values are lists of unique olympians from that country (no olympian's name should appear more than once for a given country).

Name,Sex,Age,Team,Event,Medal
A Dijiang,M,24,China,Basketball,NA
A Lamusi,M,23,China,Judo,NA
Gunnar Nielsen Aaby,M,24,Denmark,Football,NA
Edgar Lindenau Aabye,M,34,Sweden,Tug-Of-War,Gold
Christine Jacoba Aaftink,F,21,Netherlands,Speed Skating,NA
Christine Jacoba Aaftink,F,21,Netherlands,Speed Skating,NA
Christine Jacoba Aaftink,F,25,Netherlands,Speed Skating,NA
Christine Jacoba Aaftink,F,25,Netherlands,Speed Skating,NA
Christine Jacoba Aaftink,F,27,Netherlands,Speed Skating,NA
Christine Jacoba Aaftink,F,27,Netherlands,Speed Skating,NA
Per Knut Aaland,M,31,United States,Cross Country Skiing,NA
Per Knut Aaland,M,31,United States,Cross Country Skiing,NA
Per Knut Aaland,M,31,United States,Cross Country Skiing,NA
Per Knut Aaland,M,31,United States,Cross Country Skiing,NA
Per Knut Aaland,M,33,United States,Cross Country Skiing,NA
Per Knut Aaland,M,33,United States,Cross Country Skiing,NA
Per Knut Aaland,M,33,United States,Cross Country Skiing,NA
Per Knut Aaland,M,33,United States,Cross Country Skiing,NA
John Aalberg,M,31,United States,Cross Country Skiing,NA
John Aalberg,M,31,United States,Cross Country Skiing,NA
John Aalberg,M,31,United States,Cross Country Skiing,NA
John Aalberg,M,31,United States,Cross Country Skiing,NA
John Aalberg,M,33,United States,Cross Country Skiing,NA
John Aalberg,M,33,United States,Cross Country Skiing,NA
John Aalberg,M,33,United States,Cross Country Skiing,NA
John Aalberg,M,33,United States,Cross Country Skiing,NA
"Cornelia ""Cor"" Aalten (-Strannood)",F,18,Netherlands,Athletics,NA
"Cornelia ""Cor"" Aalten (-Strannood)",F,18,Netherlands,Athletics,NA
Antti Sami Aalto,M,26,Finland,Ice Hockey,NA
"Einar Ferdinand ""Einari"" Aalto",M,26,Finland,Swimming,NA
Jorma Ilmari Aalto,M,22,Finland,Cross Country Skiing,NA
Jyri Tapani Aalto,M,31,Finland,Badminton,NA
Minna Maarit Aalto,F,30,Finland,Sailing,NA
Minna Maarit Aalto,F,34,Finland,Sailing,NA
Pirjo Hannele Aalto (Mattila-),F,32,Finland,Biathlon,NA
Arvo Ossian Aaltonen,M,22,Finland,Swimming,NA
Arvo Ossian Aaltonen,M,22,Finland,Swimming,NA
Arvo Ossian Aaltonen,M,30,Finland,Swimming,Bronze
Arvo Ossian Aaltonen,M,30,Finland,Swimming,Bronze
Arvo Ossian Aaltonen,M,34,Finland,Swimming,NA
Juhamatti Tapio Aaltonen,M,28,Finland,Ice Hockey,Bronze
Paavo Johannes Aaltonen,M,28,Finland,Gymnastics,Bronze
Paavo Johannes Aaltonen,M,28,Finland,Gymnastics,Gold
Paavo Johannes Aaltonen,M,28,Finland,Gymnastics,NA
Paavo Johannes Aaltonen,M,28,Finland,Gymnastics,Gold
Paavo Johannes Aaltonen,M,28,Finland,Gymnastics,NA
Paavo Johannes Aaltonen,M,28,Finland,Gymnastics,NA
Paavo Johannes Aaltonen,M,28,Finland,Gymnastics,NA
Paavo Johannes Aaltonen,M,28,Finland,Gymnastics,Gold
Paavo Johannes Aaltonen,M,32,Finland,Gymnastics,NA
Paavo Johannes Aaltonen,M,32,Finland,Gymnastics,Bronze
Paavo Johannes Aaltonen,M,32,Finland,Gymnastics,NA
Paavo Johannes Aaltonen,M,32,Finland,Gymnastics,NA
Paavo Johannes Aaltonen,M,32,Finland,Gymnastics,NA
Paavo Johannes Aaltonen,M,32,Finland,Gymnastics,NA
Paavo Johannes Aaltonen,M,32,Finland,Gymnastics,NA
Paavo Johannes Aaltonen,M,32,Finland,Gymnastics,NA
Timo Antero Aaltonen,M,31,Finland,Athletics,NA
Win Valdemar Aaltonen,M,54,Finland,Art Competitions,NA