# 260+ Quantitative Techniques Solved MCQs

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1.

## The techniques which provide the decision maker a systematic and powerful means of analysis to explore policies for achieving predetermined goals are called..........................

A. Correlation techniques
B. Mathematical techniques
C. Quantitative techniques
D. None of the above
2.

## Correlation analysis is a ..............................

A. Univariate analysis
B. Bivariate analysis
C. Multivariate analysis
D. Both b and c
Answer» D. Both b and c
3.

## If change in one variable results a corresponding change in the other variable, then the variables are.........................

A. Correlated
B. Not correlated
C. Any of the above
D. None of the above
4.

A. Linear
B. Non-linear
C. Positive
D. Negative
5.

A. Linear
B. Non-linear
C. Positive
D. Negative
6.

A. Linear
B. Non-linear
C. Positive
D. Negative
7.

## ...........................attempts to determine the degree of relationship between variables.

A. Regression analysis
B. Correlation analysis
C. Inferential analysis
D. None of these
8.

## Non-linear correlation is also called.....................................

A. Non-curvy linear correlation
B. Curvy linear correlation
C. Zero correlation
D. None of these
9.

## Scatter diagram is also called ......................

A. Dot chart
B. Correlation graph
C. Both a and b
D. None of these
10.

## If all the points of a scatter diagram lie on a straight line falling from left upper corner to the right bottom corner, the correlation is called...................

A. Zero correlation
B. High degree of positive correlation
C. Perfect negative correlation
D. Perfect positive correlation
11.

## If all the dots of a scatter diagram lie on a straight line falling from left bottom corner to the right upper corner, the correlation is called..................

A. Zero correlation
B. High degree of positive correlation
C. Perfect negative correlation
D. Perfect positive correlation
12.

## Numerical measure of correlation is called .....................

A. Coefficient of correlation
B. Coefficient of determination
C. Coefficient of non-determination
D. Coefficient of regression
13.

A. Concentration
B. Relation
C. Dispersion
D. Asymmetry
14.

A. 0 and +1
B. 0 and –1
C. –1 and +1
D. – 3 and +3
15.

## A high degree of +ve correlation between availability of rainfall and weight of weight of people is:

A. A meaningless correlation
B. A spurious correlation
C. A nonsense correlation
D. All of the above
Answer» D. All of the above
16.

A. Linear
B. Non-linear
C. Curvilinear
D. None of these
17.

A. K
B. r
C. R
D. None of these
18.

## If r= +1, the correlation is said to be ...................

A. High degree of +ve correlation
B. High degree of –ve correlation
C. Perfect +ve correlation
D. Perfect –ve correlation
19.

A. Zero
B. High
C. Low
D. None of these
20.

A. 0
B. +1
C. –1
D. None of these
21.

## If all the points of a dot chart lie on a straight line parallel to the X-axis, it denotes .................................of correlation.

A. High degree
B. Low degree
C. Moderate degree
D. Absence
22.

A. 0
B. +1
C. –1
D. None of these
23.

## The unit of Coefficient of correlation is ........................

A. Percentage
B. Ratio
C. Same unit of the data
D. No unit
24.

## Product moment correlation method is also called ........................

A. Rank correlation
B. Pearsonian correlation
C. Concurrent deviation
D. None of these
25.

## The –ve sign of correlation coefficient between X and Y indicates.............................

A. X decreasing, Y increasing
B. X increasing, Y decreasing
C. Any of the above
D. There is no change in X and Y
Answer» C. Any of the above
26.

## Coefficient of correlation explains .................... of the relationship between two variables.

A. Degree
B. Direction
C. Both of the above
D. None of the above
Answer» C. Both of the above
27.

A. ± 1
B. + 1
C. – 1
D. 0
28.

A. Fisher
B. Spearman
C. Karl Pearson
D. Bowley
29.

## The rank correlation coefficient is always............................

A. + 1
B. – 1
C. 0
D. Between + 1 and – 1
Answer» D. Between + 1 and – 1
30.

A. K
B. r
C. S
D. R
31.

## Probable error is used to:

A. Test the reliability of correlation coefficient
B. Measure the error in correlation coefficient
C. Both a an b
D. None of these
Answer» A. Test the reliability of correlation coefficient
32.

A. 2 times
B. 5 times
C. 6 times
D. 10 times
33.

## In correlation analysis, Probable Error = ........................ x 0.6745

A. Standard deviation
B. Standard error
C. Coefficient of correlation
D. None of these
34.

## Coefficient of concurrent deviation depends on .......................

A. The signs of the deviations
B. The magnitude of the deviations
C. Bothe a and b
D. None of these
Answer» A. The signs of the deviations
35.

