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Independent Events and Their Important Properties | Mathematics (Maths) Class 12 - JEE PDF Download

Independent Events

Two events A & B are said to be independent if occurrence or non occurrence of one does not effect the probability of the occurrence or non occurence of other.

(a) If the occurrence of one event affects the probability of the occurrence of the other event then the events are said to be dependent or Contingent. For two independent events A and B 

Independent Events and Their Important Properties | Mathematics (Maths) Class 12 - JEE

. P(B). Often this is taken as the definition of independent events.

(b) Three events A, B & C are independent if & only if all the following conditions hold ;

Independent Events and Their Important Properties | Mathematics (Maths) Class 12 - JEE

i.e., they must be pairwise as well as mutually independent.

Similarly for n events A1, A2, A3, ........... An to be independent, the number of these conditions is equal to nC2 + nC3 + ............. + nCn = 2n - n - 1.

Note : Independent events are not in general mutually exclusive & vice versa.

Mutually exclusiveness can be used when the events are taken from the same experiment & independence can be used when the events are taken from different experiments.

Ex.1 The probability that an anti aircraft gun can hit an enemy plane at the first, second and third shot are 0.6, 0.7 and 0.1 respectively. The probability that the gun hits the plane is

Sol. Let the events of hitting the enemy plane at the first, second and third shot are respectively A, B and C. Then as given P(A) = 0.6, P(B) = 0.7, P(C) = 0.1

Since events A, B, C are independent, so

Independent Events and Their Important Properties | Mathematics (Maths) Class 12 - JEE

⇒ 

Independent Events and Their Important Properties | Mathematics (Maths) Class 12 - JEE

    

Independent Events and Their Important Properties | Mathematics (Maths) Class 12 - JEE

= 1 - (1 - 0.6) (1 - 0.7) (1 - 0.1)) = 1 - (0.4)(0.3)(0.9) = 1 - 0.108 = 0.892

 

Ex.2 If two events A and B are such that 

Independent Events and Their Important Properties | Mathematics (Maths) Class 12 - JEE

, P(B) = 0.4 and 

Independent Events and Their Important Properties | Mathematics (Maths) Class 12 - JEE

then 

Independent Events and Their Important Properties | Mathematics (Maths) Class 12 - JEE

equals

Sol.

Independent Events and Their Important Properties | Mathematics (Maths) Class 12 - JEE

 

 Probability of Three Events

Independent Events and Their Important Properties | Mathematics (Maths) Class 12 - JEE

For any three events A, B and C we have

(a) P(A or B or C) = P(A) + P(B) + P(C) – P(A∩B) – P(B ∩ C) – P(C ∩ A) + P(A ∩ B ∩ C)

(b) P (at least two of A, B, C occur) = P(B ∩ C) + P (C ∩ A) + P(A ∩ B) – 2P (A ∩ B ∩ C)

(c) P (exactly two of A, B, C occur) = P(B ∩ C) + P (C ∩ A) + P(A ∩ B) – 3P (A ∩ B ∩ C)

(d) P (exactly one of A, B, C occurs) = P(A) + P(B) + P(C) – 2P (B ∩ C) – 2P (C ∩ A) – 2P (A ∩ B) + 3P (A ∩ B ∩ C)

The document Independent Events and Their Important Properties | Mathematics (Maths) Class 12 - JEE is a part of the JEE Course Mathematics (Maths) Class 12.
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FAQs on Independent Events and Their Important Properties - Mathematics (Maths) Class 12 - JEE

1. What are independent events in probability theory?
Ans. Independent events in probability theory are events that do not affect each other's probabilities. The occurrence or non-occurrence of one event does not have any impact on the occurrence or non-occurrence of the other event. In other words, the probability of one event happening remains the same regardless of whether the other event happens or not.
2. What are some important properties of independent events?
Ans. The important properties of independent events are: 1. Multiplication Rule: The probability of the intersection of two or more independent events is equal to the product of their individual probabilities. 2. Addition Rule: The probability of the union of two or more independent events is equal to the sum of their individual probabilities. 3. Complement Rule: The probability of an event and its complement being independent is equal to the probability of the event multiplied by the probability of its complement. 4. Conditional Probability: The conditional probability of an event, given that another event has already occurred, remains the same as the original probability of the event. 5. Transitive Property: If event A is independent of event B, and event B is independent of event C, then event A is also independent of event C.
3. How can the multiplication rule be used to calculate the probability of independent events?
Ans. The multiplication rule states that the probability of the intersection of two independent events is equal to the product of their individual probabilities. To calculate the probability of independent events, you simply multiply the probabilities of each event occurring. For example, if the probability of event A is 0.3 and the probability of event B is 0.5, the probability of both events A and B occurring would be 0.3 * 0.5 = 0.15.
4. Can events that are mutually exclusive also be independent?
Ans. No, events that are mutually exclusive cannot be independent. Mutually exclusive events are events that cannot happen at the same time. If two events are mutually exclusive, the occurrence of one event automatically eliminates the possibility of the other event occurring. In contrast, independent events are events that do not affect each other's probabilities, meaning the occurrence or non-occurrence of one event does not impact the occurrence or non-occurrence of the other event. Therefore, mutually exclusive events cannot be independent.
5. How can the concept of independent events be applied in real-life scenarios?
Ans. The concept of independent events is widely applicable in various real-life scenarios. For example: 1. Weather forecasting: The occurrence of rain on one day does not affect the probability of rain on the next day. Each day's weather is considered an independent event. 2. Gambling: In games like roulette or flipping a coin, each spin or flip is considered an independent event, and the outcome of one spin or flip does not affect the probabilities of subsequent spins or flips. 3. Medical testing: The accuracy of medical tests is often based on the assumption that the occurrence of a certain medical condition is independent of the test results. 4. Sports: The outcome of one game in a series does not impact the outcome of the next game if the teams are evenly matched, making each game an independent event. 5. Stock market analysis: The performance of one stock on a particular day does not impact the performance of another stock, assuming they are not influenced by common factors. Each stock's performance can be considered an independent event.
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