MCQs

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Overall MCQs for Reference

Which of the following describes the probability of an impossible event?
a. 0
b. 0.5
c. 1
d. Infinity
Answer: a. 0sanfoundry
What is the sum of probabilities of all mutually exclusive outcomes of a random experiment?
a. 1
b. 0
c. 100
d. Undefined
Answer: a. 1sanfoundry
In Bayesian probability, what does denote?
a. Probability of B given A
b. Probability of A and B
c. Probability of A given B
d. Probability of B
Answer: c. Probability of A given Bdiptisurvase.wordpress
What is the probability of getting heads in a single toss of a fair coin?
a. 1
b. 0.5
c. 0.25
d. 2
Answer: b. 0.5sanfoundry
Which distribution is commonly used to model the probability of the number of successes in a fixed number of independent Bernoulli trials?
a. Normal
b. Binomial
c. Exponential
d. Poisson
Answer: b. Binomialsanfoundry
In a probability distribution, what does the area under the curve represent?
a. Variance
b. Standard deviation
c. Probability
d. Sample size
Answer: c. Probabilitytestbook
The probability of the union of two independent events A and B is given by:
a.
b.
c.
d.
Answer: d. sanfoundry
Which is true for conditional probability?
a. Always 0
b. Always 1
c. May range from 0 to 1
d. May be negative
Answer: c. May range from 0 to 1sanfoundry
What is a probability distribution that describes the likelihood of a given number of events occurring in a fixed interval?
a. Binomial
b. Poisson
c. Uniform
d. Bernoulli
Answer: b. Poissonsanfoundry
The Maximum Likelihood Estimate (MLE) is a method used in machine learning to:
a. Minimize probability
b. Maximize probability
c. Minimize error
d. Minimize variance
Answer: b. Maximize probabilitydiptisurvase.wordpress
In the context of machine learning, “prior probability” refers to:
a. Probability before evidence is taken into account
b. Probability after evidence
c. Probability of data
d. Sample probability
Answer: a. Probability before evidence is taken into accountdiptisurvase.wordpress
Which theorem updates the probability estimate for a hypothesis as more evidence is acquired?
a. Bayes’ theorem
b. Pythagorean theorem
c. Central limit theorem
d. Law of large numbers
Answer: a. Bayes’ theoremdiptisurvase.wordpress
In Naive Bayes Classifier, the features are assumed to be:
a. Correlated
b. Dependent
c. Strongly correlated
d. Independent
Answer: d. Independentdiptisurvase.wordpress
What is the expected value of a fair die roll?
a. 6
b. 1
c. 3
d. 3.5
Answer: d. 3.5testbook
The sum of probabilities in a probability distribution must be:
a. Less than 1
b. Greater than 1
c. Equal to 1
d. Unbounded
Answer: c. Equal to 1sanfoundry
If two events A and B are independent, is:
a.
b.
c.
d.
Answer: b. sanfoundry
Which law states “the probability of the union of two events is the sum of their individual probabilities minus the probability of their intersection”?
a. Law of Total Probability
b. Addition Law
c. Multiplication Law
d. Conditional Probability Law
Answer: b. Addition Lawsanfoundry
What is the probability that a fair coin will land heads up three times in a row?
a. 1/2
b. 1/4
c. 1/8
d. 1
Answer: c. 1/8sanfoundry
What does a likelihood function represent?
a. Probability of the data given a hypothesis
b. Probability of hypothesis given data
c. Joint probability
d. Marginal probability
Answer: a. Probability of the data given a hypothesisdiptisurvase.wordpress
For a discrete random variable X with values 1, 2, 3, each having equal probability, what is ?
a. 1/2
b. 1/3
c. 1/4
d. 1
Answer: b. 1/3testbook
The Law of Large Numbers asserts that as the number of trials increases, the experimental probability:
a. Moves away from theoretical probability
b. Remains unchanged
c. Approaches theoretical probability
d. Becomes zero
Answer: c. Approaches theoretical probabilitydiptisurvase.wordpress
If events A and B are mutually exclusive, what is ?
a. 1
b. 0
c.
d.
Answer: b. 0sanfoundry
To calculate the probability of the complement of event A, use:
a.
b.
c.
d.
Answer: a. sanfoundry
What best describes a probability mass function (PMF)?
a. Maps events to probabilities for discrete variables
b. Describes continuous variables
c. Maps mean values
d. Measures joint probability only
Answer: a. Maps events to probabilities for discrete variablestestbook
What is the role of the prior in Bayesian inference?
a. Ignore initial belief
b. Update belief after observation
c. Represent initial belief before evidence
d. Only considers marginal likelihood
Answer: c. Represent initial belief before evidencediptisurvase.wordpress
The probability of drawing an ace from a standard deck of 52 cards is:
