1 |
Binomial distribution is used when n is |
Large
Small
Negative
Zero
|
2 |
If x and y are independent random variables, then E(xy) |
E(xy)
xE(y)
E(x)
E(x)E(y)
|
3 |
If the random variable x denotes the number of heads when three distinct coins are tossed, the x assumes values |
0, 1, 2, 3
1, 3, 3, 1
1, 2, 3
None of these
|
4 |
|
4/10
2/10
1/10
0
|
5 |
If mean = 25 and variance is also 25, then coefficient of variation is |
100%
25%
20%
10%
|
6 |
If x is a random variable with E(x) = 5 then E(3x - 2) = |
0
1
13
All of them
|
7 |
|
8
0
1/8
3
|
8 |
For a constant k, the variance of k is |
zero
k<sup>2</sup>
k
none of these
|
9 |
E(y-μ) is equal to |
E(y)
<span style="color: rgb(0, 0, 0); font-family: 'Lucida Sans Unicode', 'Lucida Grande', sans-serif; font-size: 18px; line-height: 23.390625px;">μ</span>
zero
y-<span style="color: rgb(0, 0, 0); font-family: 'Lucida Sans Unicode', 'Lucida Grande', sans-serif; font-size: 18px; line-height: 23.390625px;">μ</span>
|
10 |
If a is a constant then E(a) is equal to |
a
Square of a
Zero
2a
|
11 |
Probability distribution of a continuous random variable can be presented by |
tabular form
Formula
Curve
None of these
|
12 |
Var (3x + 2) |
3 Var(X) + 2
3 Var X
9 var (x) + 2
9 var (x)
|
13 |
The probability of a continuous random variable at x = a is --------------- |
One
Zero
Between 0 and 1
More than one
|
14 |
The probability distribution of discrete random variable is called is |
Frequency distribution
Probability distribution
Probability mass function
Both (a) and (b)
|
15 |
The simplest form of the continues distribution is the |
Skewed distribution
Kurtic distribution
Binomial distribution
Uniform distribution
|
16 |
Variance σ2 is equal to E(y2) - -------------------- |
E(y)
[E(y)]<sup>2</sup>
E(y)<sup>2</sup>
E<sup>2</sup> (y)
|
17 |
|
y<sub>1</sub> = y<sub>2</sub>
Y<sub>1</sub> > y<sub>2</sub>
None of these
|