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Econometrics Final || Questions and 100% Verified Answers.
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Using the notation of the text, letting β0 = 3.0 and β1=2.0 in a regression model implies that: correct answers Y is expected to increase by 2.0 units if X increases by 1 unit If R^2 = 0.8, then correct answers SSR/TSS = 0.2 In a linear regression the one regressor, the standard error of th...

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  • September 10, 2024
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Econometrics Final || Questions and 100% Verified Answers.
Using the notation of the text, letting β0 = 3.0 and β1=2.0 in a regression model implies that:
correct answers Y is expected to increase by 2.0 units if X increases by 1 unit

If R^2 = 0.8, then correct answers SSR/TSS = 0.2

In a linear regression the one regressor, the standard error of the regression (SER) is defined as
correct answers sqrt(SSR/(n-2))

In the simple linear regression model, the regression slope correct answers indicates by how
many units Y increases, given a one unit increase in X

The OLS residuals correct answers can be calculated by subtracting the fitted values from the
actual values

Sir Francis Galton estimated a regression of students' heights on their parents average height.
Updating the regression, you get:

estimated student height in inches = 19.6 + 0.73 x average parent's height in inches;

R^2 = 0.45, and SER = 2.0

Based on this finding, we can conclude that correct answers students of very tall parents typically
are not as tall as their parents

The ordinary least squares regression estimates come from minimizing correct answers the sum
of squared residuals

The estimated regression of test scores on class size using the California data yielded an
estimated equation of:

estimated test score = 698.9 - 2.28 x student teacher ratio

According to this equation, reducing the student-teacher ratio by 2 corresponds to correct
answers an increase in test scores of about 4.6 points

Changing the units of measurement of the Y variable will affect all by which one of the
following? correct answers The R^2 of the regression

Other things equal, the OLS estimates of the slope will be greater if correct answers the
covariance between X and Y is greater

Heteroskedasticity means that correct answers the variance of the error term is not constant

, The t-statistic is calculated by dividing correct answers the estimator minus its hypothesized
value by the standard error of the estimator

A regression of student test scores on a measure of local air pollution obtains the following:

testscore = 725 - 12.4pollution, SER = 45

The R-squared for this regression should be correct answers between 0 and 1

Consider the following regression line:
estimated test score = 698.9 - 2.28 x STR
You are told that the t-statistic on the slope coefficient is 4.38. What is the standard error of the
slope coefficient? correct answers 0.52

(For this problem, let β1^ be the OLS estimate of β1) The 95% confidence interval for β1 is the
interval correct answers (β1^ - 1.645(SE))(β1^), (β1^ + 1.645(SE))(β1^)

Finding a small value for the p-value (e.g. less than 5%) correct answers indicates evidence
against the null hypothesis

The difference between a one- and two-sided hypothesis test is correct answers how you interpret
the t-statistic

If an estimator of the slope is unbiased, then when we calculate that estimate from a sample, it
means correct answers the expected value of the estimator over many random samples would be
equal to the true population slope

The least-squares assumption that rules out bias due to confounding effects is correct answers the
expected error conditional on X is zero

You have collected data for the 50 U.S. states and estimated the following relationship between
the change in the unemployment rate from the previous year (du) and the growth rate of the
respective state real GDP (dy). The results are as folllows

du = 2.81 [SE (0.12)] - 0.23dy [SE(0.04)] , R^2 = 0.36, SER = 0.78

If the estimator has a normal distribution, then the 95% confidence interval for the slope is
approximately the interval correct answers [-0.31, -0.15]

When you have an omitted variable problem correct answers the assumption that E(ui | Xi) = 0 is
violated

Using a sample of individual workers, a regression of average hourly earnings on a binary
(dummy) variable for female yields the following

AHE^ = 23 -2.5 Female

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