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# Test: Correlation And Regression- 1

## 40 Questions MCQ Test Business Mathematics and Logical Reasoning & Statistics | Test: Correlation And Regression- 1

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This mock test of Test: Correlation And Regression- 1 for CA Foundation helps you for every CA Foundation entrance exam. This contains 40 Multiple Choice Questions for CA Foundation Test: Correlation And Regression- 1 (mcq) to study with solutions a complete question bank. The solved questions answers in this Test: Correlation And Regression- 1 quiz give you a good mix of easy questions and tough questions. CA Foundation students definitely take this Test: Correlation And Regression- 1 exercise for a better result in the exam. You can find other Test: Correlation And Regression- 1 extra questions, long questions & short questions for CA Foundation on EduRev as well by searching above.
QUESTION: 1

### (Direction 1-40) Write the correct answers. Each question carries 1 mark. Q. Bivariate Data are the data collected for

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The primary purpose of bivariate data is to compare the two sets of data or to find a relationship between the two variables.

QUESTION: 2

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QUESTION: 3

### Some of the cell frequencies in a bivariate frequency table may be

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QUESTION: 4

For a p x q bivariate frequency table, the maximum number of marginal distributions is

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QUESTION: 5

For a p x q classification of bivariate data, the maximum number of conditional distributions is

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QUESTION: 6

Correlation analysis aims at

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QUESTION: 7

Regression analysis is concerned with

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QUESTION: 8

What is spurious correlation?

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QUESTION: 9

Scatter diagram is considered for measuring

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QUESTION: 10

If the plotted points in a scatter diagram lie from upper left to lower right, then the correlation is

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QUESTION: 11

If the plotted points in a scatter diagram are evenly distributed, then the correlation is

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QUESTION: 12

If all the plotted points in a scatter diagram lie on a single line, then the correlation is

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QUESTION: 13

The correlation between shoe-size and intelligence is

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QUESTION: 14

The correlation between the speed of an automobile and the distance travelled by it after applying the brakes is

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Solution :- Initially the acceleration will be negative then finally the speed and distance will become 0.

QUESTION: 15

Scatter diagram helps us to

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QUESTION: 16

Pearson’s correlation coefficient is used for finding

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QUESTION: 17

Product moment correlation coefficient is considered for

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QUESTION: 18

If the value of correlation coefficient is positive, then the points in a scatter diagram tend to cluster

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QUESTION: 19

A process by which we estimate the value of dependent variable on the basis of one or more independent variables is called:

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QUESTION: 20

Product moment correlation coefficient may be defined as the ratio of

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QUESTION: 21

The covariance between two variables is

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QUESTION: 22

The coefficient of correlation between two variables

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QUESTION: 23

What are the limits of the correlation coefficient?

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QUESTION: 24

In case the correlation coefficient between two variables is 1, the relationship between the two variables would be

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QUESTION: 25

If the relationship between two variables x and y in given by 2x + 3y + 4 = 0, then the value of the correlation coefficient between x and y is

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QUESTION: 26

For finding correlation between two attributes, we consider

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QUESTION: 27

For finding the degree of agreement about beauty between two Judges in a Beauty Contest, we use

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QUESTION: 28

If there is a perfect disagreement between the marks in Geography and Statistics, then what would be the value of rank correlation coefficient?

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QUESTION: 29

When we are not concerned with the magnitude of the two variables under discussion, we consider

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QUESTION: 30

What is the quickest method to find correlation between two variables?

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QUESTION: 31

What are the limits of the coefficient of concurrent deviations?

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QUESTION: 32

If there are two variables x and y, then the number of regression equations could be

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QUESTION: 33

Since Blood Pressure of a person depends on age, we need consider

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QUESTION: 34

The method applied for deriving the regression equations is known as

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QUESTION: 35

The difference between the observed value and the estimated value in regression analysis is known as

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QUESTION: 36

The errors in case of regression equations are

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QUESTION: 37

The regression line of y on is derived by

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QUESTION: 38

What are the limits of the two regression coefficients?

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QUESTION: 39

The two lines of regression become identical when

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QUESTION: 40

The regression coefficients remain unchanged due to a

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The regression coefficients remain unchanged due to a shift of origin but change due to a shift of scale. (mea of "x", mean of "y"), ... If both the regression coefficients are negative, r would be negative and if both are positive, r would assume a positive value.