Multiple Choice Questions Flashcards

1
Q

The normality assumption implies that:

A

The population error u is independent of the explanatory variables and is normally distributed with mean zero and variance σ2

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2
Q

A normal Variable is standardised by:

A

Subtracting off its mean from it and dividing by its standard distribution

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3
Q

Consider the equation, Y=β_1+β_2 X_2+u. A null hypothesis H_0:β_2=0 states that:

A

X_2 has no effect on the expected value of y

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4
Q

The general t-statistic can be written as:

A

t= (estimate - hypothesised value)/standard error

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4
Q

The significance level of a test is:

A

The probability of rejecting the null hypothesis when it is true

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5
Q

Which of the following statements is true of confidence intervals:
a. Confidence intervals in a CLM are also referred to as point estimates.
b. Confidence intervals in a CLM provide a range if likely values for the population parameter
c. Confidence intervals in a CLM do not depend on the degrees of freedom of a distribution
d. Confidence intervals in a CLM can be truly estimated when heteroskedasticity is present

A

Confidence intervals in a CLM provide a range of likely value for the population parameter

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6
Q

Which of the following is true
a. When the standard error of an estimate increases, the confidence interval for the estimate narrows down.
b. Standard error of an estimate does not affect the confidence interval for the estimate.
c. The lower bound of the confidence interval for a regression coefficient, say β_j is given by β_j - [standard error x (β_j)]
d. The upper bound of the confidence interval for a regression coefficient, say β_j, is given by β_j + [Critical value x standard error (β_j)]

A

The upper bound of the confidence interval for a regression coefficient, say β2, is given by βj + [Critical value x standard error (βj)]

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7
Q

Consider the following regression equation y=β0 +β1X1 + β2X2 + u. What does β1 imply?

A

β1 implies the ceteris paribus effect of X1 on y

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8
Q

If the explained sum of squares is 35 and the total sum of squares if 49, what is the residual sum of squares?

A

14

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9
Q

Rsquared shows…

A

Rsquared shows what percentage of the total variation in the dependent variable, y, is explained by the explanatory variables.

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10
Q

The value of Rsquared

A

lies between 0 and 1

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11
Q

If an independent variable in a multiple linear regression model is an exact linear combination of other independent variables, the model suffers from the problem of…

A

Perfect Collinearity

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12
Q

High (but not perfect) correlation between two or more independent variables is called…

A

Multicollinearity

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13
Q

The term “linear” in a **multiple regression model **means that the equation is linear in parameters (True or False)

A

True

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14
Q

The key assumption for the general multiple regression model is that all factors in the unobserved error term be uncorrelated with the explanatory variables (True or False)

A

True

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15
Q

A data set that consists of a sample of individuals, households, firms, cities, states, countries, or a variety of other units, taken at a given point in time, is called a(n)

A

Cross-sectional data set

16
Q

A data set that consists of observations on a variable or several variables over time is called a what?

A

Time Series data set

17
Q

Which of the following refers to panel data?
* Data on the unemployment rate in a country over a 5-year period
* Data on birth rate, death rate and population growth rate in developing countries over a 10-year period.
* Data on the income of 5 members of a family on a particular year
* Data on the price of a company’s share during the year.

A

Data on the birth rate, death rate and population growth rate in developing countries over a 10-year period.

18
Q

What is the difference between panel and pooled cross-sectional data?

A

A panel data set consists of data on the same cross-sectional units over a **given period of time **while a pooled data set consists of data on different cross-sectional units over a given period of time

19
Q

The notion of ‘ceteris paribus’ plays an important role in causal analysis (true or false)

A

True

20
Q

A time series data is also called a longitudinal data set (true or false)

A

False

21
Q

The notion of ceteris paribus means “other factors being equal” (True or false)

A

True

22
Q

In the equation y=β0 + β1x + u, β0 is the…

A

Intercept parameter

23
Q

in the equation y= β0 + β1x + u, what is the estimated value of β0?

A

y̅ − β1̂x

24
Q

in the equation c = β0 + β1i + u, c denotes consumption and i denotes income, What is the residual for the 5th observation if c5=$500 and c5^=$475?

A

$25

25
Q

Consider the following regression model: y = β0 + β1x1 + u. Which of the following is a property of Ordinary Least Square (OLS) estimates of this model and their associated statistics?
a. The sum, and therefore the sample average of the OLS residuals, is positive.
b. The sum of the OLS residuals is negative.
c. The sample covariance betweeen the regessors and the OLS residuals is positive.
d. The point (xbar,ybar) always lies on the OLS regression line

A

The point (xbar, ybar) always lies on the OLS regression line

26
Q

If the total sum of squares (SST) in a regression equation is 81, and the residual sum of squares (SSR) is 25, what is the explained sum of squares (SSE)?

A

56

27
Q

If the residual sum of squares (SSR) in a regression analysis is 66 and the total sum of squares (SST) is equal to 90, what is the value of the coefficient of determination?

A

0.27 [(66/90)=0.73][1-0.73=0.27]

28
Q

Is the following equation a nonlinear regression model?
y = 1 / (β0 + β1x) + u
(True or False)

A

True

29
Q

The error term in a regression equation is said to exhibit homoskedasticity if…

A

it has the same variance for all values of the explanatory variable

30
Q

A natural measure of the association between two random variables is the correlation coefficent. (True or False)

A

True

31
Q

The sample covariance between the regressors and the Ordinary Least Square (OLS) residuals is always positive. (True or False)

A

False

32
Q

Rsquared is the ratio of the explained variation compared to the total variation (True or False)

A

True

33
Q

The variance of the slope estimator increases as the error variance decreases (true or false)

A

False