Which one of the following is NOT a condition of the binomial distribution?
Click on the arrows to vote for the correct answer
A. B. C. D. E.D
There no requirement regarding the number of observations.
The correct answer is (D) At least 10 observations.
The binomial distribution is a discrete probability distribution that describes the number of successes in a fixed number of independent Bernoulli trials, where each trial has two possible outcomes: success or failure. It is characterized by three conditions:
A. Independent trials: The trials must be independent of each other, meaning that the outcome of one trial does not affect the outcome of another trial. In other words, the probability of success or failure in one trial does not change based on the results of previous trials.
B. Only two outcomes: Each trial can result in one of two possible outcomes, typically referred to as success (S) and failure (F). These outcomes are mutually exclusive, meaning that only one of them can occur in each trial.
C. Probability of success remains constant from trial to trial: The probability of success (denoted as p) remains the same for each trial. Similarly, the probability of failure (denoted as q = 1 - p) remains constant.
D. At least 10 observations: This statement is not a condition of the binomial distribution. The number of observations or trials can be any positive integer, and there is no specific requirement for a minimum number of observations in order for a distribution to be considered binomial.
Therefore, option (D) is the correct answer as it is not a condition of the binomial distribution. The conditions of the binomial distribution are (A) Independent trials, (B) Only two outcomes, and (C) Probability of success remains constant from trial to trial.