Which of the following are used to test for the statistical significance or explanatory power of an individual variable?

Which of the following are used to test the statistical significance and explanatory power of all the independent

1. Which of the following are used to test for the statistical significance or explanatory power of an individual variable?

A) t-statistic

B) p-value

C) t-statistic and p-value

D) R-squared

E) F-statistic

F) R-squared and F-statistic

2. Which of the following are used to test the statistical significance and explanatory power of all the independent variables together (i.e., the explanatory power of the model)?

A) t-statistic

B) p-value

C) t-stastistic and p-value

D) R-squared

E) F-statistic

F) R-squared and F-statistic

3.Which should be used to determine if an individual variable should be added to the regression model?

A) Economic, business or physical theory.

B) The t-statistic and p-value of the variable coefficient.

C) The correlation with other variables included in the model.

D) All of the above.

4.Suppose you have a regression model that depicts the relationship between costs in dollars (C) and the machine hours(H) such that log(C) = 10 + 2(logH). Which of the following is the correct interpretation of the machine hours coefficient?

A) A 1 hour increase in machine use will increase costs by $2.

B) A 1 increase in costs will occur if there is a 2 hour increase in machine use.

C) A 1% increase in machine hours will increase costs 2%.

D) A 1% increase in costs will result from a 2% increase in machine hours.

5.Which of the following is NOT likely to occur when multicollinearity exists in a model?

A) Inflated Adjusted R-squared

B) High correlation between a pair or pairs of variables.

C) A variance inflation factor (VIF) > 5.

D) Theoretically important variables having coefficients that are statistically insignificant.

For this question, none of the options is right. (All the options are true in a model with multicollinearity)

8.2.1: An analyst is evaluating the demand for building and construction materials relative to the cost of borrowing or the mortgage rate in Los Angeles and San Francisco. He believes that the following model is appropriate: Y = 10 + 5X1 + 8X2, where Y is demand in $100 per capita; X1 is mortgage rate in %, and X2 equals 1 if SF, 0 if LA.

6.Given the information in 8.2.1, each additional increase of 1% in the mortgage rate will lead to an estimated average _________________ in demand for building materials, holding constant the effect of city.

A) Increase of $500 per capita.

B) Decrease of $500 per capita.

C) Increase of $5 per capita.

D) Decrease of $5 per capita.

7.Using the model in 8.2.1, the interpretation of the coefficient for X2 is: Holding constant the effect of mortgage rates,

A) Demand for building materials is $800 more per capita in SF than in LA.

B) Demand for building materials is $800 more per capita in LA than SF.

C) Demand for building materials is $8 more per capita in LA than in SF.

D) Demand for building materials is $8 more per capita in SF than in LA.

8.2.2: Advanced Technology Corporation (ATC) manufactures a home computer system and has hired a market research team to analyze the potential demand for this product using historical data on sales of similar products in 66 regions of the country in conjunction with information from consumer surveys. The research firm estimated the following demand function: Q = -36,000 – 10P + 2Px + 300I + 24A – 0.01Asquared, where Q=annual demand in units, P=price of ATC computer ($), Px=price of ATC major competitor computer ($), I = average family disposable income ($100), and A = advertising by ATC ($100).

8.Using situation 8.2.2, the correct interpretation of the coefficient for Px (i.e., +2) is:

A) An increase of computer sales of one unit will occur if there is a $2 increase in the price of the competitor’s computer holding constant P, I, and A.

B) An increase of computer sales of one unit will occur if there is a $200 increase in the price of the competitor computer, holding constant P, I, and A.

C) A $1 increase in the price of the competitor’s computer will increase ATC computer sales by 2 units, holding constant P, I, and A.

D) A $1 increase in the price of the competitor’s computer will increase ATC computer sales by 200 units, holding constant P, I and A.

9.Suppose you review the information in situation 8.2.2 and plan to test the explanatory power of: 1. the overall model and 2. a one-tail test of the individual coefficients, both at the .05 level of significance, then what critical values would you use for your tests? The first answer refers to tests for the model; the second answer refers to the test for the individual variable coefficient.

A) F=2.37 and t=1.671

B) t=1.671 and F=2.37.

C) F=2.25 and t=1.671

D) t=2.00 and F=2.37.

For this question, none of the options is right. (The correct answer is F = 2.52 and t = 1.671)

10.Using situation 8.2.2, what would happen to computer sales if ATC increased the advertising budget by $1000 (check units of measurement before you start to answer)?

A) Sales would increase by approximately 240 units.

B) Sales would increase by approximately 241 units.

C) Sales would increase by approximately 24,000 units.

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