Run a multiple regression with trend and seasonal; forecast the next 12 months.   

4.

The Chinese government’s tobacco monopoly accounts for 12% of the government’s revenue. It sells to China's 310 million smokers, 1/4 of the world's smoking population, who consume 1700 billion cigarettes a year, about 30% of global consumption

By imposing a 230% tax rate on foreign cigarettes, and by imposing import quotas and restrictions, the government limited legal foreign cigarette sales to less than 2% of total Chinese sales in the late 1990s. However, by 2003 the foreign cigarette share was only 10%. To appease the World Trade Association, China agreed to lift restrictions on the retail sale of imported cigarettes by January 2004, to reduce the tariff on cigarettes from the current 65% to 24% , and to phase out the tariff over the next two years. Thus, the state's monopoly will be eroded.   Expectations were that the price of imported cigarettes would drop by half and imported cigarettes would gain a major share of the Chinese market.   

1. In this case study discuss the impacts of the quotas, tariffs and restrictions on Entry into the Chinese market. What was the intended end result? Explain.

2. Given your answer in (a), use a graphical analysis to demonstrate and explain what occurred after the restrictions were lifted.

With double-digit annual percentage increases in the cost of health insurance, more and more workers are likely to lack health insurance coverage (USA Today, January 23, 2004). The following sample data provide a comparison of workers with and without health insurance coverage for small, medium, and large companies. For the purposes of this study, small companies are companies that have fewer than 100 employees. Medium companies have 100 to 999 employees, and large companies have 1000 or more employees. Sample data are reported for 50 employees of small companies, 75 employees of medium companies, and 100 employees of large companies.

1. Compute the X²  test statistic:

2. What is the P-Value? (Using a Chi-Square table)

3.What can we conclude?

4. The USA Today article indicated employees of small companies are more likely to lack health insurance coverage. Calculate the percentages of employees without health insurance based on company size (to the nearest whole number).

5. Based on the Calculated percentages, what can we conclude?

The mean cholesterol levels of women age 45-59 in Ghana, Nigeria, and Seychelles is 5.1 mmol/l and the standard deviation is 1.0 mmol/l (Lawes, Hoorn, Law & Rodgers, 2004). Assume that cholesterol levels are normally distributed.

1. Find the probability that a woman age 45-59 in Ghana has a cholesterol level above 6.2 mmol/l (considered a high level).
2. Suppose doctors decide to test the woman’s cholesterol level again and average the two values.  Find the probability that this woman’s mean cholesterol level for the two tests is above 6.2 mmol/l. <----Which two numbers am I averaging?
3. Suppose doctors being very conservative decide to test the woman’s cholesterol level a third time and average the three values.  Find the probability that this woman’s mean cholesterol level for the three tests is above 6.2 mmol/l. <----Not sure which numbers I'm averaging?
4. If the sample mean cholesterol level for this woman after three tests is above 6.2 mmol/l, what could you conclude?

I'm answering these questions using the "normalcdf" function in my TI-84. I'm not sure how to get the new standard deviation/numbers I'm averaging for 2 and 3.

The following information relates to the Ashanti Group of Companies for the year to 30 April 2020.

Additional Information:

Ashanti Ltd purchased 70% of the issued share capital of Bochem Ltd in 2000. At that time, the retained profits of Bochem amounted to $896,000.

Ashant Ltd purchased 60% of the issued share capital of Ceram Ltd in 2004. At that time, the retained profits of Ceram Ltd amounted to $320,000.

Sales from Ashanti to Bochem Ltd were $ 3 million during the post-acquisition period. Ashanti marks up all sales by 20%. At the reporting date this entire inventory remained in Bochem’s warehouse.

REQUIRED:

In so far as the information permits, prepare Fab Group of Companies’ Consolidated Income Statement for the year ended 30 April 2020 in accordance with IFRSs.   

