Lenny's,a national restaurant chain,conducted a study of the factors affecting demand (sales).The following variables were defined and measured for a random sample of 30 of its restaurants: \[\begin{array} { l l } \mathrm { Y } & = \text { Annual restaurant sales ( } \$ 000 ) \\ \mathrm { X } _ { 1 } & = \text { Disposable personal income (per capita) of residents within } 5 \text { mile radius } \\ \mathrm { X } _ { 2 } & = \text { License to sell beer/wine } ( 0 = \text { No, } 1 = \mathrm { Yes } ) \\ \mathrm { X } _ { 3 } & = \text { Location (within one-half mile of interstate highway- } 0 = \text { No, } 1 = \text { Yes) } \\ \mathrm { X } _ { 4 } & = \text { Population (within } 5 \text { mile radius) } \\ \mathrm { X } _ { 5 } & = \text { Number of competing restaurants within } 2 \text { mile radius } \end{array}\] The data were entered into a computerized regression program and the following results were obtained: \[\begin{array} { l l } \text { MULTIPLE R } & .889 \\ \text { R-SQUARE } & .79 \\ \text { STD. ERROR OF EST. } & .40 \end{array}\] ANALYSIS OF VARIANCE $\begin{array}{lrrrr} & \text { DF } & \text { Sum Squares } & \text { Mean Sqr. } & \text { F-Stat } \\ \hline \text { Regression } & 5 & 326.13 & 65.226 & 18.17 \\ \text { Error } & 24 & 86.17 & 3.590 & \\ \text { Total } & 29 & 412.30 & & \end{array}$ $\begin{array}{lccr} \text { Variable } & \text { Coefficient } & \text { Std. Error } & \text { T-Value } \\ \text { Constant } & .363 & .196 & 1.852 \\ \mathrm{X}-1 & .00275 & .00104 & 2.644 \\ \mathrm{X}-2 & 76.65 & 93.70 & .818 \\ \mathrm{X}-3 & 164.3 & 235.4 & .698 \\ \mathrm{X}-4 & .00331 & .00126 & 2.627 \\ \mathrm{X}-5 & 46.2 & 12.1 & -3.818 \end{array}$ Questions: (a) Give the regression equation for predicting restaurant sales. (b) Give an interpretation of each of the estimated regression coefficients. (c) Which of the independent variables (if any) are statistically significant at the .05 level in (c) "explaining" restaurant sales? (d) What proportion of the variation in restaurant sales is "explained" by the regression equation? (e) Perform an F-test (at the 05 significance level) of the overall explanatory power of the regression model.

The answer of Lenny's,a national restaurant chain,conducted a study of...

Even though insignificant explanatory variables can raise the adjusted R2 of a demand function,one should not interpret their effects on the regression when

A) testing marketing hypotheses about the determinants of demand B) analyzing inventory relative to capacity requirements C) forecasting unit sales for operations planning D) sales revenue reaches its peak E) planning for capital budgets A) testing marketing hypotheses about the determinants of demand B) analyzing inventory relative to capacity requirements C) forecasting unit sales for operations planning D) sales revenue reaches its peak E) planning for capital budgets

In a cross section regression of 48 states,the following linear demand for per-capita cans of soda was found: Cans = 159.17 - 102.56 Price + 1.00 Income + 3.94Temp \[\begin{array} { l r r r } \hline & \text { Coeffcients}& \text { Standard Error } & t \text { Stat } \\ \hline \text { Intercept } & 159.17 & 94.16 & 1.69 \\ \text {Price } & - 102.56 & 33.25 & - 3.08 \\ \text { Income } & 1.00 & 1.77 & 0.57 \\ \text { Temperature } & 3.94 & 0.82 & 4.83 \\ \hline \end{array}\] $\mathrm { R } - \mathrm { Sq } = 54.1 \% \quad \mathrm { R } - \mathrm { Sq } ( \mathrm { adj } ) = 51.0 \%$ From the linear regression results in the cans case above, we know that:

A) Price is insignificant B) Income is significant C) Temp is significant D) As price rises for soda,people tend to drink less of it E) All of the coefficients are significant A) Price is insignificant B) Income is significant C) Temp is significant D) As price rises for soda,people tend to drink less of it E) All of the coefficients are significant

Exam 4: Estimating Demand

Lenny's,a national restaurant chain,conducted a study of the factors affecting demand (sales).The following variables were defined and measured for a random sample of 30 of its restaurants: = Annual restaurant sales ( \ 000) = Disposable personal income (per capita) of residents within 5 mile radius = License to sell beer/wine (0= No, 1=) = Location (within one-half mile of interstate highway- 0= No, 1= Yes) = Population (within 5 mile radius) = Number of competing restaurants within 2 mile radius The data were entered into a computerized regression program and the following results were obtained: MULTIPLE R .889 R-SQUARE .79 STD. ERROR OF EST. .40 ANALYSIS OF VARIANCE DF Sum Squares Mean Sqr. F-Stat Regression 5 326.13 65.226 18.17 Error 24 86.17 3.590 Total 29 412.30 Variable Coefficient Std. Error T-Value Constant .363 .196 1.852 -1 .00275 .00104 2.644 -2 76.65 93.70 .818 -3 164.3 235.4 .698 -4 .00331 .00126 2.627 -5 46.2 12.1 -3.818 Questions: (a) Give the regression equation for predicting restaurant sales. (b) Give an interpretation of each of the estimated regression coefficients. (c) Which of the independent variables (if any) are statistically significant at the .05 level in (c) "explaining" restaurant sales? (d) What proportion of the variation in restaurant sales is "explained" by the regression equation? (e) Perform an F-test (at the 05 significance level) of the overall explanatory power of the regression model.

