Question 1: Opportunity cost is best defined as
A. the amount given up when choosing one activity over all other alternatives
B. the amount given up when choosing one activity over the next best alternative
C. the opportunity to earn a profit that is greater than the one currently being made
D. the amount that is given up when choosing an activity that is not as good as the next best alternative
Question 2: Which of the following is NOT a non-price determinant of demand?
A. tastes and preferences
B. income
C. technology
D. future expectations
Question 3: Which of the following will NOT cause a short run shift in the supply curve?
A. a change in the number of sellers
B. a change in the cost of resources
C. a change in the price of the product
D. a change in future expectations
Question 4: The sensitivity of the change in quantity consumed of one product to a change in the price of a related product is called
A. cross-elasticity
B. substitute elasticity
C. complementary elasticity
D. price elasticity of demand
Question 5: The t-statistic is computed by
A. dividing the regression coefficient by the standard error of the estimate
B. dividing the regression coefficient by the standard error of the coefficient
C. dividing the standard error of the coefficient by the regression coefficient
D. dividing the R2 by the F-Statistic
Question 6: The forecasting technique, which predicts technological trends and is carried out by a sequential series of written questions and answers is
A. the Delphi method
B. the market research method
C. opinion polling
D. the jury of executive opinion approach
Question 7: If the income elasticity of a particular product is -0.2, it would be considered
A. a superior good
B. a normal good
C. an inferior good
D. an elastic good
Question 8: If a regression coefficient passes the t-test, it means that ( the regression equation is valid
A. the regression coefficient is significantly different from zero
B. the regression coefficient can be used for forecasting
C. the regression coefficient should be included in the regression equation
Question 9: Which of the following refers to a relatively high correlation among the independent variables of a regression equation?
A. autocorrelation
B. the identity problem
C. statstically insignificant regression coefficients
D. multicollinearity