The NORMDIST function in Google Sheets is a powerful tool for statistical analysis. It provides users the ability to compute the probability of a value occurring under a normal distribution, which is essential in various fields such as finance, research, and quality control.

Syntax

NORMDIST(x, mean, standard_dev, cumulative)

• x: The value for which you want to calculate the distribution.
• mean: The arithmetic mean of the distribution.
• standard_dev: The standard deviation of the distribution.
• cumulative: A logical value that determines the form of the function. If TRUE, returns the cumulative distribution function; if FALSE, returns the probability density function.

Example #1

NORMDIST(1.5, 0, 1, TRUE)

This function calculates the cumulative probability of a value of 1.5, given a mean of 0 and a standard deviation of 1. The result is approximately 0.9332, meaning there is a 93.32% chance of a value being less than or equal to 1.5 under this normal distribution.

Example #2

NORMDIST(2, 1, 0.5, FALSE)

Here, the function computes the probability density for a value of 2, with a mean of 1 and a standard deviation of 0.5. The value returned is approximately 0.7962, representing the density at that point in the distribution.

Example #3

NORMDIST(0, 0, 1, TRUE)

This instance evaluates the cumulative probability for the value of 0, mean of 0, and standard deviation of 1. The result is 0.5, indicating that there is a 50% probability of obtaining a value less than or equal to 0.

Error handling

• VALUE! – Indicates that one or more arguments are of the wrong type. Ensure that the inputs are numeric where necessary.
• NUM! – Occurs when the standard deviation is less than or equal to zero, which is not acceptable. Make sure the standard deviation is a positive number.
• NAME? – This suggests that the function name may be misspelled. Double-check the function name “NORMDIST”.

Conclusion

The NORMDIST function is integral for statistical calculations involving normal distributions in Google Sheets. By understanding its syntax and how to apply it, users can effectively analyze data and make informed decisions based on probabilistic outcomes.