Which of the following conditions is not a condition that n-fold bernoulli trials needs to meet?

Question

Options

• AEach test was repeated under the same conditions.
• BThere are only two possible outcomes for each trial, i.e. event A occurs and event A does not
• CEach test itself is obeying normal distribution
• DThe results of each trial are independent of each other.

• A
  5% (2)
• B
  17% (7)
• C
  69% (29)
• D
  10% (4)

Explanation

Option C is correct because Bernoulli trials are defined by a binomial distribution, not a normal distribution - each individual trial follows a Bernoulli distribution (a binary outcome), and the number of successes across n trials follows a binomial distribution. Normal distribution is simply not part of the definition and is irrelevant to whether an experiment qualifies as Bernoulli trials.

Options A, B, and D are all genuine requirements: A (same conditions) ensures the probability of success remains constant across trials; B (two possible outcomes) is the defining characteristic of a Bernoulli trial; and D (independence) ensures that the result of one trial does not influence another, which is essential for the binomial probability formula to hold.

Memory tip: Think of flipping a fair coin repeatedly - same coin every flip (A), only heads or tails (B), each flip unaffected by the last (D). Nothing about that setup requires a bell curve, which is why C is the odd one out.

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