Mathematics • Class 12
Probability - Class 12
Master Probability — Advanced through focused practice that strengthens conceptual understanding, problem-solving skills, and the ability to recognize common traps and misconceptions. Explore challenging questions designed to develop deeper reasoning and confident application of key ideas.
Overview
This chapter covers advanced topics in probability, including conditional probability, Bayes' theorem, random variables, probability distributions, and binomial distributions. It explores the practical applications of probability in various real-life scenarios.
Why This Chapter Matters
- Probability is a crucial mathematical tool used in science, engineering, economics, and everyday life. Understanding probability helps make informed decisions, analyze risks, and predict outcomes in uncertain situations.
Real-Life Applications
- Analyzing risks and uncertainties in insurance and financial markets.
- Solving problems related to genetics and population studies in biology.
- Predicting outcomes in sports, weather forecasts, and artificial intelligence models.
Skills You Will Learn
- Understanding conditional probability and Bayes' theorem.
- Working with random variables and probability distributions.
- Applying probability concepts to solve real-world problems.
Core Concepts to Master
Sample Space Partitioning
Total probability theorem requires mutually exclusive and exhaustive events; ignoring the 'exhaustive' condition leads to invalid results.
Conditional Probability Constraints
P(A|B) is only defined when P(B) > 0; students often fail to verify this constraint in complex problems.
Independent vs Disjoint Events
Confusion between P(A∩B)=P(A)P(B) and P(A∩B)=0; they are mathematically distinct and never imply each other.
Bayes' Theorem Reversal
Identifying the 'cause' versus 'effect' in inverse probability; mapping the correct prior and posterior distributions.
Bernoulli Trials Logic
Fixed probability of success and independence are mandatory; applying binomial distribution to dependent events is a fatal error.
Binomial Distribution Tail-Ends
Calculating 'at least one' via 1 - P(none) is efficient; manual summation of multiple terms invites calculation traps.
Random Variable Expectation
E(X) is the probability-weighted average; confusion arises when X is not a simple numerical count.
Sampling With/Without Replacement
Replacement implies independence (Binomial); non-replacement implies dependence (Hypergeometric/Combinatorics) which changes probability per trial.
Probability Mass Function (PMF)
Sum of probabilities must equal one; check if the defined range of X covers all possible sample space outcomes.
Complementary Counting
Using 'at most' or 'at least' constraints; failing to identify the full complement set is a common logical oversight.
Combinatorial Probability
Using nCr/nPr correctly; students often mistake 'ordered' versus 'unordered' selection in marbles/cards problems.
Equiprobable Outcomes
Classical definition requires equally likely events; applying it to biased dice or weighted sets results in total failure.
De Morgan's Laws in Probability
Transforming P(A' ∩ B') into 1 - P(A ∪ B) is crucial for simplifying complex intersection-based Venn diagrams.
Variance of Discrete Variable
Calculated as E(X²) - [E(X)]²; students frequently forget to square the expectation or miscalculate the variance.
Multiplication Principle Scope
Distinguishing between independent sequential events and conditional dependence; the logic pivot is whether the first action alters the second.
Concept Collisions Used by Examiners
Competitive examinations rarely assess concepts in isolation. Instead, examiners intentionally combine multiple concepts from this and related chapters to create higher-order questions that test conceptual reasoning, analytical thinking, and problem-solving ability. The concept collision patterns below represent the combinations most frequently used while designing questions for this chapter.
Exam Coverage
Understand how this chapter is tested across major competitive examinations.
