Probability Basics Rules – CBSE 10th boards

Probability

1. Definition of Probability

Probability of an event is defined as: where:

  • is the probability of event .
  • Favorable outcomes are the outcomes that satisfy the event .
  • Total outcomes are the total number of possible outcomes in the experiment.

2. Sample Space (S)

The set of all possible outcomes of a random experiment is called the sample space. For example:

  • Tossing a coin:
  • Rolling a die:

3. Event

An event is a subset of the sample space. For example, when rolling a die, getting an even number () is an event.

Important Points to Remember

  • Probability always lies between 0 and 1, inclusive: .

  • Probability of an impossible event is 0.

  • Probability of a sure event is 1.

Probability : Solved Examples

Example 1: Tossing a Coin

A coin is tossed once. What is the probability of getting a head?

Solution:

  1. Sample space:

  2. Total outcomes = 2

  3. Favorable outcomes (Head) = 1

Example 2: Rolling a Die

A die is rolled once. What is the probability of getting a number greater than 4?

Solution:

  1. Sample space:

  2. Total outcomes = 6

  3. Favorable outcomes ({5, 6}) = 2

Example 3: Drawing a Card

A card is drawn from a standard deck of 52 cards. What is the probability of drawing a king?

Solution:

  1. Total outcomes = 52

  2. Favorable outcomes (Kings) = 4

Structure of a Standard Deck

  1. Total Cards: 52 cards
  2. Suits: 4 suits (Hearts, Diamonds, Clubs, Spades) with 13 cards in each suit.
    • Hearts and Diamonds are red.
    • Clubs and Spades are black.
  3. Ranks: Each suit contains:
    • Number cards: 2 through 10
    • Face cards: Jack, Queen, King
    • Ace

Applications in Probability

  1. Basic Probability Concepts

    • Single Event Probability: Calculating the chance of drawing a specific card, such as an Ace or a Heart. P(Event)=Number of favorable outcomes/Total outcomes
    •  Example: Probability of drawing an Ace = 4/52=1/13
  2. Compound Events

    • Independent Events: Drawing a card, replacing it, and drawing again.
    • Dependent Events: Drawing a card, not replacing it, and drawing again. Example: Probability of drawing two Aces without replacement:
    P(2 Aces)=4/52×3/51
  3. Complementary Events

    • Probability of an event not happening. Example: Probability of not drawing a Heart = 1−13/52=39/52
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