Probability

Probability

1. Probability of Events

   • Sum
     • Sum of the probability of all events is always one e.g. Suppose these are n events corresponding to a random experiment, them P(E1) + P(E2) +P(E3) + ---- P(En) =1
   • Complimentary Event
     • P(E) + P(E) =1 or P(E) =1-P(E) here, P(E) =P(not(E)= complimentary events
   • Certain event or sure event
     • Probability of an event is equal to 1
   • Impossible event
     • Probability of an event is equal to 0

2. Types

   • Empirical Probability
     • When probability is based on an actual experiment suppose event E is happen, when experiment is performed, then P(E) = No. of times event E occurs / Number of times the experiment was performed
   • Measurement Probability
     • When repetition of an experiment can be avoided for exact probability. Therefore P(E) = No. of favourable outcomes / Total number of all possible outcomes
   • Classical Probability
     • Probability of an event denotes likelihood of its happening. therefore P(E) = No. of event favourable / Total number of all possible event

3. Random Experiment

   • Random Experiment may result in two or more outcomes e.g. i) tossing a coin ii) throwing a dice

4. Sample Space

   • Set of all possible outcomes of an experiment

5. Event

   • An outcome of a random experiment or an event is something that happens

6. Equally likely events

   • The different outcomes have the same as equal chance of occurrence

7. Probability of any event can never be less than 0 and not more than 1. 0 < P(E) < 1