You have estimated the following simple regression model y = 379 + 1.44 x3 What is the elasticity when x = 8.49?

A) 263.19 B) 311.39 C) 2.10 D) -24.7 A) 263.19 B) 311.39 C) 2.10 D) -24.7

You have estimated the following simple regression model y = 379 + 1.44 x3 What does this model predict y to be when x = 8.49?

A) 415.68 B) 690.39 C) 1260.22 D) 2205.47 A) 415.68 B) 690.39 C) 1260.22 D) 2205.47

At what values of x0 will the standard error of the forecast be smallest?

A) x0 = 0 B) x0 =x̅ C) x02 = $\sigma$2 D) x0 = tc se(f) A) x0 = 0 B) x0 =x̅ C) x02 = $\sigma$2 D) x0 = tc se(f)

Exam 5: Prediction, Goodness-Of-Fit and Modeling Issues

While working with the sales manager of your firm you have estimated the following model of sales volume as a function of monthly household income: (0.781)(0.392) Where Q is monthly sales volume,I is monthly household income in thousands,and standard errors are listed below the parameter estimates. What is the income elasticity of your firm's product?

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Question 1

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What is the skewness of the normal distribution?

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Question 2

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When the residuals from a simple regression model appear to be correlated with x,this is known as_______________________________.

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Question 3

Correct Answer:

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Heteroskedasticity

You have estimated a model of two variables related such that ln(y)= 17.3 - .04 x If x decreases by 2 units,what is the expected change in y?

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Question 4

If a scatter plot of the data reveals an inverted U shape,what data transformation would allow it to be estimated with simple linear regression?

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Question 5

A measure of the symmetry of a distribution is ________________________.

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Question 6

You have estimated the following simple regression model y = 379 + 1.44 x³ What is the elasticity when x = 8.49?

(Multiple Choice)

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Question 7

When should a researcher consider transforming the explanatory variable in the simple linear regression model?

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Question 8

You have estimated a regression model and your printout includes the following information s_xy= 3614.00 S_x = 12.72 S_y = 394.61 SST = 758912.00. What is R² for this regression model?

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Question 9

What about the distribution of a random variable does kurtosis measure?

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Question 10

You have estimated the following simple regression model y = 379 + 1.44 x³ What does this model predict y to be when x = 8.49?

(Multiple Choice)

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Question 11

You have estimated a regression model and your printout includes the following information s_xy= 3614.00 S_x = 12.72 S_y = 394.61 SST = 758912.00. Use this information to calculate SSE.

(Multiple Choice)

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Question 12

Which of the following leads to large forecast errors?

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Question 13

When should a researcher consider transforming the explanatory variable in a simple linear regression model?

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Question 14

What hypothesis is tested when using the Jarque-Berra test ?

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Question 15

At what values of x₀ will the standard error of the forecast be smallest?

(Multiple Choice)

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Question 16

What does R2,the coefficient of determination,measure?

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Question 17

Which of the following will change if you scale the dependent variable in a simple regression model?

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Question 18

Which of the following expressions is NOT equal to Ʃ(y_i - y̅)² ?

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Question 19

While working with the sales manager of your firm you have estimated the following model of sales volume as a function of monthly household income: (0.781)(0.392) Where Q is monthly sales volume,I is monthly household income in thousands,and standard errors are listed below the parameter estimates. What does the model predict sales volume to be if using the corrected predictor when income is $4000 per month?

(Multiple Choice)

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Question 20

Showing 1 - 20 of 20

What is the skewness of the normal distribution?

When the residuals from a simple regression model appear to be correlated with x,this is known as_______________________________.

You have estimated a model of two variables related such that ln(y)= 17.3 - .04 x If x decreases by 2 units,what is the expected change in y?

If a scatter plot of the data reveals an inverted U shape,what data transformation would allow it to be estimated with simple linear regression?

A measure of the symmetry of a distribution is ________________________.

You have estimated the following simple regression model y = 379 + 1.44 x³ What is the elasticity when x = 8.49?

When should a researcher consider transforming the explanatory variable in the simple linear regression model?

You have estimated a regression model and your printout includes the following information s_xy= 3614.00 S_x = 12.72 S_y = 394.61 SST = 758912.00. What is R² for this regression model?

What about the distribution of a random variable does kurtosis measure?

