Regression
Analysis
Multiple
Choice Questions
1. The
process of constructing a mathematical model that can be used to predict one
variable by other is called
i.
Regression
ii.
Correlation
iii.
Scatter plot
iv.
All the above
2. The
predicted rate of response of the dependent variable to changes in the
independent variable is called:
i.
Slope
ii.
Intercept
iii.
Error
iv.
Regression equation
3. In
simple linear regression, the numbers of unknown parameters are:
i.
0
ii.
1
iii.
2
iv.
3
4. In
simple linear regression, the numbers of variables involve are
i.
1
ii.
2
iii.
3
iv.
4
5. In the regression equation Y = 21 - 3X, the slope is
i.
21
ii.
– 21
iii.
3
iv.
- 3
6. In the regression equation Y = 2.50X+ 100, the intercept is
i.
2.50
ii.
– 2.50
iii.
– 100
iv.
100
7. For the Least Square trend Y^ = a + b X
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8. In
the Least Square Regression Line, ∑(Y−Y^)2 is always
i.
Zero
ii.
1
iii.
Least
iv.
Most
9. If
the equation of the regression line is y=5, then what result will you take
out from it?
i. The line passes through origin
ii. The line passes through (0, 5)
iii. The line passes through (5, 0)
iv. None of them
10. In
the model Y=mX+ a, Y is also known as the
i.
Regressend
ii.
Regressor
iii.
Explanatory
iv.
All the above
11. If
the regression equation is equal to Y=23.6–54.2X, then 23.6 is
the ______ while −54.2 is the ____ of the regression line.
i.
Slope & intercept
ii.
Intercept & slope
iii.
Slope & coefficient
iv.
Residual & intercept
12. In
regression equation y= α + βX + e, both X and Y variables
are
i.
Random
ii.
Fixed
iii.
X random & Y fixed
iv.
X fixed & Y random
13. In
Regression Analysis, the regression line (Y = α + βX) always intersect at the point
i.
(0, 0)
ii.
(X, Y)
iii.
(Mean of X, Mean of Y)
iv. all the above
14. The
regression Line always passes through
i.
Origin
ii.
Median of data
iii.
Mean of data
iv.
None of them
15. In Correlation both variables are always
i.
Random
ii.
Non Random
iii.
Same
iv.
None of these
16. The correlation coefficient for the regression
equation Y = 21
- 3X
i.
Positive
ii.
Negative
iii.
0
iv.
1
17. If
X and Y in the regression model are totally unrelated, then
i. r will be zero
ii.
r will be one
iii. r will be - 1
iv. r will be 0.5
18. Which
of the following statement is correct?
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19. The value we would predict for the dependent variable when the independent variables are all equal to zero is called:
i.
Slope
ii.
Sum of residual
iii.
Intercept
iv.
Difficult to tell
20. Which of the following statement is
correct, if Y^ = 200 - 0.25 X,
i.
Y
is increase by 25 %
ii.
Y
is increase by 2.5 %
iii.
Y
is decrease by 25 %
iv.
Y
is decrease by 2.5 %
21. If
the two lines of regression are perpendicular to each other, the correlation
coefficient r is …..
i. r = 0
ii. r = 1
iii. r = - 1
iv. Nothing can said
22. Homogeneity
of two population correlation coefficients can be tested by …
i.
Z test
ii.
T test
iii.
F test
iv. Chi square test
23. The
geometric mean of the two regression coefficient βYX and βXY is
equal to ….
i. r
ii. r ^2
iii. 1
iv. – 1
24. If
each of X variable is divided by 5 and Y by 10 then the
correlation between coded values is ….
i.
Same as original
ii.
Different from original
iii.
Direction will be change
iv.
Magnitude will be change
25. If βXY and βYX are
two regression coefficients, they have
i.
Same sign
ii.
Opposite sign
iii.
Both i) & ii) are possible
iv. Nothing can be said
26. In
regression analysis, the square root of Mean Squared Error (MSE) is called the
….
i.
Correlation coefficient
ii.
Standard error of the estimate
iii.
Coefficient of determination
iv.
None of these
28. If
i. Less than 0
ii. Greater than 0
iii.
Equal to 1
iv.
Equal to 0
29. The
strength (degree) of the correlation between
a set of independent variables X and a dependent
variable Y is measured by …
i.
Coefficient of correlation
ii.
Coefficient of determination
iii.
Standard error of the estimate
iv.
All the above
30. Relationship
between the
correlation coefficient and coefficient
of determination is that
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31. If R^2 = 0.40 for the regression line
i. The relation b/w X & Y is positive
ii. r is also 0.40
iii. 40 % variation is explain by X
iv.
40 % variation in Y is explain by X
32.
Which of the following
Y is strongly dependent on X:
i. R^2 = 0.45
ii. R^2 = 0.65
iii. R^2 = 0.85
iv. R^2 = 1.45
33. Which
one is equal to explained variation divided by total variation?
i.
SS due regression
ii.
Coefficient of determination
iii.
Standard error of the estimate
iv.
Coefficient of correlation
34. If correlation coefficient of y x is 0.70, then correlation coefficient of xy is
i.
0.7
ii.
– 0.7
iii.
0.36
iv.
– 0.36
35. If r xy = 0.7, then r uv is
i.
0.7
ii.
– 0.7
iii.
0.36
iv.
– 0.36
36. A
perfect negative correlation is signified by
i.
0
ii.
1
iii.
-1
iv.
0.5
37.
If two variables were
perfectly positively correlated, then which of statement is incorrect?
i.
r= 0
ii.
r< 0
iii.
r> 0
iv.
r = 1
38. If Y^ = a, then r xy?
i. 0
ii.
1
iii.
-1
iv.
0.5
39. If X and Y are
independent of each other, the Coefficient
of Correlation is
i.
0
ii.
0.5
iii.
-1
iv.
1
40. The Coefficient
of Correlation r is independent of
i.
Origin
ii.
Scale
iii.
Scale & origin
iv.
None of these
41. If r=0.6,byx=1.2 then
bxy is
i.
0.3
ii.
0.2
iii.
0.72
iv.
0.40
42. When
the regression line passes through the origin then
i. Intercept is zero
ii. slope is zero
iii. both i) & ii) are zero
iv. r is zero
43. The
range of a partial correlation coefficient is:
i. 0 to 1
ii. 0 to infinity
iii. - 1 to + 1
iv. negative infinity to positive infinity
44. If
the correlation coefficient between the
variables X and Y is ρ, the correlation coefficient
between X^2 and Y^2 is
i. ρ
ii. ρ^2
iii. 1
iv. 0
45. In
a regression analysis if SSE = 200 and SSR = 300, then the coefficient of
determination is
i.
0.6000
ii.
0.6667
iii.
0.4000
iv.
0.1500
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