JEE Advanced
India · Competitive Exam · Undergraduate
JEE Main
India · Competitive Exam · Undergraduate
BITSAT
India · Competitive Exam · Undergraduate
IISER Aptitude Test (IAT)
India · Competitive Exam · Undergraduate
NEST
India · Competitive Exam · Undergraduate
ISI Admission Test
India · Competitive Exam · Undergraduate
CMI Entrance
India · Competitive Exam · Undergraduate
IOQM / INMO
India · Olympiad · High School
SAT Math
United States · Curriculum · High School
A-Level Mathematics
United Kingdom · Curriculum · Advanced Level
A-Level Further Mathematics
United Kingdom · Curriculum · Advanced Level
IB Mathematics AA HL
International · Curriculum · IB Diploma
Singapore A-Level Mathematics
Singapore · Curriculum · Advanced Level
Cambridge International A-Level Mathematics
International · Curriculum · Cambridge
International Mathematical Olympiad (IMO)
International · Olympiad · International
Practice Questions
Strengthen your understanding by solving carefully selected questions from this chapter.
Two fair dice are rolled to obtain two numbers and respectively, where . Consider the system of linear equations: Three urns and contain balls as follows: has 3 Red and 2 Black balls, has 2 Red and 3 Black balls, and has 4 Red and 1 Black balls. A ball is drawn at random from if the system has a unique solution, from if the system has infinitely many solutions, and from if the system has no solution. If the drawn ball is Red, what is the probability that the system of equations had no solution?
A biased die has its faces painted with three colors: Red, Blue, and Green. The probability of rolling a Red face is , a Blue face is , and a Green face is . In a game, a player rolls this die times independently. For each Red face rolled, the player scores point; for each Blue face, points; and for each Green face, points. What is the probability that the player scores exactly points in the rolls?
Let be a generating function whose first derivative is given by . A random variable follows a binomial distribution with and . Let be the event that is strictly decreasing at , and let be the event that is strictly concave at . Find the conditional probability .
Let , where . Let be the set of all quadratic equations of the form , where . If two distinct equations are chosen at random from , the probability that they have at least one common root is , where and are coprime positive integers. The value of is:
Let . A point is chosen uniformly at random such that . Let be the point and be the plane . What is the probability that the line segment intersects the plane ?
15 identical coins are distributed into 3 distinct boxes. Let be the number of coins in the -th box (). Let be the event that , where denotes the greatest integer function. Let be the event that for all . The conditional probability is
Let . A continuous random variable has the probability density function where is a constant such that is a valid probability density function. Find the conditional probability .
Let be the set of distinct complex roots of the polynomial . For any , let denote its principal argument. Define the set as: A pair of distinct complex numbers is chosen uniformly at random from . Let be the probability that . Find the value of:
Let be three mutually perpendicular unit vectors in forming a right-handed coordinate system. Let be a random unit vector chosen uniformly from the surface of the unit sphere centered at the origin. Let be the volume of the parallelepiped whose coterminous edges are the vectors , and .
Define two events based on this volume: : :
Find the conditional probability .
Let . A biased coin with probability of heads is tossed repeatedly. Let be the random variable representing the number of tails obtained before exactly 3 heads appear. Let be the number of successes in independent Bernoulli trials, where the probability of success in each trial is . Find the variance of the random variable .
Let be the sample space of all orthogonal matrices with real entries. A matrix is chosen uniformly at random from . (The uniform distribution is defined by choosing the parameter uniformly, and the determinant with equal probability ). Let be the event that , be the event that , be the event that , and be the event that . Which of the following statements is correct?
Let and be two independent events with probabilities and , where . Consider the matrix Let be the set of all values of for which the eigenvectors of span . Then the sum of all elements in is:
Let and be two disjoint events in a sample space such that . Consider three points in the Cartesian plane: , , and . Let be the matrix whose rows are for , where are the coordinates of in the standard coordinate system. Let . A new coordinate system is defined by the transformation and . Let be the corresponding matrix using the coordinates of the same points in the system, and let . If , what is the value of ?
For sufficiently small , let and be two events such that and . The probability of their union satisfies the integral equation: Let . Find the value of .
Let and be the set of all functions from to . The set is partitioned into three subsets as follows:
: The set of all bijective functions. : The set of all functions that can be expressed as , where is surjective, is injective, and . : The set of all remaining functions in .
