🎲 Maths Class 9 NCERT Lesson 7 The Mathematics of Maybe: Probability Special Edition for Easy Learning

What is inside?

📝 Section 1 — Classroom Notes

🌎 Real-World Hook: Have you ever played Ludo or snakes and ladders? Every roll of a dice is a probability event! Weather forecasts say "70% chance of rain" — that is probability. Insurance companies, doctors, sports analysts, and stock market traders all use probability every single day. Even when your phone shows "Do you want to see more of this?" — it is using probability to guess what you like! Probability is the science of measuring chance, and it is all around us.

Topic 1: What is Probability?

Topic 2: What is Randomness?

Topic 3: The Probability Scale

Topic 4: Experimental Probability

Experimental P = times event happened ÷ total trials

Topic 5: Theoretical Probability

P(event) = favourable outcomes ÷ total outcomes

Topic 6: Sample Space

Topic 7: Events

Topic 8: Tree Diagrams

Topic 9: The Probability Formula

0 ≤ P(E) ≤ 1

Topic 10: Gambler's Fallacy

🎨 Section 2 — Illustrations

Picture 1: The Probability Scale

The Probability Scale 0 0.25 0.5 0.75 1 Impossible (never) Less Likely (rare) Even Chance (50-50) More Likely (probable) Certain (always) Coin flip: P(Heads) = 0.5    |    Die roll: P(6) = 1/6 ≈ 0.17

Probability is measured on a scale from 0 (impossible) to 1 (certain).

Picture 2: Tossing a Coin

Tossing a Fair Coin H Heads T Tails P(H) = 1/2 P(T) = 1/2 Sample Space: S = { H , T }

A fair coin has two equally likely outcomes: Heads or Tails.

Picture 3: Rolling a Die

Rolling a Fair Die: 6 Outcomes 1 2 3 4 5 6 Each face has the same chance: P = 1/6 Sample Space: S = { 1 , 2 , 3 , 4 , 5 , 6 } P(even number) = {2, 4, 6} = 3 out of 6 = 1/2 P(number > 4) = {5, 6} = 2 out of 6 = 1/3

A fair die has 6 equally likely outcomes. Each has probability 1/6.

Picture 4: Tree Diagram (Two Coin Tosses)

Tree Diagram: Toss a Coin Twice Start H (1/2) T (1/2) H T H T H T HH HT TH TT P = 1/4 P = 1/4 P = 1/4 P = 1/4 4 outcomes: HH, HT, TH, TT. Each P = 1/4 P(at least 1 head) = 3/4 = 0.75

A tree diagram shows every possible outcome step by step.

Picture 5: Picking from a Bag

Picking a Ball from a Bag R R R B B Bag: 3 Red + 2 Blue = 5 balls P(Red) = 3/5 = 0.6 = 60% P(Blue) = 2/5 = 0.4 = 40%

3 red and 2 blue balls. P(Red) = 3/5 because 3 out of 5 are red.

📐 Section 3 — Worked Examples

Example 1: Theoretical Probability (Die)

A fair die is rolled once.

Find the probability of getting a 4.

1 Write the sample space: S = {1, 2, 3, 4, 5, 6}.
2 Total outcomes = 6.
3 Favourable outcome = getting 4. Count = 1.
4 P(4) = favourable ÷ total = 1 ÷ 6
P(4) = 1/6 ≈ 0.17

P = favourable outcomes ÷ total outcomes

Example 2: Experimental Probability (Coin)

A coin is tossed 50 times.

Heads came 22 times. Find P(Heads).

1 Count times event happened = 22.
2 Total trials = 50.
3 P(H) = 22 ÷ 50
4 Simplify: 22/50 = 11/25 = 0.44
P(Heads) = 22/50 = 0.44 = 44%

Experimental P = event count ÷ total trials

Example 3: Tree Diagram (Two Coins)

Two coins are tossed together.

Find P(at least one head).

1 Draw tree: first coin H or T, second coin H or T.
2 All outcomes: HH, HT, TH, TT. Total = 4.
3 "At least one head" = HH, HT, TH. Count = 3.
4 P = 3 ÷ 4 = 3/4 = 0.75
P(at least one head) = 3/4 = 75%

List all outcomes, then count the ones you want

📋 Section 4 — Cheat Sheet

Word / RuleWhat It Means
ProbabilityHow likely an event is. Number from 0 to 1
RandomCannot predict exactly what will happen
Sample space (S)Set of ALL possible outcomes
EventOne or more outcomes you care about
OutcomeOne single result of an experiment
Equally likelyAll outcomes have the same chance
Experimental PEvent count ÷ total trials (from doing it)
Theoretical PFavourable ÷ total (from logic)
P = 0Impossible. Can never happen
P = 1Certain. Will always happen
Tree diagramShows all outcomes of multi-step experiments
Gambler's FallacyWrong belief that past changes future chances

✏️ Section 5 — Handout

A. Fill in the Blanks

1. Probability is measured on a scale from ________ to ________.

2. The set of all possible outcomes is called the ________.

3. Experimental P = times event happened ÷ ________.

4. If an event is certain, its probability = ________.

5. Each face of a fair die has probability ________.

B. True or False

1. Probability can be more than 1. ________

2. A fair coin has two equally likely outcomes. ________

3. If you get heads 5 times, tails is more likely next. ________

4. Sample space of a die = {1, 2, 3, 4, 5, 6}. ________

C. Solve

1. A bag has 4 red and 6 blue balls.

Find P(red ball).

