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simple regression Flashcards

1
Q

1) If we regressed daily temperature on daily ice cream sales, we would expect to
find…
a. β1 = 0
b. β1 > 0
c. β1 < 0

A

B

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2
Q

2) In a simple linear regression model, we find that β1 is not significantly different
from zero. Which of the following can we conclude?
a. X is a good predictor of Y.
b. There is no linear relationship between X and Y.
c. There is no relationship between X and Y.
d. We cannot make any conclusion.

A

B

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3
Q

3) If we ran a simple linear regression of X on Y and found a highly
statistically significant result, we could conclude which of the following?
a. X causes Y
b. Y causes X
c. Changes in X are associated with changes in Y
d. X and Y are not related

A

C

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4
Q

4) What is β0?
a. The value of X when Y = 0
b. The predicted value of Y, given a specific value of X.
c. The intercept of the simple regression equation.
d. The slope of the simple regression equation

A

C

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5
Q

) In regression analysis, if the dependent variable is measured in dollars, the
independent variable ___.
a) must also be measured in dollars
b) can be measured in any unit of currency
c) cannot be measured in dollars
d) can be measure in any units

A

D

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6
Q

6) Another name for an explanatory variable is the dependent variable.
a. TRUE
b. FALSE

A

B

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7
Q

7) The following scatterplot indicates that the relationship between the two variables
x and y is ____.
a. Weak and positive
b. Strong and positive
c. Strong and negative
d. No relationship

A

C

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8
Q

8) In the sample regression equation Yhat = B0 + B1 *X, What is Yhat?
a. The y-intercept
b. The slope of the equation
c. The value of Y when X = 0
d. The predicted value of Y, given a specific X value

A

D

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9
Q

9) What does the estimated intercept (B0) in regression analysis?
a. The slope of the regression line
b. The value of the response variable when all of the explanatory variables are 0
c. The relationship between the response and explanatory variables
d. The difference in observed and predicted values of the response variable

A

B

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10
Q

10) A fitted least squares regression line ________.
a. May be used to predict a value of y if the corresponding X value is given
b. Is evidence for a cause-effect relationship between X and Y
c. Can only be computed if a strong linear relationship exists between x and y
d. None of the above

A

A

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11
Q

11) What does the Y intercept B0 represent:
a) The predicted value of Y when X = 0.
b) The estimated change in average Y per unit change in X.
c) The predicted value of Y.
d) The variation around the line of regression

A

A

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12
Q

12) In regression analysis, if the dependent variable is measured in dollars, the
independent variable ___.
a. must also be measured in dollars
b. can be measured in any unit of currency
c. cannot be measured in dollars
d. can be measure in any units

A

D

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13
Q

13) The least squares method chooses the line that minimizes _________.
a. The absolute value of the sum of errors
b. The number of independent variables
c. The sum of squared errors, or SSE
d. The Adjusted R-squared value

A

C

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14
Q

14) In the sample regression equation Yhat = B0 + B1*X, What is Yhat?
a. The y-intercept
b. The slope of the equation
c. The value of y when x = 0
d. The predicted value of y, given a specific x value

A

D

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15
Q

15) Consider the following simple linear regression model: Y = β0 + β1*X + ε.
The random error term is ________.
a. y
b. x
c. ε
d. β0

A

C

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16
Q

16) A sample regression equation is found to be Y = 0.7 + 0.4*X.
Which of the following statements is true?
a) X represents predicted values of the independent variable
b) If we plot this equation, 0.4 will be the y-intercept
c) If x is equal to 1, the predicted y-value is 1.1
d) If x is equal to 0 and y is equal to 0, the residual for this observation is .7

A

C

17
Q

1) Consider the following simple linear regression model:
Y = β0 + β1*X + ε
The random error term is ________.
a. Y
b. X
c. ε
d. β0

A

C

18
Q

2) If we ran a simple linear regression with our dependent variable being ice
cream sales and our independent variable being temperature, what sign would
we expect the coefficient on temperature to be?
Y (Sales) = B0 + B1*Temperature + ε
a. Positive
b. Negative
c. Zero
d. Not Enough Information to say

A

A

19
Q

3) In a regression equation, the slope term indicates the change in the dependent
variable given a change in the independent variable.
a. True
b. False

A

A

20
Q

4) What relationship do the following data have?
X 7 9 12 16 20
Y 4 12 20 26 29
a. Positive and linear
b. Negative and linear
c. Positive and non-linear
d. Negative and non-linear

A

C

21
Q

5) Simple linear regression analysis differs from multiple regression analysis in
that _______.
a) simple linear regression uses only one explanatory variable
b) the coefficient of correlation is meaningless in simple linear regression
c) goodness-of-fit measures cannot be calculated with simple linear regression
d) the coefficient of determination is always higher in simple linear regression

A

A

22
Q

6) What is a residual?
a. The value of the dependent variable for a given set of independent variable values.
b. The difference between out observed Y-value and the estimated Y-value
c. The difference between the various observed Y-values
d. The ratio of explained variation in Y to unexplained variation in Y

A

B

23
Q

7) In Ordinary Least Squares (OLS) regressions, we:
a. Create a regression line which minimizes SSE
b. Create a regression line that maximizes the dependent variable
c. Create a regression line to touch all the observations
d. Create a regression line that maximizes the SSE

A

A

24
Q

8) You are interested in studying the relationship between the age of automobiles
and their price on the used car market.
Which variable should be the independent variable?
a) Age of automobile
b) Price
c) There is probably no relationship between these variables
d) Could be either one

A

A

25
Q

9) the results of estimating a simple linear regression model (SLRM) help us to
decide which variable to use as the dependent variable, and which one to use as
the independent variable.
a. True
b. False

A

B

26
Q

10) Below is the estimated regression equation of car price on mileage.
Which is the correct interpretation of the coefficient on mileage?
Price = 23,000 – 0.57 Mileage
a. The price of a car decreases by 23,000 for every mile a car is driven.
b. The price of a car decreases by 57 cents for every mile a car is driven.
c. The price of a car decreases by 57 cents for every additional mile that car is driven,
on average.
d. On average driving a car another mile will increase the value of that car by 57 cents.

A

C

27
Q
A
28
Q
A

D

29
Q
A

C

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