Mathematics · Chapter 7 · Part II
Probability Distributions
Conditional probability, Bayes theorem, random variables, binomial distribution — Maharashtra HSC Maths Part II Ch 7 & 8
12 formulas · 3 solved examples · 5 practice questions · Board weight: 6 marks · Maharashtra State Board Class 12 · 2025–26 syllabus
Board Exam Tips
- →Bayes theorem numerical (drawing balls from an urn, faulty machines) is a Maharashtra HSC 4-marker every year.
- →Binomial distribution — write PMF P(X = r) = ⁿCr pʳ qⁿ⁻ʳ and compute mean np and variance npq.
- →Random variable — construct probability distribution table, then compute E(X) = Σx·p(x), Var(X) = Σx²·p(x) − [E(X)]².
- →Conditional probability formula P(A|B) = P(A∩B)/P(B) is asked as a 2-marker every year.
- →State whether events are independent (P(A∩B) = P(A)P(B)) before applying formulas.
Formulas(12)
Classical Definition
Addition TheoremBoard favourite
Conditional ProbabilityBoard favourite
Multiplication Theorem
Total Probability TheoremBoard favourite
Bayes TheoremBoard favourite
Probability Distribution of Random VariableBoard favourite
Expectation (mean)Board favourite
Variance and Standard Deviation
Binomial Distribution (PMF)Board favourite
Binomial Mean and Variance
Independence
Solved Examples
A die is rolled. Find the probability that the outcome is (i) an even number, (ii) a prime number.
Sample space: S = {1, 2, 3, 4, 5, 6}, n(S) = 6.
In a factory, machine A produces 60% of the items, machine B produces 40%. Defect rates are 3% and 5% respectively. An item is picked at random and found defective. Find the probability that it was made by A. (Bayes' theorem)
Let A₁ = made by A, A₂ = made by B, D = defective.
A coin is tossed 10 times. Find the probability of getting exactly 6 heads. Also find mean and variance of the number of heads.
Binomial with n = 10, p = 1/2 (fair coin).
Traps & Common Mistakes
- 1
Confusing P(A ∩ B) with P(A|B)
✓P(A|B) = P(A ∩ B)/P(B). They are different — the conditional restricts sample space.
- 2
Assuming events are independent without checking
✓Verify P(A ∩ B) = P(A)P(B). Never assume from context alone.
- 3
Using addition without subtracting intersection when events overlap
✓P(A ∪ B) = P(A) + P(B) − P(A ∩ B). Do not skip the third term unless mutually exclusive.
- 4
Applying binomial when n is not known or trials not independent
✓Binomial requires: fixed n, two outcomes, constant p, independent trials. Check all four.
- 5
Writing Var(X) = E(X²) + [E(X)]² instead of − [E(X)]²
✓Var(X) = E(X²) − [E(X)]². Minus sign is critical.
- 6
Forgetting Σp = 1 when constructing a probability distribution
✓Total column must sum to 1. If not, redo the table — probability of some outcome missed or an error.
Practice Yourself
- Q1
Two cards are drawn without replacement from a standard deck. Find P(both aces).
- Q2
A random variable X has P(X = 0) = 0.4, P(X = 1) = 0.3, P(X = 2) = 0.3. Find E(X).
- Q3
A binomial variable has n = 8, p = 1/3. Find variance.
- Q4
P(A) = 0.4, P(B) = 0.5, P(A ∩ B) = 0.2. Find P(A|B).
- Q5
A basket has 3 red and 5 white balls. Two balls are drawn without replacement. Find P(both same colour).
Notes
Probability Distributions — Maharashtra HSC Overview
Part II Chapter 7 (Probability Distributions — random variables) and Chapter 8 (Binomial Distribution) of the Maharashtra Class 12 Mathematics textbook together cover conditional probability, Bayes theorem, discrete random variables, and binomial distribution.
Maharashtra syllabus specifics
- Bayes theorem numerical — Maharashtra HSC gives at least one 4-mark Bayes problem every year (urn/machine/disease context).
- Probability distribution table + E(X), Var(X) — Balbharati asks it as a 4-marker in every board paper.
- Binomial distribution derivation and mean/variance derivation (E(X) = np, Var(X) = npq) is a 3-marker.
- Random variable and its types — discrete vs continuous, with examples — is a Balbharati staple theoretical question.
Strategy
- Always list the sample space explicitly for simple problems.
- Distinguish P(A|B) from P(A ∩ B) — this is the #1 error in HSC.
- For Bayes problems, list all priors P(A_i) and likelihoods P(B|A_i) BEFORE substituting.
- For binomial distribution, verify n, p, q, independence conditions before applying the PMF.
- Show every step: writing the formula BEFORE substitution earns 1 mark.
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