Show your work here

2. A die is rolled 30 times. Number 6 came 8 times.

Find the experimental P(6).

Show your work here

D. Match the Columns

1. P = 0 — (a) Even chance

2. P = 1/2 — (b) Impossible

3. P = 1 — (c) Less likely

4. P = 1/6 — (d) Certain

E. Draw and Label

Draw a tree diagram for tossing one coin twice.

List all 4 outcomes.

Draw your tree diagram here

✅ Detailed Solutions — Handout Practice

✓ A. Fill in the Blanks — Answers

1 Probability is measured on a scale from 0 to 1. (0 = impossible, 1 = certain)
2 The set of all possible outcomes is called the sample space.
3 Experimental P = times event happened ÷ total number of trials.
4 If an event is certain, its probability = 1.
5 Each face of a fair die has probability 1/6. (1 out of 6 equally likely outcomes)
🏆 Answers: (1) 0 to 1   (2) sample space   (3) total trials   (4) 1   (5) 1/6

✓ B. True or False — Answers

1 "Probability can be more than 1." → FALSE. Probability is always between 0 and 1 (inclusive). P = 0 means impossible; P = 1 means certain.
2 "A fair coin has two equally likely outcomes." → TRUE. Heads and tails are equally likely, each with P = 1/2.
3 "If you get heads 5 times, tails is more likely next." → FALSE. This is the gambler's fallacy! Each coin toss is independent. P(tails) = 1/2 every single time.
4 "Sample space of a die = {1, 2, 3, 4, 5, 6}." → TRUE. A standard die has 6 faces.
🏆 Answers: (1) False   (2) True   (3) False   (4) True

✓ C. Problem 1: Bag with 4 red and 6 blue balls. Find P(red ball).

1 Total balls: 4 red + 6 blue = 10 balls.
2 Favourable outcomes (red ball): 4.
3 Formula: P(red) = Favourable ÷ Total = 4 ÷ 10 = 2/5.
🏆 Answer: P(red ball) = 4/10 = 2/5 = 0.4 = 40%.

✓ C. Problem 2: Die rolled 30 times; 6 came up 8 times. Find experimental P(6).

1 Total trials (rolls): 30.
2 Times 6 appeared: 8.
3 Experimental probability formula: P = Number of times event occurred ÷ Total trials.
4 Calculate: P(6) = 8/30 = 4/15.
🏆 Answer: Experimental P(6) = 8/30 = 4/15 ≈ 0.267.

💡 Compare: Theoretical P(6) = 1/6 ≈ 0.167. In 30 rolls, the experimental result differs — this is normal! As we roll more times, experimental probability gets closer to 1/6.

✓ E. Tree Diagram for Tossing a Coin Twice

The 4 outcomes when a coin is tossed twice:

1 First toss Heads, Second toss Heads → HH
2 First toss Heads, Second toss Tails → HT
3 First toss Tails, Second toss Heads → TH
4 First toss Tails, Second toss Tails → TT
🏆 Sample space = {HH, HT, TH, TT} — 4 equally likely outcomes.

💡 P(exactly one head) = 2/4 = 1/2.   P(both heads) = 1/4.   P(at least one head) = 3/4.

🃏 Section 6 — Revision Flashcards

Front
What is probability?
Back

A measure of how likely an event is. Scale from 0 to 1.

Front
What is a random event?
Back

You cannot predict exactly what will happen.

Front
What is the sample space?
Back

The set of ALL possible outcomes. Die: {1,2,3,4,5,6}.

Front
Experimental probability formula?
Back

Times event happened ÷ total trials. Based on doing it.

Front
Theoretical probability formula?
Back

Favourable outcomes ÷ total outcomes. Based on logic.

Front
P(impossible event)?
Back

P = 0. It can never happen.

Front
P(certain event)?
Back

P = 1. It will always happen.

Front
What is Gambler's Fallacy?
Back

Wrong belief that past results change future chances. They don't!

🧠 Section 7 — Mind Map

PROBABILITY Chapter 7 What is Probability? Measures how likely an event is (0 to 1) Randomness Can't predict exactly what will happen Probability Scale 0 = impossible 1 = certain Experimental P Event count ÷ total trials From doing experiments Theoretical P Favourable ÷ total From logic, no experiment Sample Space All possible outcomes Coin: {H, T} Die: {1-6} Events Subset of sample space "Even number" = {2, 4, 6} Tree Diagrams Multi-step experiments Shows every path

All the key ideas about probability in one picture.