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Question 1

The strength (degree) of the correlation between a set of independent variables X and a dependent variable Y is measured by

A

Coefficient of Correlation

B

Coefficient of Determination

C

Standard error of estimate

D

All of the above

Question 2

The percent of total variation of the dependent variable Y explained by the set of independent variables X is measured by

A

Coefficient of Correlation

B

Coefficient of Skewness

C

Coefficient of Determination

D

Standard Error or Estimate

E

Multicollinearity

Question 3

A coefficient of correlation is computed to be -0.95 means that

A

The relationship between two variables is weak.

B

The relationship between two variables is strong and positive

C

The relationship between two variables is strong and but negative

D

Correlation coefficient cannot have this value

Question 4

Let the coefficient of determination computed to be 0.39 in a problem involving one independent variable and one dependent variable. This result means that

A

The relationship between two variables is negative

B

The correlation coefficient is 0.39 also

C

39% of the total variation is explained by the independent variable

D

39% of the total variation is explained by the dependent variable

Question 5

Relationship between correlation coefficient and coefficient of determination is that

A

both are unrelated

B

The coefficient of determination is the coefficient of correlation squared

C

The coefficient of determination is the square root of the coefficient of correlation

D

both are equal

Question 6

Multicollinearity exists when

A

independent varialbes are correlated less than -0.70 or more than 0.70

B

An independent variables is strongly correlated with a dependent variable.

C

There is only one independent variable

D

The relationship between dependent and independent variable is non-linear

Question 7

If "time" is used as the independent variable in a simple linear regression analysis, then which of the following assumption could be violated

A

There is a linear relationship between the independent and dependent variables

B

The residual variation is the same for all fitted values of Y

C

The residuals are normally distributed

D

Successive observations of the dependent variable are uncorrelated

Question 8

In multiple regression, when the global test of significance is rejected, we can conclude that

A

All of the net sample regression coefficients are equal to zero

B

All of the sample regression coefficients are not equal to zero

C

At least one sample regression coefficient is not equal to zero

D

The regression equation intersects the Y-axis at zero.

Question 9

A residual is defined as

A

$Y-\hat{Y}$

B

Error sum of square

C

Regression sum of squares

D

Type I Error

Question 10

What test statistic is used for a global test of significance?
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A

Z test

B

t test

C

Chi-square test

D

F test

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Question 1

Correlation Coefficient values lies between

A

-1 and +1

B

0 and 1

C

-1 and 0

D

None of these

Question 2

If r_{xy} = -0.84 then r_{yx}=?

A

-0.84

B

0.84

C

0.42

D

None of these

Question 3

In correlation both variables are always

A

Random

B

Non Random

C

Same

D

None

Question 4

If two variables oppose each other then the correlation will be

A

Positive Correlation

B

Zero Correlation

C

Perfect Correlation

D

Negative Correlation

Question 5

A perfect negative correlation is signified by

A

0

B

1

C

0.5

D

-1

Question 6

The correlation coefficient between U=X and V=-X is

A

+1

B

-1

C

0

D

0.5

Question 7

The correlation coefficient between X and X is

A

-1 to +1

B

0

C

-1

D

1

Question 8

The correlation coefficient r is independent of

A

Origin only

B

Scale of Measurement only

C

Both change of origin and scale of measurement

D

None of these

Question 9

If X and Y are independent to each other, the coefficient of correlation is

A

-1

B

0

C

+1

D

None

Question 10

If b_{yx }<0 and b_{xy} =<0, then r is

A

=0

B

<0

C

>0

D

≠ 0

Question 11

If r=0.6, b_{yx}=1.2 then b_{xy}=?

A

0.3

B

0.2

C

0.72

D

0.40

Question 12

When regression line passes through the origin then

A

Regression coefficient is zero

B

Correlation is zero

C

Intercept is zero

D

Association is zero

Question 13

Two regression lines are parallel to each other if their slope is

A

Different

B

Same

C

Negative

D

None of these

Question 14

When b_{xy} is positive, then b_{yx} will be

A

Positive

B

Negative

C

Zero

D

One

Question 15

If $\hat{Y}=a\,$ then r_{xy}

A

$b_{xy}=1$

B

$b_{yx}=-1$

C

$b_{yx}=0$

D

None of these

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Question 1

For a Least Square trend $\hat{Y}=\alpha +\beta X$

A

$\sum Y =\sum \hat{Y}$

B

$\sum \hat{Y}=0$

C

$\sum Y< \sum \hat{Y}$

D

$\sum Y > \sum \hat{Y}$

E

None

Question 2

In Regression Analysis $\sum \hat{Y}$ is equal to

A

0

B

ΣY

C

a

D

bX

E

None

Question 3

In Regression Analysis two regression lines intersect at the point

A

(0, 0)

