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Formula Generator - LOGNORMDIST function

The LOGNORMDIST function returns the value of the log-normal cumulative distribution with a given mean and standard deviation at a specified value. It is commonly used in statistics and finance to model data that follows a log-normal distribution. The function takes three arguments: x, which is the value at which to evaluate the distribution; mean, which is the mean of the log-normal distribution; and standard_deviation, which is the standard deviation of the log-normal distribution. The function returns the probability of observing a value less than or equal to x in the log-normal distribution.
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How to generate an LOGNORMDIST formula using AI.

To obtain the LOGNORMDIST formula for your data, you can ask the AI chatbot the following question: "Is there a formula in Excel that can calculate the logarithmic normal distribution for a given set of data?"

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LOGNORMDIST formula syntax.

The LOGNORMDIST function in Excel is used to calculate the probability density of a value in a log-normal distribution. Here is a clear and concise overview of its syntax: LOGNORMDIST(x, mean, standard_dev) - x: The value at which you want to evaluate the probability density function. - mean: The mean of the logarithm of the distribution. - standard_dev: The standard deviation of the logarithm of the distribution. The LOGNORMDIST function returns the probability density of the specified value in the log-normal distribution.

Use Cases & Examples In these use cases, we use the LOGNORMDIST formula to calculate the cumulative probability of a value in a log-normal distribution. The LOGNORMDIST formula takes four arguments: the value, the mean, the standard deviation, and a boolean value that determines whether to calculate the cumulative probability (TRUE) or the probability density function (FALSE).
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Provide Clear Context When describing your requirements to the AI, provide clear and concise context about the data you have, the specific task you want to accomplish, and any relevant constraints or conditions. This helps the AI understand the problem accurately.
Include Key Details Include important details such as column names, data ranges, and specific criteria that need to be considered in the formula. The more precise and specific you are, the better the AI can generate an appropriate formula.
Use Examples If possible, provide examples or sample data to illustrate the desired outcome. This can help the AI better understand the pattern or logic you are looking for in the formula.
Mention Desired Functionality Clearly articulate the functionality you want the formula to achieve. Specify if you are looking for lookups, calculations, aggregations, or any other specific operations.