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Published on: 02/09/2022
QB365 provides a detailed and simple solution for every Possible Book Back Questions in Class 12 Business Maths Subject -Random Variable and Mathematical Expectation, English Medium. It will help Students to get more practice questions, Students can Practice these question papers in addition to score best marks.
Download Tamil Nadu 12th Standard Business Maths and Statistics question papers, model tests, one-mark questions, important questions, and public exam papers in PDF format. Free study materials and answer keys for TN State Board students.
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Take MCQ Business Maths and Statistics Test

1.
The distribution function F(x) is equal to ________.
\(P(X=x)\)
P(X\(\le\)x)
P(X\(\ge\)x)
all of these
2.
The height of persons in a country is a random variable of the type ________.
discrete random variable
continuous random variable
both (a) and (b)
neither (a) nor (b)
3.
The probability density function p(x) cannot exceed ________.
zero
one
mean
infinity
4.
A discrete probability function p(x) is always non-negative and always lies between ________.
0 and \(\infty \)
0 and 1
–1 and +1
–∞ and +∞
5.
An expected value of a random variable is equal to it’s ________.
variance
standard deviation
mean
covariance
6.
In a discrete probability distribution the sum of all the probabilities is always equal to ________.
zero
one
minimum
maximum
7.
A discrete probability function p(x) is always ________.
non-negative
negative
one
zero
8.
If p(x) =\(\frac{1}{10}\), c = 10, then E(X) is ________.
zero
\(\frac{6}{8}\)
1
-1
9.
The probability function of a random variable is defined as
| X=x | -1 | -2 | 0 | 1 | 2 |
| P(x) | K | 2K | 3K | 4K | 5K |
Then k is equal to ________.
zero
\(\frac{1}{4}\)
\(\frac{1}{15}\)
one
10.
A variable which can assume finite or countably infinite number of values is known as ________.
continuous
discrete
qualitative
none of them
11.
A set of numerical values assigned to a sample space is called ________.
random sample
random variable
random numbers
random experiment
12.
Which one is not an example of random experiment?
A coin is tossed and the outcome is either a head or a tail
A six-sided die is rolled
Some number of persons will be admitted to a hospital emergency room during any hour
All medical insurance claims received by a company in a given year
13.
A listing of all the outcomes of an experiment and the probability associated with each outcome is called ________.
probability distribution
probability density function
attributes
distribution function
14.
\(\int _{ -\infty }^{ \infty }{ f(x)dx } \) is always equal to ________.
zero
one
E(X)
f(x)+1
15.
If we have f(x)=2x, 0\(\le\)x\(\le\)1, then f (x) is a ________.
probability distribution
probability density function
distribution function
continuous random variable
16.
If the random variable takes negative values, then the negative values will have ________.
positive probabilities
negative probabilities
constant probabilities
difficult to tell
17.
E[X-E(X)]2 is ________.
E(X)
E(X2)
V(X)
S.D(X)
18.
E[X-E(X)] is equal to ________.
E(X)
V(X)
0
E(X)-X
19.
If c is a constant in a continuous probability distribution, then p(x = c) is always equal to ________.
zero
one
negative
does not exist
20.
A probability density function may be represented by ________.
table
graph
mathematical equation
both (b) and (c)
21.
A discrete probability distribution may be represented by ________.
table
graph
mathematical equation
all of these
22.
If c is a constant, then E(c) is ________.
0
1
c f (c)
c
23.
Which of the following is not possible in probability distribution?
\(\sum { p(x)\ge 0 } \)
\(\sum { p(x)=1 } \)
\(\sum { xp(x)=2 } \)
\(p(x)=-0.5\)
24.
If X is a discrete random variable and p(x) is the probability of X, then the expected value of this random variable is equal to ________.
\(\sum { f(x) } \)
\(\sum[x+f(x)]\)
\(\sum { f(x)+x } \)
\(\sum { xp(x) } \)
25.
A formula or equation used to represent the probability distribution of a continuous random variable is called ________.
probability distribution
distribution function
probability density function
mathematical expectation
26.
A variable that can assume any possible value between two points is called ________.
discrete random variable
continuous random variable
discrete sample space
random variable
27.
Given E(X)=5 and E(Y)=−2, then E(X−Y) is ________.
3
5
7
-2
28.
29.
Demand of products per day for three days are 21, 19, 22 units and their respective probabilities are 0.29, 0.40, 0.35. Profit per unit is 0.50 paisa then expected profits for three days are ________.
21, 19, 22
21.5, 19.5, 22.5
0.29, 0.40, 0.35
3.045, 3.8, 3.85
30.
Value which is obtained by multiplying possible values of random variable with probability of occurrence and is equal to weighted average is called ________.
Discrete value
Weighted value
Expected value
Cumulative value
1.
(b)
P(X\(\le\)x)
2.
(b)
continuous random variable
3.
(b)
one
4.
(b)
0 and 1
5.
(c)
mean
6.
(b)
one
7.
(a)
non-negative
8.
(c)
1
9.
(c)
\(\frac{1}{15}\)
10.
(b)
discrete
11.
(b)
random variable
12.
(d)
All medical insurance claims received by a company in a given year
13.
(a)
probability distribution
14.
(b)
one
15.
(b)
probability density function
16.
(a)
positive probabilities
17.
(c)
V(X)
18.
(c)
0
19.
(a)
zero
20.
(d)
both (b) and (c)
21.
(d)
all of these
22.
(d)
c
23.
(d)
\(p(x)=-0.5\)
24.
(d)
\(\sum { xp(x) } \)
25.
(c)
probability density function
26.
(b)
continuous random variable
27.
(c)
7
28.
(b)
29.
(d)
3.045, 3.8, 3.85
30.
(c)
Expected value
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Tamilnadu Stateboard 12th Standard Subjects

Maths

Chemistry

Physics

Biology

Computer Science

Business Maths and Statistics

Economics

Commerce

Accountancy

History

Computer Applications

Biology

Computer Technology

Computer Applications

Computer Science

Business Maths and Statistics

Commerce

Economics

Maths

Chemistry

Physics

Computer Technology

History

Accountancy

Tamil

English

French
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