Answer :
Final answer:
The Large Counts Condition for normal approximation is a principle in statistics that allows a binomial distribution to be approximated by a normal distribution if the number of successes and failures are both at least 10; using a coin flip as an example.
Explanation:
The Large Counts Condition (for normal approximation) is a principle in statistics used for determining if a distribution can be approximated by the normal distribution. It generally states that if the number of successes and the number of failures in a sample are both at least 10, the distribution can be approximated by a normal distribution.
To illustrate, let's consider flipping a fair coin 100 times. Here, 'success' could be defined as flipping a heads. If we infer from the fair nature of the coin that there is a 50% chance of flipping heads, we would expect about 50 heads. Similarly, we would expect about 50 tails (failures). As both these counts are over 10, according to the Large Counts Condition, we can use the normal approximation to describe the distribution of the number of heads.
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