a. 1/13
b. 1/52
c. 1/4
d. 1/26
Answer: a. 1/13sanfoundry
What is overfitting in probabilistic models?
a. Low probability
b. Model fits noise in data
c. Model fits all data perfectly
d. Underfitting
Answer: b. Model fits noise in datainterviewkickstart
Which of the following is true for a random variable?
a. It can take any value
b. Takes deterministic values
c. Takes values based on chance
d. Always discrete
Answer: c. Takes values based on chancetestbook
In Gaussian distribution, mean and variance are:
a. Both zero
b. Parameters
c. Always equal
d. Irrelevant
Answer: b. Parameterstestbook
Which is NOT a property of probability?
a. Negative values are allowed
b. Value always between 0 and 1
c. Sum of probabilities is 1
d. Probability of certain event is 1
Answer: a. Negative values are allowedsanfoundry
What is the probability that a randomly thrown die shows a number greater than 4?
a. 1/2
b. 1/3
c. 1/6
d. 2/3
Answer: b. 1/3testbook
If , and A and B are mutually exclusive, , equals:
a. 0.9
b. 0.7
c. 0.3
d. 0.2
Answer: a. 0.9sanfoundry
Which distribution describes the probability of a continuous variable?
a. Probability Mass Function
b. Probability Density Function
c. Cumulative Distribution Function
d. Bernoulli Distribution
Answer: b. Probability Density Functiontestbook
Which of the following is a discrete probability distribution?
a. Normal
b. Exponential
c. Binomial
d. Uniform (continuous)
Answer: c. Binomialsanfoundry
Poisson distribution is best used for:
a. Continuous outcomes
b. Rare events
c. Uniform distribution
d. Non-random events
Answer: b. Rare eventssanfoundry
The probability of drawing a red card from a standard deck of 52 cards is:
a. 1/4
b. 1/2
c. 1/3
d. 1/8
Answer: b. 1/2sanfoundry
Which of the following statements is true for random sampling in probability?
a. Each outcome is equally likely
b. Some outcomes are more likely
c. Only one outcome is possible
d. No outcomes are possible
Answer: a. Each outcome is equally likelysanfoundry
The probability density function (PDF) is defined for:
a. Discrete random variables
b. Continuous random variables
c. Both types
d. Neither
Answer: b. Continuous random variablestestbook
In the context of probability in ML, marginal probability is:
a. Probability of a single event irrespective of others
b. Joint probability
c. Conditional probability
d. Prior probability
Answer: a. Probability of a single event irrespective of othersdiptisurvase.wordpress
What does the Central Limit Theorem state?
a. Means of a large number of samples approach a normal distribution
b. Variance increases with data
c. Probabilities always add to 2
d. Only applies to discrete variables
Answer: a. Means of a large number of samples approach a normal distributiondiptisurvase.wordpress
What is the covariance between two independent random variables?
a. 0
b. 1
c. Negative
d. Undefined
Answer: a. 0testbook
If all outcomes of an experiment are equally likely, the probability of an event is:
a. Number of favorable outcomes / Total outcomes
b. Number of total outcomes / Favorable outcomes
c. Always 1
d. Always 0
Answer: a. Number of favorable outcomes / Total outcomessanfoundry
What is the “joint probability” in a Bayesian Network?
a. Probability of all variables together
b. Probability of only parent nodes
c. Probability of data
d. Marginal probability
Answer: a. Probability of all variables togetherexploredatabase
Which is NOT a probability distribution?
a. Bernoulli
b. Binomial
c. Linear
d. Normal
Answer: c. Lineartestbook
The notion “Probably Approximately Correct” is related to:
a. PAC Learning
b. Backpropagation
c. Bagging
d. Boosting
Answer: a. PAC Learningdiptisurvase.wordpress
What is the probability of picking a black card from a standard deck?
a. 1/2
b. 1/4
c. 1/13
d. 1/52
Answer: a. 1/2sanfoundry
If event B is certain given event A, then is:
a. 0
b. 1
c. Undefined
d. 0.5
Answer: b. 1diptisurvase.wordpress
In probability, a “trial” refers to:
a. Any process whose outcome is uncertain
b. The result of a coin toss
c. The sum of two events
d. Only deterministic outcomes
Answer: a. Any process whose outcome is uncertainsanfoundry
Which of these is used to describe “overfitting” in probabilistic models?
a. High variance
b. Low variance
c. High bias
d. None of the above
Answer: a. High varianceinterviewkickstart
In Bayes’ theorem, the “evidence” corresponds to:
a. Marginal probability of observed data
b. Posterior probability
c. Joint probability
d. Prior probability
Answer: a. Marginal probability of observed datadiptisurvase.wordpress

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