Question 1

the equation Y = a + bX,the objective of regression analysis is to

Accepted Answer

A) estimate the parameters a and B 
B) estimate the variables Y and X. 
C) fit a straight line through the data scatter in such a way that the sum of the squared errors is minimized. 
D) both a and c 
A) estimate the parameters a and B 
B) estimate the variables Y and X. 
C) fit a straight line through the data scatter in such a way that the sum of the squared errors is minimized. 
D) both a and c D

Question 2

a linear regression equation of the form Y = a + bX,the intercept parameter a shows

Accepted Answer

A) the value of X when Y is zero. 
B) the value of Y when X is zero. 
C) the amount that Y changes when X changes by one unit. 
D) the amount that X changes when Y changes by one unit. 
A) the value of X when Y is zero. 
B) the value of Y when X is zero. 
C) the amount that Y changes when X changes by one unit. 
D) the amount that X changes when Y changes by one unit. B

Question 3

Tests for statistical significance must be performed

Accepted Answer

A) because the TRUE values of the intercept and slope parameters are random variables. 
B) because the ESTIMATED values of the intercept and slope parameters are not,in general,equal to the true values of the intercept and slope parameters. 
C) because the computed t-ratios are random variables and may be too large to provide evidence that b is not equal to zero. 
D) in order to determine whether or not the parameter estimates are far enough away from zero to conclude that the true parameter values are not equal to zero. 
E) both b and d 
A) because the TRUE values of the intercept and slope parameters are random variables. 
B) because the ESTIMATED values of the intercept and slope parameters are not,in general,equal to the true values of the intercept and slope parameters. 
C) because the computed t-ratios are random variables and may be too large to provide evidence that b is not equal to zero. 
D) in order to determine whether or not the parameter estimates are far enough away from zero to conclude that the true parameter values are not equal to zero. 
E) both b and d E

Question 4

An estimator is unbiased if it produces

Accepted Answer

A) a parameter from the sample that equals the true parameter. 
B) estimates of a parameter that are close to the true parameter. 
C) estimates of a parameter that are statistically significant. 
D) estimates of a parameter that are on average equal to the true parameter. 
E) both b and c 
A) a parameter from the sample that equals the true parameter. 
B) estimates of a parameter that are close to the true parameter. 
C) estimates of a parameter that are statistically significant. 
D) estimates of a parameter that are on average equal to the true parameter. 
E) both b and c

Question 5

a linear regression equation of the form Y = a + bX,the slope parameter b shows

Accepted Answer

A) $\Delta$X / $\Delta$Y. 
B) $\Delta$Y / $\Delta$X. 
C) $\Delta$Y /$\Delta$b. 
D) $\Delta$X / $\Delta$b. 
E) none of the above 
A) $\Delta$X / $\Delta$Y. 
B) $\Delta$Y / $\Delta$X. 
C) $\Delta$Y /$\Delta$b. 
D) $\Delta$X / $\Delta$b. 
E) none of the above

Question 6

sample regression line

Accepted Answer

A) shows the actual (or true)relation between the dependent and independent variables. 
B) is used to estimate the population regression line. 
C) connects the data points in a sample. 
D) is estimated by the population regression line. 
E) maximizes the sum of the squared differences between the data points in a sample and the sample regression line. 
A) shows the actual (or true)relation between the dependent and independent variables. 
B) is used to estimate the population regression line. 
C) connects the data points in a sample. 
D) is estimated by the population regression line. 
E) maximizes the sum of the squared differences between the data points in a sample and the sample regression line.

Question 7

The quadratic equation Y = a + bX +cX2 can be estimated using linear regression by estimating

Accepted Answer

A) Y = a + bX + ZX where Z = c2 
B) Y = a + ZX where Z = (b + c) 
C) Y = a + bZ where Z = X2 
D)  Y = a + ZX where Z = (b + c)2 
E) none of the above will work 
A) Y = a + bX + ZX where Z = c2 
B) Y = a + ZX where Z = (b + c) 
C) Y = a + bZ where Z = X2 
D)  Y = a + ZX where Z = (b + c)2 
E) none of the above will work

Question 8

The critical value of t is the value that a t-statistic must exceed in order to

Accepted Answer

A) reject the hypothesis that the true value of a parameter equals zero. 
B) accept the hypothesis that the estimated value of parameter equals the true value. 
C) reject the hypothesis that the estimated value of the parameter equals the true value. 
D) reject the hypothesis that the estimated value of the parameter exceeds the true value. 
A) reject the hypothesis that the true value of a parameter equals zero. 
B) accept the hypothesis that the estimated value of parameter equals the true value. 
C) reject the hypothesis that the estimated value of the parameter equals the true value. 
D) reject the hypothesis that the estimated value of the parameter exceeds the true value.