You have estimated the following simple regression model y = 379 + 1.44 x³ What does this model predict y to be when x = 8.49?

You have estimated a regression model and your printout includes the following information s_xy= 3614.00 S_x = 12.72 S_y = 394.61 SST = 758912.00. Use this information to calculate SSE.

Which of the following leads to large forecast errors?

When should a researcher consider transforming the explanatory variable in a simple linear regression model?

What hypothesis is tested when using the Jarque-Berra test ?

At what values of x₀ will the standard error of the forecast be smallest?

What does R2,the coefficient of determination,measure?

Which of the following will change if you scale the dependent variable in a simple regression model?

Which of the following expressions is NOT equal to Ʃ(y_i - y̅)² ?

An Introduction to Econometrics

Pp : Prob, Probability Primer, Probability Primer

The Simple Linear Regression Model

Interval Estimation and Hypothesis Testing

The Multiple Regression Model

Further Inference in the Multiple Regression Model

Using Indicator Variables

Heteroskedasticity

Regression With Time Series Data: Stationary Variables

Random Regressors and Moment Based Estimation

Simultaneous Equations Models

Regression With Time Series Data: Nonstationary Variables

Vector Error Correction and Vector Autoregressive Models

Time-Varying Volatility and Arch Models

Panel Data Models

Qualitative and Limited Dependent Variable Models

Filters

Exam 5: Prediction, Goodness-Of-Fit and Modeling Issues

What is the skewness of the normal distribution?

When the residuals from a simple regression model appear to be correlated with x,this is known as_______________________________.

You have estimated a model of two variables related such that ln(y)= 17.3 - .04 x If x decreases by 2 units,what is the expected change in y?

If a scatter plot of the data reveals an inverted U shape,what data transformation would allow it to be estimated with simple linear regression?

A measure of the symmetry of a distribution is ________________________.

You have estimated the following simple regression model y = 379 + 1.44 x3 What is the elasticity when x = 8.49?

When should a researcher consider transforming the explanatory variable in the simple linear regression model?

You have estimated a regression model and your printout includes the following information sxy= 3614.00 Sx = 12.72 Sy = 394.61 SST = 758912.00. What is R2 for this regression model?

What about the distribution of a random variable does kurtosis measure?

You have estimated the following simple regression model y = 379 + 1.44 x3 What does this model predict y to be when x = 8.49?

You have estimated a regression model and your printout includes the following information sxy= 3614.00 Sx = 12.72 Sy = 394.61 SST = 758912.00. Use this information to calculate SSE.

Which of the following leads to large forecast errors?

When should a researcher consider transforming the explanatory variable in a simple linear regression model?

What hypothesis is tested when using the Jarque-Berra test ?

At what values of x0 will the standard error of the forecast be smallest?

What does R2,the coefficient of determination,measure?

Which of the following will change if you scale the dependent variable in a simple regression model?

Which of the following expressions is NOT equal to Ʃ(yi - y̅)2 ?

An Introduction to Econometrics

Pp : Prob, Probability Primer, Probability Primer

The Simple Linear Regression Model

Interval Estimation and Hypothesis Testing

The Multiple Regression Model

Further Inference in the Multiple Regression Model

Using Indicator Variables

Heteroskedasticity

Regression With Time Series Data: Stationary Variables

Random Regressors and Moment Based Estimation

Simultaneous Equations Models

Regression With Time Series Data: Nonstationary Variables

Vector Error Correction and Vector Autoregressive Models

Time-Varying Volatility and Arch Models

Panel Data Models

Qualitative and Limited Dependent Variable Models

Filters

You have estimated the following simple regression model y = 379 + 1.44 x³ What is the elasticity when x = 8.49?

You have estimated a regression model and your printout includes the following information s_xy= 3614.00 S_x = 12.72 S_y = 394.61 SST = 758912.00. What is R² for this regression model?

You have estimated the following simple regression model y = 379 + 1.44 x³ What does this model predict y to be when x = 8.49?

You have estimated a regression model and your printout includes the following information s_xy= 3614.00 S_x = 12.72 S_y = 394.61 SST = 758912.00. Use this information to calculate SSE.

At what values of x₀ will the standard error of the forecast be smallest?

Which of the following expressions is NOT equal to Ʃ(y_i - y̅)² ?