A real estate builder wishes to determine how house size is influenced by family income, family size, and education of the head of the household. House size is measured in hundreds of square feet, income is measured in thousands of dollars, and education is in years. The builder randomly selected 50 families and constructed the multiple regression model. The business literature involving human capital shows that education influences an individual's annual income. Combined, these may influence family size. With this in mind, what should the real estate builder be particularly concerned with when analyzing the multiple regression model? a. Collinearity.

b. Missing observations.

c. Randomness of error terms.

d. Normality of residual.

Shelby company produces three products: product x, product y, and product z. data concerning the three products follow (per unit): product x product y product z selling price $ 85 $ 65 $ 75 variable expenses: direct materials 25.50 19.50 5.25 labor and overhead 25.50 29.25 47.25 total variable expenses 51.00 48.75 52.50 contribution margin $ 34.00 $ 16.25 $ 22.50 contribution margin ratio 40 % 25 % 30 % demand for the company’s products is very strong, with far more orders each month than the company can produce with the available raw materials. the same material is used in each product. the material costs $8 per pound, with a maximum of 4,400 pounds available each month. required: a. compute contribution margin per pound of materials used. (round your intermediate calculations and final answers to 2 decimal places.) contribution margin per pound product x $ product y $ product z $ b. which orders would you advise the company to accept first, those for product x, for product y, or for product z? which orders second? third? product x product y product z

Sue now has $125. how much would she have after 8 years if she leaves it invested at 8.5% with annual compounding? a. $205.83b. $216.67c. $228.07d. $240.08e. $252.08

6. why the aggregate supply curve slopes upward in the short run in the short run, the quantity of output that firms supply can deviate from the natural level of output if the actual price level in the economy deviates from the expected price level. several theories explain how this might happen. for example, the misperceptions theory asserts that changes in the price level can temporarily mislead firms about what is happening to their output prices. consider a soybean farmer who expects a price level of 100 in the coming year. if the actual price level turns out to be 90, soybean prices will , and if the farmer mistakenly assumes that the price of soybeans declined relative to other prices of goods and services, she will respond by the quantity of soybeans supplied. if other producers in this economy mistake changes in the price level for changes in their relative prices, the unexpected decrease in the price level causes the quantity of output supplied to the natural level of output in the short run.