B

(α, α)

C

(X, Y)

D

$(\bar{X},\bar{Y})$

E

None

Question 4

If a straight line is fitted to data, then

A

$\sum Y = \sum \hat{Y}$

B

$\sum Y > \sum \hat{Y}$

C

$\sum Y < \sum \hat{Y}$

D

$\sum(Y-\hat{Y})^2=0$

Question 5

Which one is equal to explained variation divided by total variation?

A

Sum of squares due to regression

B

Coefficient of Determination

C

Standard Error of Estimate

D

Coefficient of Correlation

Question 6

The best fitting trend is one for which the sum of squares of error is

A

Zero

B

Minimum (Least)

C

Maximum

D

None

Question 7

In Least Square Regression Line $\sum(Y-\hat{Y})^2\,$ is always

A

Negative

B

Zero

C

Non-Negative

D

Fractional

E

None

Question 8

In a Least Square Regression line the quantity $\sum(Y-\hat{Y})\,$ is always

A

Negative

B

Zero

C

Positive

D

Fractional

E

None

Question 9

Regression Line always passes through

A

(X, Y)

B

$(\alpha, \beta)$

C

$(\bar{X},\bar{Y})$

D

$(\bar{X},Y)$

E

None

Question 10

If all the values fall on the same straight line and the line has a positive slope then what will be the value of the correlation coefficient ‘r’:

A

0 ≤ r ≤ 1

B

r ≥ 0

C

r = +1

D

r = -1

E

0

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Question 1

The regression equation is the line with slope a passing through

A

The point ($\overline{Y}, \overline{X}$)

B

The point ($\overline{X}, \overline{Y}$)

C

The point (Y, X)

D

The point (X, Y)

Question 2

The sample coefficient of correlation

A

Is also called Peterson's $r$

B

Has the same sign as the slope, i.e. $\beta$

C

Can range from -3.00 up to 2.00

D

Can range from -1.00 up to 2.00

Question 3

In regression equation $y = a + \beta x + e$, both x and y variables are

A

Random

B

x is fixed and y is random

C

Fixed

D

y is fixed and x is random

E

None of above

Question 4

The value of coefficient of correlation lies between

A

0 to -1

B

1 to -10

C

0 to 1

D

-1 to 1

Question 5

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

A

Radius, intercept

B

Slope, regression coefficient

C

Intercept, slope

D

Slope, intercept

Question 6

In the model $Y= mX+ a$,Y is also known as the

A

Predictor variable

B

Explanatory variable

C

Independent variable

D

Predicted (dependent) variable

Question 7

If the scatter diagram is drawn the scatter points lie on a straight line then it indicate

A

None of the above

B

Skewness

C

Perfect correlation

D

No correlation

Question 8

The method of least squares finds the best fit line that _____ the error between observed and estimated points on the line

A

Reduces to zero

B

Minimize

C

Maximize

D

Approaches to infinity

Question 9

If $R^2$ is zero, that is no collinearity/ Multicollinearity, the variance inflation factor (VIF) will be

A

Zero

B

One

C

None of the above

D

Two

Question 9 Explanation:

$VIF = \frac{1}{1-R^2}$

Question 10

If the equation of regression line is $y = 5$, then what result will you take out from it?

Student and Instructor of Statistics and business mathematics.
Currently Ph.D. Scholar (Statistics), Bahauddin Zakariya University Multan.
Like Applied Statistics and Mathematics and Statistical Computing.
Statistical and Mathematical software used are: SAS, STATA, GRETL, EVIEWS, R, SPSS, VBA in MS-Excel.
Like to use type-setting LaTeX for composing Articles, thesis etc.

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nice exercise

GOOD JOB FOR INTELGENT STU.

😯

jazakALLAH…….. very good work

Quite informative and good source of quick learning and assessing one’s self…

Salam Sir,

Sir l am going to appear in lecturer test therefore I need your kind help

Please share some books for FPSC test.

Informative but if you add reference of answers, it will be appreciable