If X is a binomial random variable and if ≥np10 and ≥n−1p10, then X is approximately normal with μX = ▼(Choose one) and σX = .

If X is a binomial random variable and if np ≥ 10 and n(1-p) ≥ 10, then X is approximately normal with μX = np and σX = sqrt(np(1-p)).

Here's the step by step explanation:

1. The conditions np ≥ 10 and n(1-p) ≥ 10 are the rule of thumb for approximating a binomial distribution with a normal distribution. This is known as the Central Limit Theorem.

2. The mean (μX) of a binomial distribution is np. This is derived from the formula for the mean of a binomial distribution, which is the number of trials (n) times the probability of success (p).

3. The standard deviation (σX) of a binomial distribution is sqrt(np(1-p)). This is derived from the formula for the standard deviation of a binomial distribution, which is the square root of the number of trials (n) times the probability of success (p) times the probability of failure (1-p).