## Correlation analysis between two sets of data only is called....................

A. Partial correlation
B. Multiple correlation
C. Nonsense correlation
D. Simple correlation
36.

## Correlation analysis between one dependent variable with one independent variable by keeping the other independent variables as constant is called......................

A. Partial correlation
B. Multiple correlation
C. Nonsense correlation
D. Simple correlation
37.

## Study of correlation among three or more variables simultaneously is called.............

A. Partial correlation
B. Multiple correlation
C. Nonsense correlation
D. Simple correlation
38.

A. 80%
B. 8%
C. 64%
D. 0.8%
39.

## If r is the simple correlation coefficient, the quantity r2 is known as ...................

A. Coefficient of determination
B. Coefficient of non-determination
C. Coefficient of alienation
D. None of these
40.

## If r is the simple correlation coefficient, the quantity 1 -- r2 is known as ...................

A. Coefficient of determination
B. Coefficient of non-determination
C. Coefficient of alienation
D. None of these
41.

## The term regression was first used by..........................

A. Karl Pearson
B. Spearman
C. R A Fisher
D. Francis Galton
42.

## ....................refers to analysis of average relationship between two variables to provide mechanism for prediction.

A. Correlation
B. Regression
C. Standard error
D. None of these
43.

A. One
B. Two
C. Three
D. Infinite
44.

## If the regression line is Y on X, then the variable X is known as..........................

A. Independent variable
B. Explanatory variable
C. Regressor
D. All the above
45.

## Regression line is also called.................................

A. Estimating equation
B. Prediction equation
C. Line of average relationship
D. All the above
46.

## If the regression line is X on Y, then the variable X is known as..........................

A. Dependent variable
B. Explained variable
C. Both a and b
D. Regressor
Answer» C. Both a and b
47.

## If the regression line is X on Y, then the variable X is known as..........................

A. Dependent variable
B. Independent variable
C. Bothe a and b
D. None of the above
48.

## If the regression line is Y on X, then the variable X is known as..........................

A. Dependent variable
B. Independent variable
C. Both a and b
D. None of the above
49.

A. (0,0)
B. (1,1)
C. (x,y)
D. (x̄ , ӯ)
50.

## If r = ± 1, the two regression lines are...............................

A. Coincident
B. Parallel
C. Perpendicular to each other
D. None of these
51.

A. Ninety degree
B. Thirty degree
C. Zero degree
D. Sixty degree
52.

## If r = 0, the two regression lines are:

A. Coincident
B. Parallel
C. Perpendicular to each other
D. None of these
Answer» C. Perpendicular to each other
53.

## If bxy and byx are two regression coefficients, they have:

A. Same signs
B. Opposite signs
C. Either a or b
D. None of the above.
54.

## If byx > 1, then bxy is:

A. Greater than one
B. Less than one
C. Equal to one
D. Equal to zero
55.

## If X and Y are independent, the value of byx is equal to ........................

A. Zero
B. One
C. Infinity
D. Any positive value
56.

## The property that both the regression coefficients and correlation coefficient have same signs is called................................

A. Fundamental property
B. Magnitude property
C. Signature property
D. None of these
57.

## The property that byx > 1 implies that bxy < 1 is known as .....................

A. Fundamental property
B. Magnitude property
C. Signature property
D. None of these
58.

## If X and Y are independent, the property byx = bxy = 0 is called ...................

A. Fundamental property
B. Magnitude property
C. Mean property
D. Independence property
59.

## The Correlation coefficient between two variables is the ........................... of their regression coefficients.

A. Arithmetic mean
B. Geometric mean
C. Harmonic mean
D. None of these
60.

A. Positive
B. Negative
C. Not certain
D. None of these
61.

A. R
B. r2
C. 1 – r2
D. None of these
62.

A. 0
B. – ve
C. +ve
D. Either a or b
63.

## Arithmetic mean of the two regression coefficients is:

A. Equal to correlation coefficient
B. Greater than correlation coefficient
C. Less than correlation coefficient
D. Equal to or greater than correlation coefficient
Answer» B. Greater than correlation coefficient
64.

A. Y on X
B. X on Y
C. Either a or b
D. None of these
65.

A. Y on X
B. X on Y
C. Either a or b
D. None of these
66.

A. Multiple
B. Non-linear
C. Linear
D. None of these
67.

## The regression coefficient and correlation coefficient of the two variables will be the same if their .............................are same.

