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Events and general points (in Hindi)
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Mutually exclusive and exhaustive events, general points about value of Probability and limits of Probability, compliment of an event and solved examples for iit jee maths

## Jagat Chaudhary is teaching live on Unacademy Plus

U
sir please give the guidence on CAPF AC exam
laplace's principle?????????
sir hmko kuch samgh me ni aa rha hai
Kk
sir ans is 1/10?
1. IIT-JEE (main +Advanced) Probability On

2. Equally likely Events:

3. Equally likely Events: Events are said to be equally likely, when No particular event has a preference to occur in relation to other event.

4. Equally likely Events: Events are said to be equally likely, whe particular event has a preference to occur in relation to othe event. Example: Experiment is Dice is rolled. E1: Getting face 1 then P(E1)-1/6 E2: Getting face 2 then P(E2)-1/6

5. Equally likely Events: Events are said to be equally likely, when No particular event has a preference to occur in relation to other event. Example: Experiment is Dice is rolled. E1: Getting face 1 then P(E1)-1/6 E2: Getting face 2 then P(E2)-1/6 Then E1 and E2 are equally likely

6. Equally likely Events: Events are said to be equally likely, when No particular event has a preference to occur in relation to other event. Example: Experiment is Dice is rolled. E1: Getting face 1 then P(E1)-1/6 E2: Getting face 2 then P(E2)-1/6 Then E1 and E2 are equally likely Mutuallv Exclusive Events;

7. Equally likely Events: Events are said to be equally likely, when No particular event has a preference to occur in relation to other event. Example: Experiment is Dice is rolled. E1: Getting face 1 then P(E1)-1/6 E2: Getting face 2 then P(E2)-1/6 Then E1 and E2 are equally likely Mutually Exclusive Events:Events are said to be mutually excusive, if their Simultaneous occurrence is impossible.

8. Equally likely Events: Events are said to be equally likely, when No particular event has a preference to occur in relation to other event Example: Experiment is Dice is rolled. E1: Getting face 1 then P(E1)-1/6 E2: Getting face 2 then P(E2)-1/6 Then E1 and E2 are equally likely Mutually Exclusive Events:Events are said to be mutually excusive, if their Simultaneous occurrence is impossible. Example: E,: Throwing a total of 7 when two Different Dice are rolled. E2 : Throwing a total of 11when two Different Dice are rolled.

9. Example: Experiment is Dice is rolled. E1: Getting face 1 then P(E1)-1/6 E2: Getting face 2 then P(E2)-1/6 Then E1 and E2 are equally likely Mutually Exclusive Events: Events are said to be mutually excusive, i their Simultaneous occurrence is impossible. Example E1: Throwing a total of 7 when two Different Dice are rolled. E2 Throwing a total of 11when two Different Dice are rolled. Yes these are mutually exclusive.

10. particular event has a preference to occur in relation to other event. Example: Experiment is Dice is rolled. E1: Getting face 1 then P(E1)-1/6 E2: Getting face 2 then P(E2)-1/6 Then E1 and E2 are equally likely Mutually Exclusive Events: Events are said to be mutually excusive, if their Simultaneous occurance is impossible Example E1: Throwing a total of 7 when two Different Dice are rolled. E2 : Throwing a total of 11when two Different Dice are rolled. Yes these are mutually exclusive. A : Getting a doublet B: Sum is 10

11. Equally likely Events: Events are said to be equally likely, when No particular event has a preference to occur in relation to other event. Example: Experiment is Dice is rolled. E1: Getting face 1 then P(E1)-1/6 E2: Getting face 2 then P(E2)-1/6 Then E1 and E2 are equally likely Mutually Exclusive Events: Events are said to be mutually excusive, if their Simultaneous occurance is impossible. Example:E1: Throwing a total of 7 when two Different Dice are rolled. E2 Throwing a total of 11when two Different Dice are rolled. Yes these are mutually exclusive. A : Getting a doublet B: Sum is 10 This is not mutually exclusive

12. Mutually exclusive / disjoint/ incompatible events: Two events are said to be mutually exclusive if occurrence of one of them rejects the possibility o occurrence of the other i.e. both cannot occur simultaneously. In the vein diagram the events A and B are mutually exclusive. Mathematically, we write Events A1, A2, , A"n are said to be mutually exclusive events iff AinA=ovi, j e {1, 2, , n} where i # j

13. Mutually Exhaustive events: Event as a consequence of an experimental perforamance are said to be exhaustive if nothing beyond those listed in the set of Possible outcomes/ Sample space can occur.

14. General Points:

15. General Points: 1. Probability of a sure event is 1 Example: Probability of getting either head or tail whena coin is tossed 2. Probability of an impossible event is zero.

16. General Points: 1. Probability of a sure event is 1 Example: Probability of getting either head or tail when a coin is tossed 2. Probability of an impossible event is zero. Example Probability of getting 6 when a coin is tossed.

17. General Points: 1. Probability of a sure event is 1 Example: Probability of getting either head or tail when a co tossed 2. Probability of an impossible event is zero Example Probability of getting 6 when a coin is tossed. 3. Consider two events A and B which are mutually exclusive occurrence of both simultaneously is Impossible.

18. General Points: 1. Probability of a sure event is 1 Example: Probability of getting either head or tail when a co tossed 2. Probability of an impossible event is zero Example Probability of getting 6 when a coin is tossed 3. Consider two events A and B which are mutually exclusive occurrence of both simultaneously is Impossible. Then probability is zero because n(ATB)-O 4. A and B are exhaustive defined on a sample space then

19. General Points; 1. Probability of a sure event is 1 Example: Probability of getting either head or tail when a co tossed 2. Probability of an impossible event is zero Example Probability of getting 6 when a coin is tossed 3. Consider two events A and B which are mutually exclusive occurrence of both simultaneously is Impossible. Then probability is zero because n(ANB)-O 4. A and B are exhaustive defined on a sample space then P(AUB)-1

21. Addition theorem of probability: If 'A' and 'B' are any two events associated with an experiment, then P(AuB) P(A) P(B) P(AnB) De Morgan's laws : If A & B are two subsets of a universal set U, then

22. Ques: An old man while dialing a seven digit phone number. After having dialed the first 5 digits, suddenly forgets the last two but he remembered that the last two digits were different. What is the probability that Correct phone number will be dialed

23. Ques: An old man while dialing a seven digit phone number. After having dialed the first 5 digits, suddenly forgets the last two but he remembered that the last two digits were different. What is the probability that Correct phone number will be dialed Sol: We have to check possibility for last two digits

24. Ques: An old man while dialing a seven digit phone number. After having dialed the first 5 digits, suddenly forgets the last two but he remembered that the last two digits were different. What is the probability that Correct phone number will be dialed Sol: We have to check possibility for last two digits total possible outcomes or Sample space have n(S)-10x9-90

25. Ques: An old man while dialing a seven digit phone number. After having dialed the first 5 digits, suddenly forgets the last two but he remembered that the last two digits were different. What is the probability that Correct phone number will be dialed Sol: We have to check possibility for last two digits total possible outcomes or Sample space have n(S)-10x9-90 Correct outcomes n(A)-1 hence P(A)- n(S)

26. Ques: An old man while dialing a seven digit phone number. After having dialed the first 5 digits, suddenly forgets the last two but he remembered that the last two digits were different. What is the probability that Correct phone number will be dialed. Sol: We have to check possibility for last two digits total possible outcomes or Sample space have n(S)-10x9-90 Correct outcomes n(A)-1 hence P(A))1 n(S) 90