Differences in productivity are usually the major force behind differences in wages and unit labor costs. Suppose that a single unskilled worker at a pottery factory in Mexico can produce 1 mug per hour. By comparison, suppose that a single unskilled worker at a pottery factory in the United States can produce 15 mugs per hour because more and better machinery generates higher labor productivity. The Mexican mugs and the American mugs are identical in quality and durability and sell for the same price. The daily minimum wage in Mexico is 70 pesos per day for an 8-hour work day, and the exchange rate between Mexican pesos and U.S. dollars is 10 pesos per dollar. The federal minimum wage in the United States is $7.25 per hour.
Instructions: Round your answers to 3 decimal places.
a. If unskilled pottery workers are paid the local minimum wage in both countries, how much is the labor cost per mug for mugs produced in Mexico?
For mugs produced in the United States?
b. With regard to mug production, how much higher are labor costs per hour in the United States?
c. With regard to mug production, how much higher are labor costs per unit in Mexico?
d. Do higher labor costs per hour always imply higher labor costs per unit?
(Click to select) No Yes
e. If firms with lower labor costs per unit expand, while those with higher labor costs per unit contract, in which country will mug-making firms be increasing in size and hiring more employees?
(Click to select) The United States Mexico
If unskilled pottery workers relocate to where they can find jobs, to which country will they be moving?
In: Economics
Which hypothesis test you believe you should use and why.
One Sample Proportion Z-test
Two Sample Proportion Z-test
One Mean t-test
Pooled t-test
Non-Pooled t-test
Paired t-test
ANOVA F-test
Bootstrapping is also an option
Questions:
The NOAA National Climatic Data Center of the United States provides data on the average annual temperature for every state in the United States. The average annual temperatures are based on data collected by weather stations throughout each state during the years 1971 to 2000. Is there strong evidence that the mean average annual temperature in the United States is greater than 50 degrees Fahrenheit? Explain. Use a significance level of 5%.
As gas prices continue to rise, more customers are beginning to take into account miles per gallon (a measure of the average distance traveled per unit of energy consumed) when determining which type of car to purchase. Do cars made in Japan typically get more miles per gallon than cars made in the United States? A random sample of 79 cars made in Japan had a mean of 30.48 and a standard deviation of 6.11 miles per gallon. A random sample of 249 cars made in the United States produced a mean of 20.14 and a standard deviation of 6.41 miles per gallon. Use a significance level of 0.10.
The U.S. Census Bureau reports that 26% of all U.S. businesses are owned by women. A Colorado consulting firm surveys a random sample of 410 businesses in the Denver area and finds that 115 of them have women owners. Should the firm conclude that its area is unusual? Test an appropriate hypothesis and state your conclusion. Use =0.05.
In: Statistics and Probability
An American worker can produce either 5 cars or 9 tons of grain a year. A Japanese worker can produce either 3 cars or 9 tons of grain a year. To keep things simple, assume that each country has 100 million workers.
Complete the following table with the number of workers needed to make one car or 1 ton of grain in the United States and Japan.
|
Workers Needed to Make |
||
|---|---|---|
| 1 Car | 1 Ton of Grain | |
| United States | 1/5 | 1/9 |
| Japan | 1/3 | 1/9 |
Use the blue line (circle symbol) to graph the production possibilities frontier for the American economy. Then use the green line (triangle symbol) to graph the production possibilities frontier for the Japanese economy.
U.S.Japan01002003004005006007008009001000500450400350300250200150100500Cars (Millions)Grain (Millions of tons)900, 0Y-Intercept: 300X-Intercept: NoneSlope: 0
Complete the following table by determining the opportunity cost of a car and of a ton of grain for both the United States and Japan.
|
Opportunity Cost of |
||
|---|---|---|
| 1 Car | 1 Ton of Grain | |
| (In terms of tons of grain given up) | (In terms of cars given up) | |
| United States | ||
| Japan | ||
Given this information, has an absolute advantage in producing cars, and has an absolute advantage in producing grain.
Also, has a comparative advantage in producing cars, and has a comparative advantage in producing grain.
Assume that without trade, half of each country's workers produce cars and half produce grain.
Complete the following table with the quantities of cars produced and consumed in each country if there is no trade.
| Cars Produced and Consumed | Tons of Grain Produced and Consumed | |
|---|---|---|
| (Millions) | (Millions) | |
| United States | ||
| Japan |
True or False: Both countries would be better off if they produced the good in which they have a comparative advantage and then traded 400 million tons of grain for 200 million cars.
