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This mock test of Test: Theoretical Distributions- 4 for CA Foundation helps you for every CA Foundation entrance exam.
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QUESTION: 1

Whatever may be the parameter of __________ distribution, it has same shape.

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QUESTION: 2

In Standard Normal distribution

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QUESTION: 3

The no. of methods for fitting the normal curve is

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QUESTION: 4

____________ distribution is symmetrical around t = 0

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QUESTION: 5

As the degree of freedom increases, the ________ distribution approaches the Standard Normal distribution

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QUESTION: 6

_________ distribution is asymptotic to the horizontal axis.

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QUESTION: 7

________ distribution has a greater spread than Normal distribution curve

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QUESTION: 8

In Binomial Distribution if n is infinitely large, the probability p of occurrence of event’ is close to _______ and q is close to _________

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QUESTION: 9

Poisson distribution approaches a Normal distribution as n

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QUESTION: 10

If neither p nor q is very small but n sufficiently large, the Binomial distribution is very closely approximated by _________ distribution

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QUESTION: 11

For discrete random variable x, Expected value of x (i.e E(x)) is defined as the sum of products of the different values and the corresponding probabilities.

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QUESTION: 12

For a probability distribution, —————— is the expected value of x.

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QUESTION: 13

_________ is the expected value of (x – m)^{2} , where m is the mean.

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QUESTION: 14

The probability distribution of x is given below :

**Q. Mean is equal to **

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QUESTION: 15

For n independent trials in Binomial distribution the sum of the powers of p and q is always n , whatever be the no. of success.

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QUESTION: 16

In Binomial distribution parameters are

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QUESTION: 17

In Binomial distribution if n = 4 and p = 1/3 then the value of variance is

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QUESTION: 18

In Binomial distribution if mean = 20, S.D.= 4 then q is equal to

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QUESTION: 19

If in a Binomial distribution mean = 20 , S.D.= 4 then p is equal to

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QUESTION: 20

If is a Binomial distribution mean = 20 , S.D.= 4 then n is equal to

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QUESTION: 21

Poisson distribution is a ___________ probability distribution .

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QUESTION: 22

No. of radio- active atoms decaying in a given interval of time is an example of

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QUESTION: 23

__________ distribution is sometimes known as the “distribution of rare events“.

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QUESTION: 24

The probability that x assumes a specified value in continuous probability distribution is

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QUESTION: 25

In Normal distribution mean, median and mode are

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QUESTION: 26

In Normal distribution the quartiles are equidistant from

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QUESTION: 27

In Normal distribution as the distance from the ___________ increases, the curve comes closer and closer to the horizontal axis .

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QUESTION: 28

A discrete random variable x follows uniform distribution and takes only the values 6, 8, 11, 12, 17The probability of P( x = 8) is

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QUESTION: 29

A discrete random variable x follows uniform distribution and takes the values 6, 9, 10, 11, 13The probability of P( x = 12) is

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QUESTION: 30

A discrete random variable x follows uniform distribution and takes the values 6, 8, 11, 12, 17

**Q. The probability of P is**

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QUESTION: 31

A discrete random variable x follows uniform distribution and takes the values 6, 8, 10, 12, 18

**Q. The probability of P( x < 12) is **

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QUESTION: 32

A discrete random variable x follows uniform distribution and takes the values 5, 7, 12, 15, 18

**Q. The probability of P( x > 10) is**

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QUESTION: 33

The probability density function of a continuous random variable is defined as follows :

**Q. f(x) = c when , otherwise The value of c is**

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QUESTION: 34

A continuous random variable x has the probability density fn.f(x) = ½ –ax ,

**Q. When ‘a’ is a constant. The value of ‘ a’ is**

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QUESTION: 35

A continuous random variable x follows uniform distribution with probability density function

**Q. **

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QUESTION: 36

An unbiased die is tossed 500 times.The mean of the no. of ‘Sixes’ in these 500 tosses is

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QUESTION: 37

An unbiased die is tossed 500 times. The Standard deviation of the no. of ‘sixes’ in these 500 tossed is

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QUESTION: 38

A random variable x follows Binomial distribution with mean 2 and variance 1.2.Then the value of n is

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QUESTION: 39

A random variable x follows Binomial distribution with mean 2 and variance 1.6 then the value of p is

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QUESTION: 40

“The mean of a Binomial distribution is 5 and standard deviation is 3”

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