The Google Sheets function LOGINV is utilized to determine the inverse of the log-normal cumulative probability distribution. This function is particularly useful in statistical analysis when modeling skewed distributions, as it allows users to derive values based on specified mean and standard deviation parameters.

Syntax

LOGINV(probability, mean, standard_dev)

• probability: A numeric value between 0 and 1 that represents the cumulative distribution function’s probability.
• mean: The mean or average of the natural logarithm of the distribution.
• standard_dev: The standard deviation of the natural logarithm of the distribution.

Example #1

LOGINV(0.95, 0, 1)

This function call computes the inverse log-normal value for a probability of 0.95, assuming a mean of 0 and a standard deviation of 1. This may yield a result of approximately 5.062, indicating that 95% of the distribution lies below this value.

Example #2

LOGINV(0.5, 1, 0.5)

Here, the function calculates the inverse log-normal value for a probability of 0.5, with a mean of 1 and a standard deviation of 0.5. The expected result could be around 2.718, signifying that 50% of the distribution is below this calculated result.

Example #3

LOGINV(0.8, 2, 0.3)

In this example, the function finds the inverse log-normal value for a probability of 0.8, a mean of 2, and a standard deviation of 0.3. The output may be close to 8.133, indicating that 80% of the data points fall below this threshold.

Error handling

• NUM!: This error indicates that the provided probability value is not in the range of 0 to 1, making the calculation invalid.
• VALUE!: This error arises when any of the function arguments are non-numeric, thus preventing proper computation.

Conclusion

In summary, the LOGINV function in Google Sheets is a powerful tool for deriving values from the log-normal distribution. Understanding its parameters and potential errors can enhance your ability to conduct sophisticated statistical analyses and decision-making processes based on log-normally distributed data.