Question 9

To test whether the overall regression equation is statistically significant one uses

Accepted Answer

A) the t-statistic. 
B) the R2-statistic. 
C) the F-statistic. 
D) the standard error statistic. 
A) the t-statistic. 
B) the R2-statistic. 
C) the F-statistic. 
D) the standard error statistic.

Question 10

a linear regression equation Y = a + bX,the fitted or predicted value of Y is

Accepted Answer

A) the value of Y obtained by substituting specific values of X into the sample regression equation. 
B) the value of X associated with a particular value of Y. 
C) the value of X that the regression equation predicts. 
D) the values of the parameters predicted by the estimators. 
E) the value of Y associated with a particular value of X in the sample. 
A) the value of Y obtained by substituting specific values of X into the sample regression equation. 
B) the value of X associated with a particular value of Y. 
C) the value of X that the regression equation predicts. 
D) the values of the parameters predicted by the estimators. 
E) the value of Y associated with a particular value of X in the sample.

Question 11

Which of the following is an example of a time-series data set?

Accepted Answer

A) amount of labor employed in each factory in the U.S.in 2010 
B) amount of labor employed yearly in a specific factory from 1990 through 2010 
C) average amount of labor employed at specific times of the day at a specific factory in 2010 
D) All of the above are time-series data sets. 
A) amount of labor employed in each factory in the U.S.in 2010 
B) amount of labor employed yearly in a specific factory from 1990 through 2010 
C) average amount of labor employed at specific times of the day at a specific factory in 2010 
D) All of the above are time-series data sets.

Question 12

In a multiple regression model,the coefficients on the independent variables measure

Accepted Answer

A) the percent of the variation in the dependent variable explained by a change in that independent variable,all other influences held constant. 
B) the change in the dependent variable from a one-unit change in that independent variable,all other influences held constant. 
C) the change in that independent variable from a one-unit change in the dependent variable,all other influences held constant. 
D) the change in the dependent variable explained by the random error,all other influences held constant. 
A) the percent of the variation in the dependent variable explained by a change in that independent variable,all other influences held constant. 
B) the change in the dependent variable from a one-unit change in that independent variable,all other influences held constant. 
C) the change in that independent variable from a one-unit change in the dependent variable,all other influences held constant. 
D) the change in the dependent variable explained by the random error,all other influences held constant.

Question 13

A manager wishes to estimate an average cost equation of the following form: $C = a + b Q + c Q ^ { 2 }$ where Q is the level of output.Letting Z = Q2 and using least-squares estimation,the manager obtains the following computer output:   Given the above information,the value of R2 indicates that _______ of the total variation in C is explained by the regression equation.

Accepted Answer

A) 0.7679% 
B) 76.79% 
C) 7.679% 
D) 7679% 
A) 0.7679% 
B) 76.79% 
C) 7.679% 
D) 7679%

Question 14

Suppose you are testing the statistical significance (at the 1% significance level)of a parameter estimate from the regression model: M = a + bR + cI
Which is estimated using a cross-section data set on 22 firms.The critical value of the appropriate test statistic is

Accepted Answer

A) tcritical = 2.861. 
B) tcritical = -2.845. 
C) tcritical = 2.845. 
D) Fcritical = 5.93. 
E) Fcritical = 19.44. 
A) tcritical = 2.861. 
B) tcritical = -2.845. 
C) tcritical = 2.845. 
D) Fcritical = 5.93. 
E) Fcritical = 19.44.

Question 15

method of least squares

Accepted Answer

A) can be used to estimate the explanatory variables in a linear regression equation. 
B) can be used to estimate the slope parameters of a linear equation. 
C) minimizes the distance between the population regression line and the sample regression line. 
D) all of the above 
A) can be used to estimate the explanatory variables in a linear regression equation. 
B) can be used to estimate the slope parameters of a linear equation. 
C) minimizes the distance between the population regression line and the sample regression line. 
D) all of the above

Question 16

A manager wishes to estimate an average cost equation of the following form: $C = a + b Q + c Q ^ { 2 }$ where Q is the level of output.Letting Z = Q2 and using least-squares estimation,the manager obtains the following computer output:   Given the above information,which of the parameter estimates are statistically significant at the 1% significance level?

Accepted Answer

A) All parameter estimates are statistically significant. 
B) All parameter estimates except $\hat { b }$ are statistically significant. 
C)  $\hat { a }$ is not statistically significant,but all the rest of the parameter estimates are significant. 
D)  $\hat { C }$ is not statistically significant,but all the rest of the parameter estimates are significant. 
A) All parameter estimates are statistically significant. 
B) All parameter estimates except $\hat { b }$ are statistically significant. 
C)  $\hat { a }$ is not statistically significant,but all the rest of the parameter estimates are significant. 
D)  $\hat { C }$ is not statistically significant,but all the rest of the parameter estimates are significant.

Question 17

If an analyst believes that more than one explanatory variable explains the variation in the dependent variable,what model should be used?

