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# Introduction to Probability Online Exam Quiz

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

Options

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

Options

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

Options

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)

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)

Options

A : a. square

B : b. triangle

C : c. circle

D : d. rectangle

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

Options

A : a. union of A

B : b. complement of A

C : c. intersection of A

D : d. A is equal to zero