ECON 320 FINAL EXAM REVISION QUESTIONS WITH
CERTIFIED CORRECT ANWSERS
Analyzing the behavior of unemployment rates across U.S. states in March of 2010 is an
example of using: - Cross-sectional Data
Assume that you assign the following subjective probabilities for you final grade in your
econometrics course: A: 0.20, B: 0.50, C: 0.20, D: 0.08, F: 0.02. The expected value is: - 2.78
Consider the following linear transformation of a random variable: Y=x-Ux/Ox, where Ux is the
mean of x and Ox is the standard deviation. Then the expected value and the standard deviation
of Y are given as: - 0 and 1
The correlation between X and Y: - Can be calculated by dividing the covariance between X and
Y by the product of the two standard deviations
Let Y be a random variable. Then var(Y) equals - E[(Y-Uy)^2]
The central limit theorem states that - the sampling distribution of Ybar-Uy/Oy is approximately
normal
A type II error is: - the error you make when not rejecting the null hypothesis when it is false
Binary Variables: - can take on only two values
, In the simple linear regression model, the regression slope: - indicates by how many units of Y
increases, given a one-unit increase in X
In the simple linear regression model Yi=Bo+B1Xi+Ui: - Bo+B1Xi represents the population
regression function
The OLS residuals, Ui-hat are sample counterparts of the population: - errors
The regression R^2 is a measure of: - the goodness of fit to your regression line
To obtain the slope estimator using the least squares principle, you divide the - sample
covariance of X and Y by the sample variance of X
The standard error of the regression (SER) is defined as follows - 1/(n-2) "Sigma" Ui-hat squared
When the estimated slope coefficient in the simple regression model, B1-hat is zero, then -
R^2=0
The following are all least squares assumptions with the exception of: - The explanatory variable
in regression model is normally distributed
Consider the estimated equation from you text book: Test Score=698.9-2.28*STR, R^2=0.051,
SER=18.6 (10.4)(0.52). The t-statistic for the slope is approximately: - 4.38
In general, the t-statistic has the following form: - estimator-hypothesized value/standard error
of estimator
CERTIFIED CORRECT ANWSERS
Analyzing the behavior of unemployment rates across U.S. states in March of 2010 is an
example of using: - Cross-sectional Data
Assume that you assign the following subjective probabilities for you final grade in your
econometrics course: A: 0.20, B: 0.50, C: 0.20, D: 0.08, F: 0.02. The expected value is: - 2.78
Consider the following linear transformation of a random variable: Y=x-Ux/Ox, where Ux is the
mean of x and Ox is the standard deviation. Then the expected value and the standard deviation
of Y are given as: - 0 and 1
The correlation between X and Y: - Can be calculated by dividing the covariance between X and
Y by the product of the two standard deviations
Let Y be a random variable. Then var(Y) equals - E[(Y-Uy)^2]
The central limit theorem states that - the sampling distribution of Ybar-Uy/Oy is approximately
normal
A type II error is: - the error you make when not rejecting the null hypothesis when it is false
Binary Variables: - can take on only two values
, In the simple linear regression model, the regression slope: - indicates by how many units of Y
increases, given a one-unit increase in X
In the simple linear regression model Yi=Bo+B1Xi+Ui: - Bo+B1Xi represents the population
regression function
The OLS residuals, Ui-hat are sample counterparts of the population: - errors
The regression R^2 is a measure of: - the goodness of fit to your regression line
To obtain the slope estimator using the least squares principle, you divide the - sample
covariance of X and Y by the sample variance of X
The standard error of the regression (SER) is defined as follows - 1/(n-2) "Sigma" Ui-hat squared
When the estimated slope coefficient in the simple regression model, B1-hat is zero, then -
R^2=0
The following are all least squares assumptions with the exception of: - The explanatory variable
in regression model is normally distributed
Consider the estimated equation from you text book: Test Score=698.9-2.28*STR, R^2=0.051,
SER=18.6 (10.4)(0.52). The t-statistic for the slope is approximately: - 4.38
In general, the t-statistic has the following form: - estimator-hypothesized value/standard error
of estimator
