Question #91

of 139 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. Jessica Jenkins, CFA, is looking at the retail property sector for her manager. She is undertaking a top down review as she feels this is the best way to analyze the industry segment. To predict U.S. property starts (housing), she has used regression analysis. Jessica included the following variables in her analysis: Average nominal interest rates during each year (as a decimal) Annual GDP per capita in $'000 Given these variables, the following output was generated from 30 years of data: Exhibit 1 – Results from regressing housing starts (in millions) on interest rates and GDP per capita Coefficient Standard Error T-statistic Intercept Interest rate 0.42 –1.0 3.1 –2.0 GDP per capita 0.03 0.7 ANOVA df SS MSS F Regression 2 3.896 1.948 21.644 Residual 27 2.431 0.090 Total 29 6.327 Observations 30 Durbin-Watson 1.27 Exhibit 2 - Critical Values for F-Distribution at 5% Level of Significance Degrees of Freedom for the Denominator Degrees of Freedom (df) for the Numerator 1 2 3 26 4.23 3.37 2.98 27 4.21 3.35 2.96 28 4.20 3.34 2.95 29 4.18 3.33 2.93 30 4.17 3.32 2.92 31 4.16 3.31 2.91 32 4.15 3.30 2.90 The following variable estimates have been made for 20X7: GDP per capita = $46,700 Interest rate = 7%