Deck 4: Basic Estimation Techniques

Question 1

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

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

Answer 1

C

Question 2

Suppose you are testing the statistical significance at the 5% significance level)of a parameter estimate from the regression equation: Y = a + bR + cS + dW
Which is estimated using a time-series sample containing monthly observations over a 30-month time period.The critical value of the appropriate test statistic is

A)t_critical = 2.042.
B)t_critical = 2.056.
C)F_critical = 4.22.
D)F_critical = 7.76.

Answer 2

t_critical = 2.056.

Question 3

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

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.

Answer 3

A

Question 4

method of least squares

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 5

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

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

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

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 7

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

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 8

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 9

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

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.

Question 10

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

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 11

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

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

Question 12

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

A)t_critical = 2.861.
B)t_critical = -2.845.
C)t_critical = 2.845.
D)F_critical = 5.93.
E)F_critical = 19.44.

Question 13

a regression equation,the ______ captures the effects of factors that might influence the dependent variable but aren't used as explanatory variables.

A)intercept
B)slope parameter
C)R-square
D)random error term

Question 14

If the p-value is 10%,then the

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 15

An estimator is unbiased if it produces

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 16

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

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.

Question 17

Tests for statistical significance must be performed

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

Question 18

In the regression model ,a test of the hypothesis that parameter c equals zero is

A)an F-test.
B)an R²-test.
C)a zero-statistic.
D)a t-test.
E)a Z-test.

Question 19

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

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.