📐 NCERT Class 10 Mathematics

Chapter 14: Probability

Complete theory, experimental probability, theoretical probability, classical definition, complementary events, impossible and sure events, playing cards, dice, coins problems, and exercise solutions for CBSE Class 10 Board Exam 2025-26.

📖 Introduction 📝 Key Definitions 📐 Probability Formula 🪙 Coin Problems 🎲 Dice Problems 🃏 Card Problems 🔄 Complementary Events 📝 Solved Examples ⭐ Key Points
📖 Introduction to Probability

Probability is a branch of mathematics that deals with the likelihood or chance of an event occurring. It is used extensively in weather forecasting, games, insurance, stock markets, and many real-life situations.

💡 Two Types of Probability:
  • Experimental Probability: Based on actual experiments and observations. Also called Empirical Probability.
  • Theoretical Probability: Based on logical reasoning without performing experiments. Also called Classical Probability.
📝 Key Definitions

🎯 Random Experiment

An experiment whose outcome cannot be predicted with certainty before it is performed. Example: Tossing a coin, rolling a die.

📊 Sample Space (S)

The set of all possible outcomes of a random experiment. Example: For a coin, S = {H, T}.

🔹 Event (E)

A subset of the sample space. Example: Getting a head when tossing a coin.

🔸 Favourable Outcomes

The number of outcomes that satisfy the event.

✅ Impossible Event

An event that cannot occur. Probability = 0. Example: Getting a 7 on a standard die.

📌 Sure Event

An event that always occurs. Probability = 1. Example: Getting a number ≤ 6 on a die.

📐 Probability Formula (Theoretical)
P(E) = (Number of favourable outcomes) / (Total number of possible outcomes)
P(E) = n(E) / n(S)

where n(E) = number of elements in event E, n(S) = number of elements in sample space S.

📌 Important Properties:
  • 0 ≤ P(E) ≤ 1
  • P(impossible event) = 0
  • P(sure event) = 1
  • Sum of probabilities of all elementary events = 1
🪙 Coin Problems

📌 1 Coin

Sample Space: S = {H, T}
n(S) = 2
P(H) = 1/2, P(T) = 1/2

📌 2 Coins

S = {HH, HT, TH, TT}
n(S) = 4
P(2 heads) = 1/4
P(1 head) = 2/4 = 1/2
P(0 head) = 1/4

📌 3 Coins

S = {HHH, HHT, HTH, THH, HTT, THT, TTH, TTT}
n(S) = 8
P(3 heads) = 1/8
P(at least 2 heads) = 4/8 = 1/2
P(at most 1 head) = 4/8 = 1/2

📝 Example

Three coins are tossed simultaneously. Find the probability of getting exactly two heads.
Solution: Total outcomes = 8. Favorable outcomes: HHT, HTH, THH = 3. P = 3/8.

🎲 Dice Problems

📌 1 Die

S = {1, 2, 3, 4, 5, 6}
n(S) = 6
P(getting 4) = 1/6
P(even number) = 3/6 = 1/2
P(prime number) = 3/6 = 1/2

📌 2 Dice

Total outcomes = 36
Sum = 7 → 6 outcomes: (1,6),(2,5),(3,4),(4,3),(5,2),(6,1) → P=6/36=1/6
Doublets → 6 outcomes: (1,1),(2,2),(3,3),(4,4),(5,5),(6,6) → P=6/36=1/6

📝 Example

Two dice are rolled. Find the probability that the sum of numbers is a prime number.
Solution: Prime sums possible: 2,3,5,7,11. Count outcomes: sum2→1, sum3→2, sum5→4, sum7→6, sum11→2. Total favorable = 15. P = 15/36 = 5/12.

🃏 Card Problems

A standard deck of 52 playing cards has:

📝 Example

One card is drawn from a well-shuffled deck of 52 cards. Find the probability of getting:
(i) a king → 4/52 = 1/13
(ii) a red card → 26/52 = 1/2
(iii) a face card → 12/52 = 3/13
(iv) a spade → 13/52 = 1/4

🔄 Complementary Events
P(E) + P(not E) = 1
P(not E) = 1 - P(E)

If the probability of an event occurring is P(E), then the probability of that event NOT occurring is 1 - P(E).

📝 Example

If the probability of raining tomorrow is 0.35, what is the probability of no rain?
Solution: P(no rain) = 1 - 0.35 = 0.65

📝 NCERT Solved Examples (Detailed)

🔹 Example 1 (Coin)

Question: A coin is tossed 1000 times with the following frequencies: Head = 455, Tail = 545. Find the probability of getting a head.

Solution: P(H) = 455/1000 = 0.455 (Experimental Probability)

🔹 Example 2 (Die)

Question: A die is thrown once. Find the probability of getting (i) an even number, (ii) a number greater than 4.

Solution: S = {1,2,3,4,5,6}.
Even numbers: 2,4,6 → P = 3/6 = 1/2.
Number > 4: 5,6 → P = 2/6 = 1/3.

🔹 Example 3 (Cards - Board PYQ)

Question: One card is drawn from a well-shuffled deck of 52 cards. Find the probability of drawing a face card or a red card.

Solution: Face cards = 12, Red cards = 26. Red face cards = 6 (2 per red suit).
P(Face or Red) = (12 + 26 - 6)/52 = 32/52 = 8/13.

🔹 Example 4 (Two Dice)

Question: Two dice are thrown together. Find the probability that the product of the numbers is 6.

Solution: Total outcomes = 36. Favorable: (1,6),(2,3),(3,2),(6,1) = 4. P = 4/36 = 1/9.

🔹 Example 5 (Complementary)

Question: The probability of winning a game is 0.25. What is the probability of losing the game?

Solution: P(losing) = 1 - 0.25 = 0.75.

Key Points for Board Exam (Quick Revision)

📌 Important Probabilities to Remember

SituationSample Space (n(S))Example
1 Coin2P(H) = 1/2
2 Coins4P(1 Head) = 1/2
3 Coins8P(All Heads) = 1/8
1 Die6P(4) = 1/6
2 Dice36P(Sum 7) = 1/6
52 Cards52P(King) = 1/13
⚠️ Important Points to Remember:
  • Probability always lies between 0 and 1 (inclusive).
  • The sum of probabilities of all elementary events = 1.
  • P(E) = 1 - P(not E) for complementary events.
  • For "at least one" problems, use P(at least one) = 1 - P(none).
  • For "or" events: P(A or B) = P(A) + P(B) - P(A and B).
  • For "and" events (independent): P(A and B) = P(A) × P(B).
  • Playing cards: 4 suits × 13 cards each = 52 cards.
  • Face cards: J, Q, K (3 per suit × 4 = 12).
  • Number cards: 2 to 10 (9 per suit × 4 = 36).
  • Aces: 4 cards.
📌 P(E) = Favourable Outcomes / Total Outcomes | 0 ≤ P(E) ≤ 1 | P(E) + P(not E) = 1
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