A biased die is rolled to select one of the subsets, such that the probability of selecting is proportional to . Then, a function is chosen uniformly at random from the selected subset. Given that the chosen function satisfies , what is the probability that it was chosen from ?
Let be the set of all integers () for which the binomial coefficient attains its maximum value. Define . Two bags and are given. Bag contains 2 Red and 3 Black balls, while Bag contains 3 Red and 4 Black balls. A bag is selected at random such that the probability of choosing is proportional to and the probability of choosing is proportional to . A ball is drawn at random from the selected bag and is found to be Red. The probability that it came from Bag is:
A point is chosen uniformly at random from the solid sphere . Let be the perpendicular distance from to the plane . Two boxes, and , contain colored balls. Box contains 2 white and 3 black balls. Box contains 4 white and 1 black balls. If , Box is selected. If , Box is selected. A ball is drawn at random from the selected box and is found to be white. The probability that Box was selected is:
A point is chosen uniformly at random from the region . Let be a complex number defined by the transformation . A Bernoulli trial is considered a success if satisfies both of the following conditions: (i) (ii) Let be the number of successes in independent trials. Find the value of , where denotes the expected value.
Let be a valid probability of success for a Bernoulli trial such that the function attains a local maximum at . An experiment consists of repeatedly performing independent Bernoulli trials with success probability until 2 consecutive successes occur. Let be the expected number of trials required. Find the value of .
Let be a random variable representing the number of successes in independent Bernoulli trials, each with probability of success . If the coefficient of variation of is at most , then the maximum possible standard deviation of is:
Let be the volume of a right circular cone of height inscribed in a sphere of radius . Let be the height that maximizes this volume, and let . For each integer , let be a random variable following the binomial distribution , where . Evaluate the limit:
Let , where , , and . It is given that is a nilpotent matrix of index 2. If represents the probability of success in a single trial of a binomial experiment, find the probability of at least 4 successes in 6 independent trials.
Let be the feasible region in the first quadrant () satisfying the system of inequalities: Let be the maximum value of the objective function over the region . A biased coin, whose probability of showing heads is , is tossed 5 times. Let be the number of heads obtained. Find the probability that the coin shows heads at least 3 times.
Let be a random variable representing the number of successes in independent Bernoulli trials. The probability of success in a single trial is given by , where Find the value of .
Let be a set of three vectors where , , and . Let be the set of all matrices whose rows are formed by choosing vectors from with replacement. A matrix is chosen at random from . Let be the event that the system of linear equations has non-trivial solutions, and be the event that is a nilpotent matrix. The value of is:
Let . A number is chosen uniformly at random from . Let be the event that Find the probability of the event .
Let . A number is chosen at random from . Let the function be defined as Let be the global maximum value of on the interval . Let be the event that is an integer, and be the event that is non-differentiable at the point(s) where it attains its global maximum. Find the conditional probability .
Let . A point is chosen at random from . Given that the equation represents a conic section, what is the probability that it represents a non-degenerate rectangular hyperbola?
Let . An ordered triplet of distinct numbers is chosen randomly from to form the matrix Let be the event that and be the event that the matrix is invertible. The value of the conditional probability is
Let be the sample space of all functions , where . A function is chosen at random from with uniform probability. Define an equivalence relation on by . Let denote the equivalence class containing . Let be the event that the chosen function satisfies for all . Let be the event that the chosen function belongs to an equivalence class of size exactly . Find the conditional probability .
Let be a continuous random variable taking values in the interval . Its probability density function satisfies the integral equation: for all . Let be the event that the roots of the quadratic equation (in variable ) are real. Let be the event that satisfies the inequality: Find the conditional probability .
A line with direction vector is generated such that is a random vector uniformly distributed on the surface of the unit sphere in . Let be a fixed plane in . Let be the acute angle between the line and the plane . If is the event that and is the event that , then the conditional probability is equal to
Let be a discrete random variable taking values in the set of non-negative integers . The probability mass function of is given by where and is a positive constant such that . Find the conditional probability .