A. Arithmetic mean
B. Standard deviation
C. Geometric mean
D. Mean deviation
68.

A. R A Fisher
B. J Neyman
C. E L Lehman
D. A Wald
69.

## By testing of hypothesis, we mean:

A. A significant procedure in Statistics
B. A method of making a significant statement
C. A rule for accepting or rejecting hypothesis
D. A significant estimation of a problem.
Answer» C. A rule for accepting or rejecting hypothesis
70.

## Testing of hypothesis and ......................are the two branches of statistical inference.

A. Statistical analysis
B. Probability
C. Correlation analysis
D. Estimation
71.

## ......................... is the original hypothesis

A. Null hypothesis
B. Alternative hypothesis
C. Either a or b
D. None of these
72.

A. H0
B. H1
C. NH
D. None of these
73.

A. H0
B. H1
C. AH
D. None of these
74.

## Whether a test is one sided or two sided, depends on........................

A. Simple hypothesis
B. Composite hypothesis
C. Null hypothesis
D. Alternative hypothesis
75.

A. One kind of error
B. Two kinds of errors
C. Three kinds of errors
D. Four kinds of errors
Answer» B. Two kinds of errors
76.

A. Type I error
B. Type II error
C. Both a and b
D. None of these
77.

A. Type I error
B. Type II error
C. Both a and b
D. None of these
78.

A. Type I error
B. Type II error
C. Both a and b
D. None of these
79.

## Type II error means..............................

A. Accepting a true hypothesis
B. Rejecting a true hypothesis
C. Accepting a wrong hypothesis
D. Rejecting a wrong hypothesis
Answer» C. Accepting a wrong hypothesis
80.

A. Alpha
B. Beta
C. Gamma
D. None of these
81.

A. Alpha
B. Beta
C. Gamma
D. None of these
82.

## The level of probability of accepting a true null hypothesis is called........................

A. Degree of freedom
B. Level of significance
C. Level of confidence
D. D,
83.

## The probability of rejecting a true null hypothesis is called.......................

A. Degree of freedom
B. Level of significance
C. Level of confidence
D. None of these
84.

## 1 – Level of confidence =.............................

A. Level of significance
B. Degree of freedom
C. Either a or b
D. None of these
85.

A. 1%
B. 2%
C. 5%
D. 10%
86.

## ...............refers to the number of independent observations which is obtained by subtracting the number of constraints from the total number of observations.

A. Sample size
B. Degree of freedom
C. Level of significance
D. Level of confidence
87.

## Total number of observations – number of constraints =......................

A. Level of significance
B. Degree of freedom
C. Level of confidence
D. Sample size
88.

## Accepting a null hypothesis when it is false is called................................

A. Type I error
B. Type II error
C. Probable error
D. Standard error
89.

## Accepting a null hypothesis when it is true is called................................

A. Type I error
B. Type II error
C. Probable error
D. No error
90.

A. t-test
B. Z test
C. F test
D. None of these
91.

A. t-test
B. Z- test
C. F test
D. Sign test
92.

## Student’s t-test is applicable when:

A. The values of the variate are independent
B. The variable is distributed normally
C. The sample is small
D. All the above
93.

## Testing of hypotheses Ho : μ = 45 vs. H1 : μ > 45 when the population standard deviation is known, the appropriate test is:

A. t-test
B. Z test
C. Chi-square test
D. F test
94.

## Testing of hypotheses Ho : μ = 85 vs. H1 : μ > 85, is a ...................test.

A. One sided left tailed test
B. One sided right tailed test
C. Two tailed test
D. None of these
Answer» B. One sided right tailed test
95.

## Testing of hypotheses Ho : μ = 65 vs. H1 : μ < 65, is a ...................test.

A. One sided left tailed test
B. One sided right tailed test
C. Two tailed test
D. None of these
Answer» A. One sided left tailed test
96.

## Testing of hypotheses Ho : μ = 65 vs. H1 : μ ≠ 65, is a ...................test.

A. One sided left tailed test
B. One sided right tailed test
C. Two tailed test
D. None of these
97.

## Student’s t-test was designed by ............................

A. R A Fisher
B. Wilcoxon
C. Wald wolfowitz
D. W S Gosset
98.

## Z test was designed by ........................................

A. R A Fisher
B. Wilcoxon
C. Wald wolfowitz
D. W S Gosset
99.

## Z test was designed by .......................................

A. R A Fisher
B. Wilcoxon
C. Wald wolfowitz
D. W S Gosset
100.

A. – 1 to + 1
B. – ∞ to ∞
C. 0 to ∞
D. 0 to 1