The CONFIDENCE function in Google Sheets is a statistical tool used to calculate a confidence interval for a population mean based on a sample mean, standard deviation, and a specified confidence level. It serves as a key function for researchers and analysts to understand the precision of their sample estimates when making inferences about a population.

Syntax

CONFIDENCE(alpha, standard_deviation, size)

• alpha: This is the significance level, representing the probability that the true population parameter falls outside the confidence interval. A common value is 0.05 for a 95% confidence level.
• standard_deviation: This parameter refers to the standard deviation of the sample data, indicating the variability within the sample.
• size: The number of observations in the sample, which helps determine the precision of the estimate. It must be a positive integer.

Example #1

CONFIDENCE(0.05, 1.2, 30)

This function calculates the confidence interval for a sample with a standard deviation of 1.2, using a significance level of 0.05 and a sample size of 30. The result might be approximately 0.438, indicating the margin of error.

Example #2

CONFIDENCE(0.01, 0.5, 50)

This call computes the confidence interval for a sample where the standard deviation is 0.5, with a 1% significance level and 50 observations. The output could be around 0.144, indicating precision in the estimate.

Example #3

CONFIDENCE(0.10, 2.0, 15)

Here, the function is applied with a standard deviation of 2.0, a 10% significance level, and a sample size of 15. The result may yield approximately 0.829 as the margin of error.

Error handling

• NUM!: Occurs if the size parameter is less than 1. Ensure that the sample size is a positive integer.
• VALUE!: Happens when any of the parameters are not numeric. Double-check that the provided values are all numbers.
• DIV/0!: This error appears if the standard deviation is 0. A non-zero value must be provided for the standard deviation.

Conclusion

The CONFIDENCE function is an essential tool for statistical analysis in Google Sheets, enabling users to quantify the uncertainty around their sample mean estimates. By correctly applying this function, researchers can effectively communicate the reliability of their findings, facilitating informed decision-making based on statistical inference.