Let and be two independent events associated with a random experiment. The probabilities of these events are given by: Find the value of , where denotes the greatest integer less than or equal to .
The probability that a quantum system remains in its initial state at time satisfies the differential equation with the initial condition . A researcher measures the state at and correctly determines the probability . To predict the probability at , the researcher incorrectly assumes the system's decay is memoryless, satisfying for all . Let be the researcher's estimated probability at , and be the actual probability at governed by the differential equation. Find the value of .
A biased coin with probability of heads is tossed repeatedly until a head appears. Let be the total number of tosses required. Let be the event that is a multiple of 3, and be the event that . If , find the probability that is an even number.
Let and be a partition of a sample space. The prior probabilities of these events are given by: where and denotes the greatest integer function. Let be the set of all possible values of for which this partition is valid. If , an observable event occurs such that the conditional probabilities are , , and . Find the value of .
Let be the coefficient of in the polynomial . A set of 14 bags, labeled , is given. A bag is selected such that the probability of selecting bag is proportional to . Each bag contains red balls and black balls. A bag is chosen at random according to the given probabilities, and two balls are drawn from it, one after another, with replacement. Given that both drawn balls are red, what is the probability that they were drawn from bag ?
Let and be two mutually exclusive and exhaustive events such that the prior probability is given by A box contains 4 red and 1 black balls, while box contains 3 red and 5 black balls. A box is selected such that the probability of selecting is and the probability of selecting is . A ball is drawn at random from the selected box and is found to be red. The probability that it was drawn from box is:
A particle is placed in the Cartesian plane. A random process selects its domain of uniform distribution: with probability , the particle is distributed uniformly over the region enclosed by the locus ; with probability , it is distributed uniformly over the region enclosed by the locus . Given that the particle's position satisfies the condition , what is the probability that its domain was ?
Let . Let be the number of points in where is non-differentiable. A biased coin with probability of heads is tossed 75 times. If is the number of heads obtained, find the value of .
Let , , and , where . Let be the volume of the parallelepiped whose coterminous edges are . A biased coin, which shows heads with probability , is tossed 10 times. Let denote the number of heads obtained. Find the value of
Let be an matrix where for . Let be the probability of success in a single trial of a Bernoulli experiment. Let be the number of successes in independent trials of this experiment. If , then the variance of is equal to
Let be the set of all positive integers for which there exists a positive integer satisfying the system of linear inequalities: A biased coin, whose probability of getting heads is , is tossed times for each . Let be the probability of getting exactly 2 heads in tosses. Find the value of .
Let be a matrix such that , , and . Let . The probability of success of an event is given by . A trial is repeated times independently. Let be the number of successes, and let . If and , find the value of .
A biased tetrahedral die has four faces coloured red, black, white, and white. The probability of rolling the red face is , the black face is , and a white face is . If the die is rolled times, let be the probability that either the red face appears at least twice, or the black face appears at least twice (or both). Find the value of .
Let be a random variable chosen uniformly from the set . A set of 5 distinct objects is divided into non-empty subsets, where . All valid partitions of the 5 objects into subsets are equally likely. Let be the random variable representing the number of objects in the subset containing a specific object . Find the expected value .
Let be the set of all integers satisfying the inequality . A number is chosen uniformly at random from . Let the random variable be defined as the maximum real root of the quadratic equation Find the expected value .
Let and be independent random variables, each chosen uniformly from the set . Consider the system of linear equations , where Let be the rank of the augmented matrix . The expected value of , denoted by , is:
Let be the greatest binomial coefficient in the expansion of . A bag contains distinct balls numbered to . Experiment A consists of drawing 3 balls from the bag with replacement. Let be the probability that the sum of the numbers on the drawn balls is at most . Experiment B consists of drawing 3 balls from the bag without replacement. Let be the probability that the sum of the numbers on the drawn balls is at most . Find the value of .
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