Question # 1

E(Y2) -[E(y)]2 is the formula, and to compute.

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Variance of the random variable

Mean of the random variable

Both A and B

None of these

For two independent random variables, Var(x) = 14 and Var(Y ) = 5, then var (X-y) is equal to.

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9

70

19

None of these

For a constant k, the variance of k is

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zero

k²

k

none of these

The properties of discrete probability distribution are:

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Σp (x) = 1 and Σx. (x) = 1

ΣP (x)= 1 and Σx. P

ΣP(x) = 1 and 0 < P(x) ≤ 1

All of these above

Hourly temperature recorded by weather brave is the example of:

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Discrete variable

Continuous variable

Qualitative

Both A and B

The probability of drawan any one spade card is.

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1/32

1/18

1/4

4/13

If x is a random variable with E(x) = 5 then E(3x - 2) =

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0

1

13

All of them

Which one is not an example of random experiments.

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A coin is tossed and the outcome is either a head or a tail

A six sided aid is rolled

All medical insurance clams received by a company in a given year.

Some one of person will be admitted to a hospital emergency room during any hour.

a measure of the chance that an uncertain event will occur.

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An experiment

An event

A probability

A trail

Probability distribution of a continuous random variable can be presented by

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tabular form

Formula

Curve

None of these

If one event is unaffected by the outcome of another event, the two events are said to be

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Dependent

Independent

Mutually exclusive

Both b and c

E(y-μ) is equal to

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E(y)

μ

zero

y-μ

Random variable is also called ___________.

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Chance stochasitc

Coverges

Random

None of these

The probability of drawing a king of spade from a pack of 52 cards is.

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1/4

1/13

1/26

1/52

Events with equal probabilities are called.

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Mutually exclusive events

Exhauative events

Eqauily likely events

Simple events

The probability distribution of discrete random variable is called is

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Frequency distribution

Probability distribution

Probability mass function

Both (a) and (b)

If x and y are independent random variables, then E(xy)

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E(xy)

xE(y)

E(x)

E(x)E(y)

Var (3x + 2)

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3 Var(X) + 2

3 Var X

9 var (x) + 2

9 var (x)

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