Sachs Brands' defined benefit pension plan specifies annual retirement benefits equal to: 1.2% × service years × final year's salary, payable at the end of each year. Angela Davenport was hired by Sachs at the beginning of 2004 and is expected to retire at the end of 2038 after 35 years' service. Her retirement is expected to span 18 years. Davenport's salary is $80,000 at the end of 2018 and the company's actuary projects her salary to be $230,000 at retirement. The actuary's discount rate is 6%. (FV of $1, PV of $1, FVA of $1, PVA of $1, FVAD of $1 and PVAD of $1) (Use appropriate factor(s) from the tables provided.)

Required:
2. Estimate by the projected benefits approach the amount of Davenport's annual retirement payments earned as of the end of 2018.
3. What is the company's projected benefit obligation at the end of 2018 with respect to Davenport? (Do not round intermediate calculations. Round your final answer to nearest whole dollar.)
4. If no estimates are changed in the meantime, what will be the company's projected benefit obligation at the end of 2021 (three years later) with respect to Davenport? (Do not round intermediate calculations. Round your final answer to nearest whole dollar.)

Sachs Brands' defined benefit pension plan specifies annual retirement benefits equal to: 1.3% × service years × final year's salary, payable at the end of each year. Angela Davenport was hired by Sachs at the beginning of 2004 and is expected to retire at the end of 2038 after 35 years' service. Her retirement is expected to span 18 years. Davenport's salary is $81,000 at the end of 2018 and the company’s actuary projects her salary to be $235,000 at retirement. The actuary's discount rate is 7%. (FV of $1, PV of $1, FVA of $1, PVA of $1, FVAD of $1 and PVAD of $1) (Use appropriate factor(s) from the tables provided.)

Required:

2. Estimate by the accumulated benefits approach the amount of Davenport’s annual retirement payments earned as of the end of 2018.

3. What is the company’s accumulated benefit obligation at the end of 2018 with respect to Davenport? (Do not round intermediate calculations. Round your final answer to nearest whole dollar.)

4. If no estimates are changed in the meantime, what will be the accumulated benefit obligation at the end of 2021 (three years later) when Davenport’s salary is $95,000?

(Do not round intermediate calculations. Round your final answer to nearest whole dollar.)

Suppose the following data were collected relating the selling price of a house to square footage and whether or not the house is made out of wood. Use statistical software to find the regression equation. Is there enough evidence to support the claim that on average wood houses are more expensive than other types of houses at the 0.05 level of significance? If yes, type the regression equation in the spaces provided with answers rounded to two decimal places. Else, select "There is not enough evidence." Selling Prices of Houses Price Sqft Wood (1 if wood, 0 if otherwise) 185821 2004 1 246288 3691 1 224158 2975 1 247893 3339 0 205153 2649 0 168477 1566 0 231917 3324 1 177916 1768 1 201064 2336 1 161010 1386 0 225514 3026 1 222100 3384 0 217999 3119 1 174755 1939 0 210379 2861 0 196333 2400 0 177035 1513 1 171289 1831 0 159158 1763 0 229969 3361 1 Answer How to enter your answer Selecting a checkbox will replace the entered answer value(s) with the checkbox value. If the checkbox is not selected, the entered answer is used

Suppose the following data were collected relating the selling price of a house to square footage and whether or not the house is made out of wood. Use statistical software to find the regression equation. Is there enough evidence to support the claim that on average wood houses are more expensive than other types of houses at the 0.05 level of significance? If yes, type the regression equation in the spaces provided with answers rounded to two decimal places. Else, select "There is not enough evidence." Selling Prices of Houses Price Sqft Wood (1 if wood, 0 if otherwise) 185821 2004 1 246288 3691 1 224158 2975 1 247893 3339 0 205153 2649 0 168477 1566 0 231917 3324 1 177916 1768 1 201064 2336 1 161010 1386 0 225514 3026 1 222100 3384 0 217999 3119 1 174755 1939 0 210379 2861 0 196333 2400 0 177035 1513 1 171289 1831 0 159158 1763 0 229969 3361 1 Answer How to enter your answer Selecting a checkbox will replace the entered answer value(s) with the checkbox value. If the checkbox is not selected, the entered answer is used.