True
False
In: Economics
Review the following PDF to learn more:
MMWR: Strategies for Reducing Health Disparities—Selected CDC-Sponsored Interventions, United States, 2014
Create a 4- to 5-page Microsoft Word document that addresses the following:
Compare the patterns of the major diseases of
Hispanic/Latino groups and their rates and health effects between
the other racial or ethnic groups living in the United
States.
Identify at least one consequence that a lack of
access to healthcare has on Hispanics/Latinos.
Explain why access to care issues will need to be
monitored even more closely within the U.S. healthcare system
beginning 2014.
Find at least two scholarly journal articles that
discuss all or at least one of the topic areas related to
Hispanic/Latino health disparities in the United States. Provide a
synopsis of each article.
Explain what type of barrier(s) (structural,
financial, or socio-cultural) each article examines? Describe at
least two policies or strategies that can be implemented to improve
access to healthcare services as they relate to the articles you
reviewed.
Compare the patterns of the major diseases of
Hispanic/Latino groups and their rates and health effects between
the other racial or ethnic groups living in the United
States.
Identify at least one consequence that a lack of
access to healthcare has on Hispanics/Latinos.
Explain why access to care issues will need to be
monitored even more closely within the U.S. healthcare system
beginning 2014.
Find at least two scholarly journal articles that
discuss all or at least one of the topic areas related to
Hispanic/Latino health disparities in the United States. Provide a
synopsis of each article.
Explain what type of barrier(s) (structural,
financial, or socio-cultural) each article examines? Describe at
least two policies or strategies that can be implemented to improve
access to healthcare services as they relate to the articles you
reviewed.
In: Nursing
I need to use Excel to solve the following:
A United Nations report shows the mean family income for Mexican migrants to the United States is $27,000 per year. A Farm Labor Organizing Committee evaluation of 25 Mexican family units reveals the mean to be $30,000 with a sample standard deviation of $10,000. Does this information disagree with the United Nations report? Apply the .01 significance level.
In: Statistics and Probability
Suppose that we randomly select 50 billing statements from each of the computer databases of the Hotel A, the Hotel B, and the Hotel C chains, and record the nightly room rates. The means and standard deviations for the data are given in the table.
| Hotel A | Hotel B | Hotel C | |
|---|---|---|---|
| Sample Average ($) | 140 | 180 | 120 |
|
Sample Standard Deviation |
17.7 | 22.6 | 12.5 |
(a) Find a 95% confidence interval for the difference in the average room rates for the Hotel A and the Hotel B chains. (Use Hotel A − Hotel B. Round your answers to two decimal places.)
$______ to $______
(b)Find a 99% confidence interval for the difference in the average room rates for the Hotel B and the Hotel C chains. (Use Hotel B − Hotel C. Round your answers to two decimal places.)
$______ to $______
In: Statistics and Probability
Suppose that we randomly select 50 billing statements from each of the computer databases of the Hotel A, the Hotel B, and the Hotel C chains, and record the nightly room rates. The means and standard deviations for the data are given in the table.
| Hotel A | Hotel B | Hotel C | |
|---|---|---|---|
| Sample Average ($) | 140 | 180 | 120 |
| Sample Standard Deviation |
17.7 | 22.6 | 12.5 |
(a) Find a 95% confidence interval for the difference in the average room rates for the Hotel A and the Hotel B chains. (Use Hotel A − Hotel B. Round your answers to two decimal places.)
$______ to $______
(b)Find a 99% confidence interval for the difference in the average room rates for the Hotel B and the Hotel C chains. (Use Hotel B − Hotel C. Round your answers to two decimal places.)
$______ to $______
In: Statistics and Probability
Suppose that we randomly select 50 billing statements from each of the computer databases of the Hotel A, the Hotel B, and the Hotel C chains, and record the nightly room rates. The means and standard deviations for the data are given in the table.
| Hotel A | Hotel B | Hotel C | |
|---|---|---|---|
| Sample Average ($) | 140 | 180 | 120 |
| Sample Standard Deviation |
17.7 | 22.6 | 12.5 |
(a) Find a 95% confidence interval for the difference in the average room rates for the Hotel A and the Hotel B chains. (Use Hotel A − Hotel B. Round your answers to two decimal places.)
