coefficient of determination Flashcards
1) If SSE = 300 and SST = 625, compute the R-squared
a. 0.48
b. 0.52
c. 0.68
d. 0.32
B
2) For a particular regression model, SSR = 950, SSE = 120. The coefficient of
determination (R2) for this model is approximately:
a. 0.112
b. 0.126
c. 0.534
d. 0.887
D
3) Suppose R-squared = 0.60 and SSR = 90.
Compute the SSE.
a. 36
b. 54
c. 60
d. 150
C
1) The coefficient of determination (R2) measures the proportion of the variation in
__________________ that is explained by the variation in ________________.
a. X1; Y
b. The independent variables; the error term
c. The dependent variable; the error term
d. The dependent variable; the independent variables
D
2) If the value of adjusted R2 increases when adding a new variable, what must also
be true?
a. The statistical significance of all independent variables decreases
b. The value of R2 also increases
c. The value of R2 decreases
d. The value of R2 stays the same
B
3) Adding an independent variable, which has no predictive power, to a regression
model will usually lower the value of R-squared
a. True
b. False
B
4) When an independent variable is added to a regression, the adjusted R-squared
will always decrease.
a. True
b. False
B
5) The sum of Squared Residuals (SSE) is the variation in the data that is explained
by our model.
a. TRUE
b. FALSE
B
6) For a multiple regression model, SSE = 600 and SSR = 200.
The coefficient of determination (R-squared) is _____.
a. 0.333
b. 0.250
c. 0.300
d. 0.750
B
7) For a particular regression model, SSE = 250 and SST = 725. Compute the R2
a. 0.256
b. 0.344
c. 0.655
d. 0.782
C
8) In a regression analysis, the SSE = 56,690 and the SST = 113,380.
What is the R-squared?
a. 0.1
b. 0.2
c. 0.4
d. 0.5
D
9) Which is a way to increase the value of R2
a. Drop a variable from the model which is not particularly useful in predicting
the dependent variable.
b. Add an independent variable to the model which is useful for predicting the
dependent variable.
c. Correct for heteroskedasticity.
d. Reduce Multicollinearity by dropping an independent variable
B
10) If a significant relationship exists between X and Y and the R2 shows that the fit
is good, the estimated regression equation should be useful for:
a) extreme extrapolation
b) estimation and prediction.
c) determining nonresponse error.
d) determining cause and effect.
B
11) Suppose we run a simple linear regression with college GPA as the dependent
variable (Y) and distance from campus as the independent variable (X).
If the slope coefficient on distance from campus is negative, how could we
interpret this?
Y = B0 + B1*Distance + ε
a. Living closer to campus causes people to be better students and earn higher
GPAs.
b. Living farther from campus is associated with a lower GPA.
c. A student’s GPA will increase if he/she moves closer to campus.
d. A student’s GPA will increase if he/she moves farther from campus
A
12) A regression analysis between sales (in $1000s) and price (in dollars) resulted
in the following equation:
Y = 50,000 − 8*X
The above equation implies that an increase of _____.
a. $1 in price is associated with a decrease of $8 in sales
b. $8 in price is associated with an increase of $8,000 in sales
c. $1 in price is associated with a decrease of $42,000 in sales
d. $1 in price is associated with a decrease of $8,000 in sales
D
