Important questions about Introduction to Probability. Introduction to Probability MCQ questions with answers. Introduction to Probability exam questions and answers for students and interviews.

The way of getting information from measuring the observation whose outcomes occurrence is on chance is called

Options

A : a. beta experiment

B : b. random experiment

C : c. alpha experiment

D : d. gamma experiment

The probability of second event in the situation if the first event has been occurred is classified as

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A : a. series probability

B : b. conditional probability

C : c. joint probability

D : d. dependent probability

The probability which is based on the self-beliefs of the persons involved in the experiment is classified as

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A : a. subjective approach

B : b. objective approach

C : c. intuitive approach

D : d. sample approach

In probability theories, the events which can never occur together are classified as

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A : a. collectively exclusive events

B : b. mutually exhaustive events

C : c. mutually exclusive events

D : d. collectively exhaustive events

The joint probability of the independent events J and K is equal to

Options

A : a. P(J) * P(K)

B : b. P(J) + P(K)

C : c. P(J) * P(K) + P(J-K)

D : d. P(J) * P(K) - P(J * K)

Consider two events X and Y, the X-bar and Y-bar represents

Options

A : a. occurrence of Y

B : b. occurrence of X

C : c. non-occurrence of X and Y

D : d. occurrence of X and Y

In measuring the probability of any certain event, the zero represents

Options

A : a. impossible events

B : b. possible events

C : c. certain event

D : d. sample event

The number of individuals arriving at boarding counter on an airport is an example of

Options

A : a. numerical outcome

B : b. non numerical outcome

C : c. random outcome

D : d. simple outcome

The variation in which outcomes of experiments are effected by uncontrolled factors is considered as

Options

A : a. random variation

B : b. mesokurtic variation

C : c. platykurtic variation

D : d. mesokurtic variation

If two events X and Y are considered as partially overlapping events then the rule of addition can be written as

Options

A : a. P(X or Y) = P(X) - P(Y) + P(X and Y)

B : b. P(X or Y) = P(X) + P(Y) * P(X - Y)

C : c. P(X or Y) = P(X) * P(Y) + P(X - Y)

D : d. P(X or Y) = P(X) + P(Y) - P(X and Y)

If a person buys a lottery, the chance of winning a Toyota car is 60%, the chance of winning Hyundai car is 70% and the chance of winning both is 40% then chance of winning Toyota or Hyundai is

Options

A : a. 0.6

B : b. 0.9

C : c. 0.8

D : d. 0.5

According to combination rule, if the total number of outcomes are 'r' and distinct outcome collection is 'n' then combinations are calculated as

Options

A : a. n! ? r!(n - r)!

B : b. n! ? r!(n + r)!

C : c. r! ? n!(n - r)!

D : d. r! ? n!(n + r)!

The outcomes of an experiment are classified as

Options

A : a. logged events

B : b. exponential results

C : c. results

D : d. events

For a random experiment, all the possible outcomes are called

Options

A : a. numerical space

B : b. event space

C : c. sample space

D : d. both b and c

The types of probabilities for independent events must includes

Options

A : a. joint events

B : b. marginal events

C : c. conditional events

D : d. all of above

The probability without any conditions of occurrence of an event is considered as

Options

A : a. conditional probability

B : b. marginal probability

C : c. non conditional probability

D : d. occurrence probability

The joint probability of two statistical dependent events Y and Z can be written as P(Y and Z) =

Options

A : a. P(Z + Y) * P(Y|Z)

B : b. P(Y) * P(Z|Y)

C : c. P(Y) * P(Z|Y) + P(Z)

D : d. P(Y) * P(Z|Y) - P(Z + Y)

In a Venn diagram used to represent probabilities, the sample space of events is represented by

Options

A : a. square

B : b. triangle

C : c. circle

D : d. rectangle

The marginal probability of independent events and dependent events must be

Options

A : a. same

B : b. different

C : c. one

D : d. two

Consider an event B, the non-occurrence of event B is represented by