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Probability
Probability
 In our daily life the “Probability” or Chance” is very commonly
used term simple say that Something, we used to say “Probably it
may rain tomorrow”.
 Probability simple mean chances or Guess.
 Probability is the measure of the chance that an event like occur
in a random experiment. The Chances of event like outcome of
experiment and occurrence like chance.
Examples
 Match
 I think there is a 60% chance of rain tomorrow.
 Coin like (Head, Tail)
Important Terms/Concept used in Probability
 Experiment
 Outcome
 Sample space
 Favorable event
 Trial
Experiment
 Any Method or Way for which more than one outcome.
Outcome
 A possible result of a random experiment is Known as Outcome.
Sample Space
 The collection of all the outcome in a trial. It is an experiment is
a set containing of all the possible experimental outcome.
 Total number of outcome or All Possible outcome is called
Sample Space.
 Example:
 Sample space is (Head, Tail)
 Coin = (H,T) = 2
Trial
 Number of Times, event will be perform or achieve or carry out.
 A single performance of an experiment or Research is called
Trial.
Favorable event
 Event basically experiment, or one event/ perform are called
event.
 One or more event is an experiment is Favorable Event
 favorable outcome
 Example:
 Coin = 1
 Even number in Dice = 3
Formula
P =
P = , P =
Examples
A = favorable outcome
S = total outcome
n = Total Number
Example # 1
 Question:
 Total event(H,T) = 2
 How many chance of H
 Solution:
 P = no of favorable outcome/Total possible outcome
 P(H) = ½ = 0.5 = 50%
 P(T) = ½ = 0.5 = 50%
Example # 2, Dice
 Question:
Who many chance of 1?
What is probability of 1?
 Solution:
Total event = 6
No of 1 = 1
P(1) = 1/6 = 0.16 = 16%
P(6) = 1/6 = 0.16 = 16%
Cont.….
Question:
 Dice
 Solution:
 What is P (1 or 6)
 P(1 or 6) = 2/6 = 1/3 = 0.33 = 33
 P(1 and 6) = 0/6 = 0
 P(even) = 3/6 = 0.5
 P(odd) = 3/6 = 0.5
Types of Probability
Objective Probability
• Classical Probability
• Relative Frequency
Subjective probability
Approaches to
Probability
Objective
Classical
Probability
Relative
Frequency
Subjective
Based on
Available
information
Objective Probability
Probabilities that can be stated before occurrence of an
event.
 Example:
Roll of Fair Dice
Subjective Probability
 Subjective Probability is based on the experience and
judgment of the person making the estimate.
 It based on what a person on what person believes or
experiences
 Example:
 I think there is a 60% chance of rain tomorrow.
Relative Frequency
 Typically based on Historical data and Simply say that the
random experiment is repeated a large number of times.
P(Event) =
Classical Probability
 A classical approach to probability often involves coin tossing
and rolling dice. It is calculated by listing all of the possible
outcomes of the activity and recording the actual occurrences.
 Example:
 For Examples, if you are tossing a coin, the possible outcomes
are either heads or tails.
THANK YOU!

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Probability and its Types with easy Examples

  • 2. Probability  In our daily life the “Probability” or Chance” is very commonly used term simple say that Something, we used to say “Probably it may rain tomorrow”.  Probability simple mean chances or Guess.  Probability is the measure of the chance that an event like occur in a random experiment. The Chances of event like outcome of experiment and occurrence like chance.
  • 3. Examples  Match  I think there is a 60% chance of rain tomorrow.  Coin like (Head, Tail)
  • 4. Important Terms/Concept used in Probability  Experiment  Outcome  Sample space  Favorable event  Trial
  • 5. Experiment  Any Method or Way for which more than one outcome. Outcome  A possible result of a random experiment is Known as Outcome.
  • 6. Sample Space  The collection of all the outcome in a trial. It is an experiment is a set containing of all the possible experimental outcome.  Total number of outcome or All Possible outcome is called Sample Space.  Example:  Sample space is (Head, Tail)  Coin = (H,T) = 2
  • 7. Trial  Number of Times, event will be perform or achieve or carry out.  A single performance of an experiment or Research is called Trial.
  • 8. Favorable event  Event basically experiment, or one event/ perform are called event.  One or more event is an experiment is Favorable Event  favorable outcome  Example:  Coin = 1  Even number in Dice = 3
  • 10. Examples A = favorable outcome S = total outcome n = Total Number
  • 11. Example # 1  Question:  Total event(H,T) = 2  How many chance of H  Solution:  P = no of favorable outcome/Total possible outcome  P(H) = ½ = 0.5 = 50%  P(T) = ½ = 0.5 = 50%
  • 12. Example # 2, Dice  Question: Who many chance of 1? What is probability of 1?  Solution: Total event = 6 No of 1 = 1 P(1) = 1/6 = 0.16 = 16% P(6) = 1/6 = 0.16 = 16%
  • 13. Cont.…. Question:  Dice  Solution:  What is P (1 or 6)  P(1 or 6) = 2/6 = 1/3 = 0.33 = 33  P(1 and 6) = 0/6 = 0  P(even) = 3/6 = 0.5  P(odd) = 3/6 = 0.5
  • 14. Types of Probability Objective Probability • Classical Probability • Relative Frequency Subjective probability
  • 16. Objective Probability Probabilities that can be stated before occurrence of an event.  Example: Roll of Fair Dice
  • 17. Subjective Probability  Subjective Probability is based on the experience and judgment of the person making the estimate.  It based on what a person on what person believes or experiences  Example:  I think there is a 60% chance of rain tomorrow.
  • 18. Relative Frequency  Typically based on Historical data and Simply say that the random experiment is repeated a large number of times. P(Event) =
  • 19. Classical Probability  A classical approach to probability often involves coin tossing and rolling dice. It is calculated by listing all of the possible outcomes of the activity and recording the actual occurrences.  Example:  For Examples, if you are tossing a coin, the possible outcomes are either heads or tails.