Exam 5: Demand Estimation and Forecasting Appendices 5A and 5B

When a regression coefficient is significant at the .05 level,it means that

From a management policy perspective,which regression result is the most useful?

One of the series included among the lagging indicators is

$\text {The following questions refer to this regression equation, (standard errors in parentheses.)}$ $\mathrm { Q } = 8,400 - 10 \mathrm { P } + 5 \mathrm {~A} + 4 \mathrm { Px } + 0.05 \mathrm { I } , ( 1,732 ) ( 2.29 ) ( 1.36 ) ( 1.75 ) 0.15 )$ =0.65 =120 =35.25 $\text {Standard error of estimate = 34.3}$ $\text {Q = Quantity demanded}$ \text {\mathrm { P } = Price \(= 1,000\)} \text {\mathrm { A } = Advertising expenditures, in thousands \(= 40\)} \text {\mathrm { PX } = price of competitor's good \(= 800\)} \text {\mathrm { I } = average monthly income \(= 4,000\)} -How is the R² value calculated,and what information does this give you?

R² is a statistical measure which

The t-test is a statistical measure which

$\mathrm { Q } = - 6,500 - 100 \mathrm { P } _ { \mathrm { A } } + 50 \mathrm {~PB} + .3 \mathrm { I } + .2 \mathrm {~A} ; \mathrm { R } ^ { 2 } = .12 , ( 2,500 ) ( 50 ) ( 30 ) ( .1 ) ( .08 )$ $\text {where Q is the quantity demanded of good \(A ; P A = \$ 10\), price of good \(A ; P _ { B } = \$ 8\), price of good }$ $\text {B ; I = \$ 12,000, per capita income; and \(A = \$ 20,000\), monthly advertising expenditures.}$ -Which of the following cannot be determined on the basis of the above regression results?

Average weekly claims for unemployment insurance,money supply and the index of stock prices are all examples of

based on the following regression equation (Standard errors in parentheses, n = 150): Q_D = 1000 - 50P_A + 10P_B + .05I, (20) (7) (.04) where Q_D = quantity demanded of good A, P_A = price of good A, P_B = price of a competing good B, and I = per capita income. -For which of the following variables should a "two tail" t-test be applied?

How could a manager use the information contained in this regression equation?

A major problem in projecting with a trend line is that

When using regression analysis for forecasting,the confidence interval indicates

How would you evaluate the quality of this equation overall? Do you have any concerns? Explain.

Which of the following is not one of the leading indicators?

The coefficient of a linear regression equation indicates

A manager will have the least confidence in an explanatory variable that

The demand equation for the Widget Company has been estimated to be: Q = 20,000 + 10 I - 50P + 20 P_C where Q = monthly number of widgets sold,I = average monthly income,P = price of widgets,and P_C = average price of competing goods. a.If next month's income is forecast to be 2,000,the price of competing goods is forecast to be $20,and the price of widgets will be set at $30,forecast sales. b.What will sales be if the price is dropped to $20?

Which of the following is the exponential trend equation to forecast sales (S)?

$\text {The following questions refer to this regression equation, (standard errors in parentheses.)}$ $\mathrm { Q } = 8,400 - 10 \mathrm { P } + 5 \mathrm {~A} + 4 \mathrm { Px } + 0.05 \mathrm { I } , ( 1,732 ) ( 2.29 ) ( 1.36 ) ( 1.75 ) 0.15 )$ =0.65 =120 =35.25 $\text {Standard error of estimate = 34.3}$ $\text {Q = Quantity demanded}$ \text {\mathrm { P } = Price \(= 1,000\)} \text {\mathrm { A } = Advertising expenditures, in thousands \(= 40\)} \text {\mathrm { PX } = price of competitor's good \(= 800\)} \text {\mathrm { I } = average monthly income \(= 4,000\)} -Calculate t-statistics for each variable and explain what this tells you.

If a regression coefficient passes the t-test,it means that