aianjie

 

18、Henry Hilton, CFA, is undertaking an analysis of the bicycle industry.  He hypothesizes that bicycle sales (SALES) are a function of three factors: the population under 20 (POP), the level of disposable income (INCOME), and the number of dollars spent on advertising (ADV).  All data are measured in millions of units.  Hilton gathers data for the last 20 years and estimates the following equation (standard errors in parentheses): 

SALES = α + 0.004 POP + 1.031 INCOME + 2.002 ADV
(0.005)	(0.337)	(2.312)

The critical t-statistic for a 95 percent confidence level is 2.120.  Which of the independent variables is statistically different from zero at the 95 percent confidence level?

A)    INCOME and ADV.

B)    POP and ADV.

C)   INCOME only.

D)   ADV only.

aianjie

 

The correct answer is C

The calculated test statistic is coefficient/standard error. Hence, the t-stats are 0.8 for POP, 3.059 for INCOME, and 0.866 for ADV. Since the t-stat for INCOME is the only one greater than the critical t-value of 2.120, only INCOME is significantly different from zero.

 

aianjie

 

19、Henry Hilton, CFA, is undertaking an analysis of the bicycle industry.  He hypothesizes that bicycle sales (SALES) are a function of three factors: the population under 20 (POP), the level of disposable income (INCOME), and the number of dollars spent on advertising (ADV).  All data are measured in millions of units.  Hilton gathers data for the last 20 years and estimates the following equation (standard errors in parentheses):

SALES = 0.000  +  0.004 POP + 1.031 INCOME + 2.002 ADV
(0.113)	(0.005)	(0.337)	(2.312)

For next year, Hilton estimates the following parameters: (1) the population under 20 will be 120 million, (2) disposable income will be $300,000,000, and (3) advertising expenditures will be $100,000,000.  Based on these estimates and the regression equation, what are predicted sales for the industry for next year?

A)    $557,143,000.

B)    $509,980,000.

C)   $656,991,000.

D)   $669,471,000.

aianjie

 

The correct answer is C

Predicted sales = $10 + 1.25 + 1 – 10 + 16 = $18.25 million.

 

aianjie

 

17、Henry Hilton, CFA, is undertaking an analysis of the bicycle industry. He hypothesizes that bicycle sales (SALES) are a function of three factors: the population under 20 (POP), the level of disposable income (INCOME), and the number of dollars spent on advertising (ADV). All data are measured in millions of units. Hilton gathers data for the last 20 years. Which of the follow regression equations correctly represents Hilton’s hypothesis?

A) SALES = α x β1 POP x β2 INCOME x β3 ADV x ε.

B) INCOME = α + β1 POP + β2 SALES + β3 ADV + ε.

C) SALES = α + β1 POP + β2 INCOME + β3 ADV + ε.

D) INCOME = α + β1 POP + β2 ADV + ε.

aianjie

 

The correct answer is C

SALES is the dependent variable. POP, INCOME, and ADV should be the independent variables (on the right hand side) of the equation (in any order). Regression equations are additive.

 

aianjie

 

15、Consider the following regression equation:

Salesi = 20.5 + 1.5 R&Di + 2.5 ADVi – 3.0 COMPi

where Sales is dollar sales in millions, R&D is research and development expenditures in millions, ADV is dollar amount spent on advertising in millions, and COMP is the number of competitors in the industry.

Which of the following is NOT a correct interpretation of this regression information?

A) If a company spends $1 more on R&D (holding everything else constant), sales are expected to increase by $1.5 million.

B) If R&D and advertising expenditures are $1 million each and there are 5 competitors, expected sales are $9.5 million.

C) One more competitor will mean $3 million less in sales (holding everything else constant).

D) Increasing advertising dollars by $1 million (holding everything else constant), will result in $2.5 million additional sales.

aianjie

 

The correct answer is A

If a company spends $1 million more on R&D (holding everything else constant), sales are expected to increase by $1.5 million. Always be aware of the units of measure for the different variables.

 

aianjie

 

16、Consider the following regression equation:

Salesi = 10.0 + 1.25 R&Di + 1.0 ADVi – 2.0 COMPi + 8.0 CAPi

where Sales is dollar sales in millions, R&D is research and development expenditures in millions, ADV is dollar amount spent on advertising in millions, COMP is the number of competitors in the industry, and CAP is the capital expenditures for the period in millions of dollars.

Which of the following is NOT a correct interpretation of this regression information?

A) If a company spends $1 million more on capital expenditures (holding everything else constant), Sales are expected to increase by $8.0 million.

B) One more competitor will mean $2 million less in Sales (holding everything else constant).

C) If R&D and advertising expenditures are $1 million each, there are 5 competitors, and capital expenditures are $2 million, expected Sales are $8.25 million.

D) Increasing advertising dollars by $1 million (holding everything else constant), will result in $1 million additional Sales.

aianjie

 

14、Baltz then tests the individual variables, at a 5% level of significance, to determine whether sales are explained by individual changes in GDP and fuel prices. Baltz concludes that:

A) neither GDP nor fuel price changes explain changes in sales.

B) only GDP changes explain changes in sales.

C) both GDP and fuel price changes explain changes in sales.

D) only fuel price changes explain changes in sales.