$______ to $______
(b)Find a 99% confidence interval for the difference in the average room rates for the Hotel B and the Hotel C chains. (Use Hotel B − Hotel C. Round your answers to two decimal places.)
$______ to $______
In: Statistics and Probability
(Use Excel or SPSS to complete this Assignment).
A random sample of respondents was drawn from three Latin American countries: Nicaragua, Guatemala, and Costa Rica. The variable if interest is the duration (in months) of stay in the United States during a respondent’s first migration to the United States.
Nicaragua: 4, 6, 6, 6, 12, 36, 36, 36, 36, 60, 72, 78, 96, 120,
126, 156, 162, 162, 186, 540
Guatemala: 1, 1, 12, 24, 24, 24, 36, 36, 42, 60, 78, 84, 102, 102,
102, 102,132, 144
Costa Rica: 12, 12, 12, 12, 14, 15, 15, 18, 18, 24, 36, 48, 66,
120, 150, 150, 174, 282, 288
Which of the three countries above has the highest median value? Does this support your idea that respondents from Latin American countries that are closer to the United States have a higher median duration of stay in the United States during their first migration than respondents from Latin American countries that are further away?
In: Statistics and Probability
plot on a graph, men's times as X column and Y column being women's times
Men’s 2015 World Championship – Final Results (top 17 finishers)
|
Rank |
Name |
Nationality |
Time (seconds) |
|
1 |
Mo Farah |
Great Britain (GBR) |
1621.13 |
|
2 |
Geoffrey Kipsang |
Kenya (KEN) |
1621.76 |
|
3 |
Paul Tanui |
Kenya (KEN) |
1622.83 |
|
4 |
Bedan Karoki |
Kenya (KEN) |
1624.77 |
|
5 |
Galen Rupp |
United States (USA) |
1628.91 |
|
6 |
Abrar Osman |
Eritrea (ERI) |
1663.21 |
|
7 |
Ali Kaya |
Turkey (TUR) |
1663.69 |
|
8 |
Timothy Toroitich |
Uganda (UGA) |
1664.90 |
|
9 |
Joshua Kiprui Cheptegei |
Uganda (UGA) |
1668.89 |
|
10 |
Muktar Edris |
Ethiopia (ETH) |
1674.47 |
|
11 |
Mosinet Geremew |
Ethiopia (ETH) |
1687.50 |
|
12 |
El Hassan El-Abbassi |
Bahrain (BHR) |
1692.57 |
|
13 |
Nguse Tesfaldet |
Eritrea (ERI) |
1694.72 |
|
14 |
Cameron Levins |
Canada (CAN) |
1695.19 |
|
15 |
Hassan Mead |
United States (USA) |
1696.30 |
|
16 |
Shadrack Kipchirchir |
United States (USA) |
1696.30 |
|
17 |
Arne Gabius |
Germany (GER) |
1704.47 |
Women’s 2015 World Championship – Final Results (top 17 finishers)
|
Rank |
Name |
Nationality |
Time (seconds) |
|
1 |
Vivian Cheruiyot |
Kenya (KEN) |
1901.31 |
|
2 |
Gelete Burka |
Ethiopia (ETH) |
1901.77 |
|
3 |
Emily Infeld |
United States (USA) |
1903.49 |
|
4 |
Molly Huddle |
United States (USA) |
1903.58 |
|
5 |
Sally Kipyego |
Kenya (KEN) |
1904.42 |
|
6 |
Shalane Flanagan |
United States (USA) |
1906.23 |
|
7 |
Alemitu Heroye |
Ethiopia (ETH) |
1909.73 |
|
8 |
Betsy Saina |
Kenya (KEN) |
1911.35 |
|
9 |
Belaynesh Oljira |
Ethiopia (ETH) |
1913.01 |
|
10 |
Susan Kuijken |
Netherlands (NED) |
1914.32 |
|
11 |
Jip Vastenburg |
Netherlands (NED) |
1923.03 |
|
12 |
Sara Moreira |
Portugal (POR) |
1926.14 |
|
13 |
Kasumi Nishihara |
Japan (JPN) |
1932.95 |
|
14 |
Brenda Flores |
Mexico (MEX) |
1935.26 |
|
15 |
Kate Avery |
Great Britain (GBR) |
1936.19 |
|
16 |
Trihas Gebre |
Spain (ESP) |
1940.87 |
|
17 |
Juliet Chekwel |
Uganda (UGA) |
1940.95 |
In: Statistics and Probability