The normal approximation provides a convenient way to estimate binomial probabilities when the number of trials is large and the success probability is not too extreme. By treating the discrete binomial distribution as a continuous normal distribution, calculations become much simpler while retaining good accuracy.
To apply the approximation, we first compute the mean (mu = np) and the standard deviation (sigma = sqrt{np(1-p)}). Then a continuity correction of (pm 0.5) is often added to the integer count to better align the discrete and continuous models.
Finally, the probability of observing a value in a given range is found by converting the bounds to standardβnormal scores (Z) and using the standard normal cumulative distribution function.
How do I calculate the mean (ΞΌ) in normal approximation?
What is the standard deviation (Ο) for normal approximation?
Why do we use continuity correction in normal approximation?
When is it appropriate to use normal approximation?
How does the calculator handle small probabilities of success?
Can I use this calculator for exact binomial probabilities?
What is the formula for continuity correction in this calculator?
Results are for informational purposes only and do not constitute professional advice.
