UGC NET Questions (Paper – 1)

Statements A, B, C and D together summarise the standard relationships between mutually exclusive and independent events. A correctly defines mutual exclusivity as events that cannot happen simultaneously. B properly describes independence in terms of unchanged probabilities. C follows because if two non-trivial events are mutually exclusive, their joint probability is zero and cannot equal the product of positive probabilities, so they are not independent. D restates the formal definition of independence using the product rule. E is false since mutual exclusivity and independence are distinct concepts, so the correct set is A, B, C and D only.

Option A:
Option A is incomplete because it omits D and thus fails to express the formal product definition of independence, even though A, B and C are true. The absence of D makes the description of independence less precise.

Option B:
Option B is correct as it combines the basic definitions and implications about mutual exclusivity and independence and excludes E, which wrongly equates the two. It matches the conceptual treatment of events found in NET-level probability questions.

Option C:
Option C is incorrect because it includes E, the false claim that mutual exclusivity and independence mean the same thing, and leaves out B, which is a core statement about independence. This mixture of error and omission invalidates the option.

Option D:
Option D is wrong as it drops A and includes only B, C and D, leaving out the explicit definition of mutual exclusivity while still not rejecting E. It therefore does not provide the complete and correct set of statements.

Statements A and B are fundamental facts about complements, D describes the multiplication rule for independent events and E is true because working with complements, like “at least one” via “1 − P(none)”, often simplifies calculations. Statement C is false because for mutually exclusive events, P(A and B) = 0, not P(A) + P(B), which is instead P(A or B) for such events. Therefore, the combination A, B, D and E only is correct.

Option A:
Option A is incomplete since it omits E and thus does not state explicitly the strategic advantage of using complementary events to simplify some NET probability questions.

Option B:
Option B is also incomplete because it leaves out D, thereby ignoring the key rule for independent events, which is central to many probability computations. Without D, the treatment of joint events is missing.

Option C:
Option C is wrong because it excludes A and consequently fails to express the basic identity P(A) + P(not A) = 1, and it still does not remove C, the incorrect equality about mutually exclusive events.

Option D:
Option D is correct as it collects all true statements and rejects C, which confuses “and” with “or” probabilities for mutually exclusive events. It represents how complementary and independent events are used in exam-level problems.

B is the definition of independence: P(A ∩ B) = P(A)P(B). C is correct because mutually exclusive events with positive probabilities have P(A ∩ B)=0 but P(A)P(B)>0, so they cannot be independent. D is true because independence carries over to complements. A is false (addition relates to mutually exclusive unions, not independence). E is false because for independent events P(A|B) = P(A), not 0. Therefore B, C and D only are correct.

Option A:
Option A is incomplete because it includes only B and leaves out C and D, which are also correct statements.

Option B:
Option B is correct as it includes exactly the true statements and excludes A and E, which confuse addition/conditional probability with independence.

Option C:
Option C is wrong because it includes E, which misstates conditional probability under independence.

Option D:
Option D is incorrect because it includes A, which is not the criterion for independence.

A is correct because conditional probability measures A given B. B is the definition formula P(A|B) = P(A ∩ B)/P(B) (when P(B) > 0). C is true because Bayes’ theorem is used to update probabilities of hypotheses/causes when evidence is known. D is true for independent events since B does not change the probability of A. E is false because P(A|B) and P(not A|B) are complementary conditional probabilities and must sum to 1, not exceed 1. Therefore, A, B, C and D only are correct.

Option A:
Option A is incomplete because it omits D, which is a key property of independent events (conditioning does not change probability).

Option B:
Option B is correct because it includes all true statements (A, B, C, D) and excludes E, which wrongly claims the sum of complementary conditional probabilities is greater than 1.

Option C:
Option C is incorrect because it includes E (false) and also omits A and D, both of which are true statements about conditional probability and independence.

Option D:
Option D is incorrect because it includes E (false) and excludes B and C, which are fundamental definitions/uses of conditional probability and Bayes’ theorem.