The standard deviation of a binomial distribution can be found using the formula:

$\sigma = \sqrt{n \cdot p \cdot (1 - p)}$

where:

• $n$ is the number of trials,
• $p$ is the probability of success on a single trial,
• $(1 - p)$ is the probability of failure.

Steps to find the standard deviation:

1. Identify the number of trials $n$.
2. Determine the probability of success $p$.
3. Substitute these values into the formula.
4. Calculate the square root of the product $n \cdot p \cdot (1 - p)$.

Would you like an example or further explanation?

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Here are 5 related questions to explore further:

1. How is the mean of a binomial distribution calculated?
2. What is the variance of a binomial distribution, and how is it related to the standard deviation?
3. Can you explain the conditions under which a binomial distribution approximates a normal distribution?
4. What happens to the standard deviation if the probability $p$ increases?
5. How does increasing the number of trials $n$ affect the shape of the binomial distribution?

Tip: The larger the number of trials $n$, the closer the binomial distribution can resemble a normal distribution if the success probability is not too extreme.