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CBSE
Class 10
Mathematics
Mathematics
Probability

Revision Guide

Probability

Revision Guide

Probability

Probability is a measure of the likelihood that an event will occur, calculated as the ratio of favorable outcomes to the total number of possible outcomes.

Probability - Quick Look Revision Guide

Your 1-page summary of the most exam-relevant takeaways from Mathematics.

This compact guide covers 20 must-know concepts from Probability aligned with Class X preparation for Mathematics. Ideal for last-minute revision or daily review.

Revision Guide

Revision guide

Complete study summary

Essential formulas, key terms, and important concepts for quick reference and revision.

Key Points

1

Define Probability with an example.

Probability measures the likelihood of an event occurring, ranging from 0 (impossible) to 1 (certain). Example: Tossing a fair coin has a probability of 0.5 for heads.

2

Theoretical vs Empirical Probability.

Theoretical probability is based on possible outcomes, while empirical probability is based on actual experiments. Example: Rolling a die theoretically has a 1/6 chance for any number.

3

Probability of sure and impossible events.

A sure event has a probability of 1, and an impossible event has 0. Example: Sun rising is a sure event; a die showing 7 is impossible.

4

Complementary events.

Two events are complementary if one is the negation of the other. P(E) + P(not E) = 1. Example: Drawing a red ball vs not drawing a red ball.

5

Elementary events.

An event with a single outcome. The sum of probabilities of all elementary events in an experiment is 1. Example: Drawing a specific card from a deck.

6

Probability formula.

P(E) = Number of favorable outcomes / Total number of outcomes. Example: Probability of drawing an ace from a deck is 4/52.

7

Equally likely outcomes.

Outcomes with the same chance of occurring. Example: Fair coin toss or die roll.

8

Probability of not E.

P(not E) = 1 - P(E). Useful for finding the probability of the complement of an event.

9

Sum of probabilities.

The sum of probabilities of all possible outcomes of an experiment is always 1.

10

Real-world application: Weather forecasting.

Probability predicts weather events, like the chance of rain, based on historical data and models.

11

Misconception: Probability can be negative.

Probability values range from 0 to 1. Negative values or values greater than 1 are not possible.

12

Memory hack: Use fractions for clarity.

Converting probabilities to fractions can simplify understanding and comparison.

13

Example: Drawing cards.

Probability of drawing a heart from a deck is 13/52 = 1/4, as there are 13 hearts in 52 cards.

14

Probability in games: Dice.

The probability of rolling a sum of 7 with two dice is 6/36 = 1/6, as there are 6 favorable outcomes.

15

Independent events.

The outcome of one event does not affect another. Example: Tossing two coins independently.

16

Mutually exclusive events.

Events that cannot occur simultaneously. Example: Drawing a red or black card from a deck.

17

Probability range.

Always 0 ≤ P(E) ≤ 1. Ensures probabilities are within valid limits.

18

Example: Birthday problem.

Probability two people share a birthday in a room of 23 is about 50%, illustrating non-intuitive probability.

19

Law of large numbers.

As an experiment repeats, the empirical probability approaches the theoretical probability.

20

Probability in genetics.

Used to predict inheritance patterns, like the 3:1 ratio in Mendelian genetics.

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