Accepted Answer

A) a simple linear regression model 
B) a multiple regression model 
C) a nonlinear regression model 
D) a log-linear model 
A) a simple linear regression model 
B) a multiple regression model 
C) a nonlinear regression model 
D) a log-linear model

Question 18

A manager wishes to estimate an average cost equation of the following form: $C = a + b Q + c Q ^ { 2 }$ where Q is the level of output.Letting Z = Q2 and using least-squares estimation,the manager obtains the following computer output:   Given the above information,when output is 20 units,what is average cost?

Accepted Answer

A) $160 
B) $200 
C) $280 
D) $340 
E) $360 
A) $160 
B) $200 
C) $280 
D) $340 
E) $360

Question 19

If the p-value is 10%,then the

Accepted Answer

A) level of significance is 10%. 
B) level of confidence is 90%. 
C) probability of a Type I error is 90%. 
D) both a and b 
E) null hypothesis should not be rejected if the level of significance is 5% 
A) level of significance is 10%. 
B) level of confidence is 90%. 
C) probability of a Type I error is 90%. 
D) both a and b 
E) null hypothesis should not be rejected if the level of significance is 5%

Question 20

parameter estimate is said to be statistically significant if there is sufficient evidence that the

Accepted Answer

A) sample regression equals the population regression. 
B) parameter estimated from the sample equals the true value of the parameter. 
C) value of the t-ratio equals the critical value. 
D) true value of the parameter does not equal zero. 
A) sample regression equals the population regression. 
B) parameter estimated from the sample equals the true value of the parameter. 
C) value of the t-ratio equals the critical value. 
D) true value of the parameter does not equal zero.

the equation Y = a + bX,the objective of regression analysis is to

a linear regression equation of the form Y = a + bX,the intercept parameter a shows

Tests for statistical significance must be performed

An estimator is unbiased if it produces

a linear regression equation of the form Y = a + bX,the slope parameter b shows

sample regression line

The quadratic equation Y = a + bX +cX² can be estimated using linear regression by estimating

The critical value of t is the value that a t-statistic must exceed in order to

To test whether the overall regression equation is statistically significant one uses

a linear regression equation Y = a + bX,the fitted or predicted value of Y is

Which of the following is an example of a time-series data set?

In a multiple regression model,the coefficients on the independent variables measure

Suppose you are testing the statistical significance (at the 1% significance level)of a parameter estimate from the regression model: M = a + bR + cI Which is estimated using a cross-section data set on 22 firms.The critical value of the appropriate test statistic is

method of least squares

If an analyst believes that more than one explanatory variable explains the variation in the dependent variable,what model should be used?

If the p-value is 10%,then the

parameter estimate is said to be statistically significant if there is sufficient evidence that the

Managers,profits,and Markets

Demand,supply,and Market Equilibrium

Marginal Analysis for Optimal Decisions

Theory of Consumer Behavior

Elasticity and Demand

Demand Estimation and Forecasting

Production and Cost in the Short Run

Production and Cost in the Long Run

Production and Cost Estimation

Managerial Decisions in Competitive Markets

Managerial Decisions for Firms With Market Power

Strategic Decision Making in Oligopoly Markets

Advanced Pricing Techniques

Decisions Under Risk and Uncertainty

Government Regulation of Business

Filters

Exam 4: Basic Estimation Techniques

the equation Y = a + bX,the objective of regression analysis is to

a linear regression equation of the form Y = a + bX,the intercept parameter a shows

Tests for statistical significance must be performed

An estimator is unbiased if it produces

a linear regression equation of the form Y = a + bX,the slope parameter b shows

sample regression line

The quadratic equation Y = a + bX +cX2 can be estimated using linear regression by estimating

The critical value of t is the value that a t-statistic must exceed in order to

To test whether the overall regression equation is statistically significant one uses

a linear regression equation Y = a + bX,the fitted or predicted value of Y is

Which of the following is an example of a time-series data set?

In a multiple regression model,the coefficients on the independent variables measure

Suppose you are testing the statistical significance (at the 1% significance level)of a parameter estimate from the regression model: M = a + bR + cI Which is estimated using a cross-section data set on 22 firms.The critical value of the appropriate test statistic is

method of least squares

If an analyst believes that more than one explanatory variable explains the variation in the dependent variable,what model should be used?

If the p-value is 10%,then the

parameter estimate is said to be statistically significant if there is sufficient evidence that the

Managers,profits,and Markets

Demand,supply,and Market Equilibrium

Marginal Analysis for Optimal Decisions

Theory of Consumer Behavior

Elasticity and Demand

Demand Estimation and Forecasting

Production and Cost in the Short Run

Production and Cost in the Long Run

Production and Cost Estimation

Managerial Decisions in Competitive Markets

Managerial Decisions for Firms With Market Power

Strategic Decision Making in Oligopoly Markets

Advanced Pricing Techniques

Decisions Under Risk and Uncertainty

Government Regulation of Business

Filters

The quadratic equation Y = a + bX +cX² can be estimated using linear regression by estimating