(Essay)

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Question 21

Even though insignificant explanatory variables can raise the adjusted R² of a demand function,one should not interpret their effects on the regression when

(Multiple Choice)

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Question 22

The principal econometric techniques used in measuring demand relationships are:

(Multiple Choice)

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Question 23

In regression analysis,the existence of a high degree of intercorrelation among some or all of the explanatory variables in the regression equation constitutes:

(Multiple Choice)

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Question 24

One commonly used test in checking for the presence of autocorrelation when working with time series data is the ____.

(Multiple Choice)

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Question 25

When using a multiplicative power function (Y = a X₁^b1X₂^b2X₃^b3)to represent an economic relationship,estimates of the parameters (a,and the b's)using linear regression analysis can be obtained by first applying a ____ transformation to convert the function to a linear relationship.

(Multiple Choice)

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Question 26

In a cross section regression of 48 states,the following linear demand for per-capita cans of soda was found: Cans = 159.17 - 102.56 Price + 1.00 Income + 3.94Temp Coeffcients Standard Error t Stat Intercept 159.17 94.16 1.69 Price -102.56 33.25 -3.08 Income 1.00 1.77 0.57 Temperature 3.94 0.82 4.83 $\mathrm { R } - \mathrm { Sq } = 54.1 \% \quad \mathrm { R } - \mathrm { Sq } ( \mathrm { adj } ) = 51.0 \%$ From the linear regression results in the cans case above, we know that:

(Multiple Choice)

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Question 27

When two or more "independent" variables are highly correlated,then we have:

(Multiple Choice)

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Question 28

The standard deviation of the error terms in an estimated regression equation is known as:

(Multiple Choice)

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Question 29

The estimated slope coefficient (b)of the regression equation (Ln Y = a + b Ln X)measures the change in Y for a one change in X.

(Multiple Choice)

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Question 30

The coefficient of determination ranges in value between 0.0 and 1.0.

(True/False)

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Question 31

Even though insignificant explanatory variables can raise the adjusted R² of a demand function,one should not interpret their effects on the regression when

The principal econometric techniques used in measuring demand relationships are:

In regression analysis,the existence of a high degree of intercorrelation among some or all of the explanatory variables in the regression equation constitutes:

One commonly used test in checking for the presence of autocorrelation when working with time series data is the ____.

When using a multiplicative power function (Y = a X₁^b1X₂^b2X₃^b3)to represent an economic relationship,estimates of the parameters (a,and the b's)using linear regression analysis can be obtained by first applying a ____ transformation to convert the function to a linear relationship.

When two or more "independent" variables are highly correlated,then we have:

The standard deviation of the error terms in an estimated regression equation is known as:

The estimated slope coefficient (b)of the regression equation (Ln Y = a + b Ln X)measures the change in Y for a one change in X.

The coefficient of determination ranges in value between 0.0 and 1.0.

Introduction and Goals of the Firm

Fundamental Economic Concepts

Demand Analysis

Business and Economic Forecasting

Managing in the Global Economy

Production Economics

Cost Analysis

Applications of Cost Theory

Prices,output,and Strategy: Pure and Monopolistic Competition

Price and Output Determination: Monopoly and Dominant Firms

Price and Output Determination: Oligopoly

Best-Practice Tactics: Game Theory

Pricing Techniques and Analysis

Contracting,governance,and Organizational Form

Government Regulation

Long-Term Investment Analysis

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Exam 4: Estimating Demand

Even though insignificant explanatory variables can raise the adjusted R2 of a demand function,one should not interpret their effects on the regression when

The principal econometric techniques used in measuring demand relationships are:

In regression analysis,the existence of a high degree of intercorrelation among some or all of the explanatory variables in the regression equation constitutes:

One commonly used test in checking for the presence of autocorrelation when working with time series data is the ____.

When using a multiplicative power function (Y = a X1b1X2b2X3b3)to represent an economic relationship,estimates of the parameters (a,and the b's)using linear regression analysis can be obtained by first applying a ____ transformation to convert the function to a linear relationship.

When two or more "independent" variables are highly correlated,then we have:

The standard deviation of the error terms in an estimated regression equation is known as:

The estimated slope coefficient (b)of the regression equation (Ln Y = a + b Ln X)measures the ____ change in Y for a one ____ change in X.

The coefficient of determination ranges in value between 0.0 and 1.0.

Introduction and Goals of the Firm

Fundamental Economic Concepts

Demand Analysis

Business and Economic Forecasting

Managing in the Global Economy

Production Economics

Cost Analysis

Applications of Cost Theory

Prices,output,and Strategy: Pure and Monopolistic Competition

Price and Output Determination: Monopoly and Dominant Firms

Price and Output Determination: Oligopoly

Best-Practice Tactics: Game Theory

Pricing Techniques and Analysis

Contracting,governance,and Organizational Form

Government Regulation

Long-Term Investment Analysis

Filters

Even though insignificant explanatory variables can raise the adjusted R² of a demand function,one should not interpret their effects on the regression when

When using a multiplicative power function (Y = a X₁^b1X₂^b2X₃^b3)to represent an economic relationship,estimates of the parameters (a,and the b's)using linear regression analysis can be obtained by first applying a ____ transformation to convert the function to a linear relationship.

The estimated slope coefficient (b)of the regression equation (Ln Y = a + b Ln X)measures the change in Y for a one change in X.