1.Suppose the Sunglasses Hut Company's profit is given by the equation P=-0.02q²+3q-32,where P is the total profit, in thousands of dollars, and q is the total number of sunglasses sold, in thousands. For example, when q=10, the equation says that P=-4. This would mean that when 10000 sunglasses are sold, the profit is $-4000.

How many pairs of sunglasses (in thousands) should be sold to maximize profits? What are the actual maximum profits (in thousands) that can be expected?

2.Explain if larger GDP is always better than smaller GDP

3.Suppose GDP is $6 trillion in 1 and $6.2T in year 2.What has caused the rise in GDP

4.What are the advantages of 2nd and 3rd generation panel data techniques over the 1st gen techniques

5.What kind of stability tests to report?

6.Can the academic research in applied economics help improve public administration of public health services in Latin American countries

7.if you paid $89 to a loan company for the use of $1075 for 82 days, what annual rate of interest did they charge?

8.The profit in dollars of the sale of x expensive watches is P(x)=0.03x^2-3x-6x^0.4-4000. Find for x=400, x=2000,x=5000, x=10000

9.Using properly labelled diagrams illustrate what will happen to the equilibrium price and quantity of muesli (ceteris paribus), in the following scenarios

Research has shown that muesli is good for the heart

The ongoing drought has affected grain (one of the ingredients for muesli) production.

10.The owner of an ice cream shop wants to determine whether there is a relationship between ice cream sales and temperature. The owner collects data on temperature and sales for a random sample of 30 days and runs a regression to determine if there is a relationship between temperature (in degrees) and ice cream sales. The p-value for the two-sided hypothesis test is 0.04. How would you interpret the p-value?

If there is no relationship between temperature and sales, the chance of selecting a sample this extreme would be 4%.

If there is a relationship between temperature and sales, the chance of seeing a regression coefficient this large would be 4%.