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QUESTION: 1

The regression lines are identical if r is equal to

Solution:

The two lines of regression coincide i.e. become identical when r = –1 or 1 or in other words, there is a perfect negative or positive correlation between the two variables under discussion.

QUESTION: 2

The regression lines are perpendicular to each other if r is equal to

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QUESTION: 3

Feature of Least Square regression lines are——— The sum of the deviations at the Y’s or the X’s from their regression lines are zero.

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QUESTION: 4

The coefficient of determination is defined by the formula

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QUESTION: 5

The line Y = 13 –3X /2 is the regression equation of

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QUESTION: 6

In the line Y = 19 – 5X/2 , b_{yx} is equal to

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QUESTION: 7

The line X = 31/6 — Y/6 is the regression equation of

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QUESTION: 8

In the equation X = 35/8 – 2Y/5, b_{xy} is equal to

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QUESTION: 9

The square of coefficient of correlation ‘r’ is called the coefficient of

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QUESTION: 10

A relationship r^{2} = 1 —^{ 580} is not possible ^{300}

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QUESTION: 11

Whatever may be the value of r, positive or negative, its square will be

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QUESTION: 12

Simple correlation is called

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QUESTION: 13

A scatter diagram indicates the type of correlation between two variables.

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QUESTION: 14

If the pattern of points ( or dots) on the scatter diagram shows a linear path diagonally across the graph paper from the bottom left- hand corner to the top right, correlation will be

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QUESTION: 15

The correlation coefficient being +1 if the slope of the straight line in a scatter diagram is

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QUESTION: 16

The correlation coefficient being –1 if the slope of the straight line in a scatter diagram is

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QUESTION: 17

The more scattered the points are around a straight line in a scattered diagram the _______ is the correlation coefficient.

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QUESTION: 18

If the values of y are not affected by changes in the values of x, the variables are said to be

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QUESTION: 19

If the amount of change in one variable tends to bear a constant ratio to the amount of change in the other variable, then correlation is said to be

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QUESTION: 20

Variance may be positive, negative or zero.

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QUESTION: 21

Covariance may be positive, negative or zero.

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QUESTION: 22

Correlation coefficient between x and y = correlation coefficient between u and v

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QUESTION: 23

In case ‘ The ages of husbands and wives’ ———— correlation is

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QUESTION: 24

In case ‘Shoe size and intelligence’

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QUESTION: 25

In case ‘Insurance companies’ profits and the no of claims they have to pay “——

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QUESTION: 26

In case ‘Years of education and income’———

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QUESTION: 27

In case ‘Amount of rainfall and yield of crop’——

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QUESTION: 28

For calculation of correlation coefficient, a change of origin is

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QUESTION: 29

The relation r_{xy} = cov (x,y)/sigma x_{* }sigma y is

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QUESTION: 30

A small value of r indicates only a _________ linear type of relationship between the variables.

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QUESTION: 31

Two regression lines coincide when

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QUESTION: 32

Neither y nor x can be estimated by a linear function of the other variable when r is equal to

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QUESTION: 33

When r = 0 then cov (x,y) is equal to

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QUESTION: 34

When the variables are not independent, the correlation coefficient may be zero

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QUESTION: 35

b_{xy} is called regression coefficient of

Solution:

This we denote by a new notation bxy. Here, the first script x indicates that it is a dependent variable and the second y variable denotes to independent variable. And, this bxy is called the regression coefficient of x on y.

QUESTION: 36

b_{yx} is called regression coefficient of

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QUESTION: 37

The slopes of the regression line of y on x is

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QUESTION: 38

The slopes of the regression line of x on y is

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QUESTION: 39

The angle between the regression lines depends on

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QUESTION: 40

If x and y satisfy the relationship y = –5 + 7x, the value of r is

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