A hypothetical data shows that, in a year, of all the adult population, 20,500,000 were employed, 755,000 were unemployed, 45,000 were workers with part-time jobs looking for full-time jobs, 25,000 were discouraged workers and 8,500,000 were not in the labor force.

1. Use the above information and calculate the labor force participation rate and the unemployment rate.
2. Suppose that the natural rate of unemployment is 1.5 percent and the potential GDP is RM 850 billion, how much would be the actual GDP achieved in the above case?
3. Suppose that 2,500,000 students graduated from higher education institutions and begin to look for jobs. Ceteris paribus, determine the new unemployment rate if none of the students have found jobs yet. How this will change your answer in (b)?
4. Now suppose that 1,500,000 of the students whom graduated in (c) find jobs and the remaining are not yet employed. Ceteris paribus, determine the new unemployment rate. Clearly show your working for all calculations.
5. Simulate a scenario in which both employment and unemployment could both possibly increase.

As part of an educational experiment a sample of sixteen Year 3 children was randomly divided into two groups, each of size eight.
The first group of eight children was taught arithmetic by the use of traditional procedures, whilst the second group of eight was taught arithmetic by newer modern methods.
At the end of the year all 16 children sat for an arithmetic achievement test, and also an arithmetic understanding test.
The marks(out of 100) obtained by the children are shown in the following tables.

In answering the following questions you may assume that both achievement marks and understanding marks are normally distributed.

1. To test whether there is a significant difference between the mean Achievement mark and the mean Understanding mark of children taught by the Modern method we would carry out ( A. A paired t test B. A two sample t test)

2. To test whether there is a significant difference between the mean Achievement marks of children taught by the Traditional method and of children taught by the Modern method.  (A. A paired t test B. A two sample t test)

3. To test whether there is a significant difference between the mean Achievement mark and the mean Understanding mark of children taught by the Traditional method we would carry out . (A. A paired t test B. A two sample t test)

4. To test whether there is a significant difference between the mean Understanding marks of children taught by the Traditional method and of children taught by the Modern method. (A. A paired t test B. A two sample t test)

The average fee in a private school in Georgia is more than $13,000 for one year with σ = $3000. Assume the population is normally distributed. A random sample of 15 private schools in Georgia yielded a mean yearly fee of $14,500. Test using the critical value method if the population mean of the yearly fee in a private school in Georgia is more than $13,000, using α = 0.10.

The balance sheet for Bryan Corporation is given below. Sales for the year were $3,190,000, with 75 percent of sales sold on credit.

Compute the following ratios: (Use 365 days in a year. Do not round intermediate calculation. Round the final answers to 2 decimal places.)

Personal Budget

At the beginning of the school year, Craig Kovar decided to prepare a cash budget for the months of September, October, November, and December. The budget must plan for enough cash on December 31 to pay the spring semester tuition, which is the same as the fall tuition. The following information relates to the budget:

a. Prepare a cash budget for September, October, November, and December. Use the minus sign to indicate cash outflows, a decrease in cash or cash payments.

b. What are the budget implications for Craig Kovar?

Craig can see that his present plan will not provide  sufficient cash. If Craig did not budget but went ahead with the original plan, he would be $__________ short  at the end of December, with no time left to adjust.

In 2001, a 3-year old boy was admitted to hospital in Mt Isa, Queensland with a two-day history of an acute febrile illness and convulsions. He remained febrile over the following two days. He had further brief seizures and then developed a left hemiparesis (paralysis of one side of the body), agitation and confusion, and subsequently became comatose. He was commenced on broad spectrum antibiotics and acyclovir. Two months later he had persisting major neurological sequelae, and remained semi-comatose with a spastic quadriplegia. In a provisional diagnosis of acute encephalitis, what viral etiologic agent is likely?

Select one:

a. Japanese encephalitis virus.

b. West Nile encephalitis virus.

c. St Louis encephalitis virus.

d. Murray Valley encephalitis virus.

Consider a 30-year mortgage for $137018 at an annual interest rate of 3.9%. What is the remaining balance after 19 years? Round your answer to the nearest dollar.

The WalMart’s fiscal year starts the first week of February. This means that when analyzing the data, week 26 is actually week 30 (26+4 weeks for January) in 2002 or the end of July 2002. Also, week 52 is actually week 4 (52+4 weeks for January 2002 minus 52 weeks for 2002) in 2003 or the end of January 2003. As an example, the spike in sales (revenue) at week 75 occurs in week 27 (75+4 weeks for January 2002 minus 52 weeks for 2002) in 2003 or the first week in July 2003. This corresponds to sales for the July 4th holiday when people are buying barbecue related items. Please use excel.

Identify spikes (outliers) in the data where extreme sales values occur and correlate these spikes with actual calendar dates in 2002 or 2003 and with holidays or special events that may occur during these periods.

1. Modeling the data linearly - a. Generate a linear model for this data by choosing two points.

b. Generate a least squares linear regression model for this data.

c. How good is this regression model? Output and discuss the R² value.

d. What are the marginal sales (derivative, i.e. rate of change) for this department using the linear model with two data points and the regression model?

e. Compare the two models. Which do you feel is better?

f. Remove appropriate outliers as you deem necessary and rerun the linear regression model. What is the marginal sales and discuss improvements.

2. Modeling the data quadratically - a. Generate a quadratic model for this data. Also output and discuss the R² value.

b. What are the marginal sales for this department using this model?

c. Calculate the model generated relative max/min value. Show backup analytical work.

d. Compare actual and model generated relative max/min value.

e. Remove outliers and rerun the quadratic least squares model. What is the marginal sales and discuss improvements.

3. Comparing models - a. Based on all models run, which model do you feel best predicts future trends? Explain your rationale.

b. Based on the model selected, what type of seasonal adjustments, if any, would be required to meet customer needs?

The WalMart’s fiscal year starts the first week of February. This means that when analyzing the data, week 26 is actually week 30 (26+4 weeks for January) in 2002 or the end of July 2002. Also, week 52 is actually week 4 (52+4 weeks for January 2002 minus 52 weeks for 2002) in 2003 or the end of January 2003. As an example, the spike in sales (revenue) at week 75 occurs in week 27 (75+4 weeks for January 2002 minus 52 weeks for 2002) in 2003 or the first week in July 2003. This corresponds to sales for the July 4th holiday when people are buying barbecue related items. Please use excel.

Identify spikes (outliers) in the data where extreme sales values occur and correlate these spikes with actual calendar dates in 2002 or 2003 and with holidays or special events that may occur during these periods.

1. Modeling the data linearly - a. Generate a linear model for this data by choosing two points.

b. Generate a least squares linear regression model for this data.

c. How good is this regression model? Output and discuss the R² value.

d. What are the marginal sales (derivative, i.e. rate of change) for this department using the linear model with two data points and the regression model?

e. Compare the two models. Which do you feel is better?

f. Remove appropriate outliers as you deem necessary and rerun the linear regression model. What is the marginal sales and discuss improvements.

2. Modeling the data quadratically - a. Generate a quadratic model for this data. Also output and discuss the R² value.

b. What are the marginal sales for this department using this model?

c. Calculate the model generated relative max/min value. Show backup analytical work.

d. Compare actual and model generated relative max/min value.

e. Remove outliers and rerun the quadratic least squares model. What is the marginal sales and discuss improvements.

3. Comparing models - a. Based on all models run, which model do you feel best predicts future trends? Explain your rationale.

b. Based on the model selected, what type of seasonal adjustments, if any, would be required to meet customer needs?