The CONFIDENCE.T function in Excel is a powerful tool used to calculate the confidence interval for a population mean based on a sample. Utilizing the Student’s t distribution, this function is particularly useful in statistical analysis when the sample size is small or when the population standard deviation is unknown. This function allows researchers and analysts to quantify the uncertainty associated with sample estimates, providing a more informed basis for decision-making.
Syntax
CONFIDENCE.T(alpha, standard_dev, size)
- alpha: This is the significance level, representing the probability that the population mean will not fall within the confidence interval. It is generally defined as 1 minus the desired confidence level (e.g., 0.05 for a 95% confidence level).
- standard_dev: This parameter refers to the estimated standard deviation of the population based on the sample data, which indicates the degree of variation in the data.
- size: This indicates the number of observations in the sample, which is crucial for calculating the confidence interval accurately.
Example #1
=CONFIDENCE.T(0.05, 4.5, 30)
This formula calculates the confidence interval for a population mean with a significance level of 0.05, a standard deviation of 4.5, and a sample size of 30. Suppose the result is 1.687, indicating that the true population mean is expected to fall within this interval around the sample mean.
Example #2
=CONFIDENCE.T(0.01, 3.2, 50)
This example computes the confidence interval with a significance level of 0.01 (99% confidence), a standard deviation of 3.2, and a sample size of 50. For instance, if the result is 0.867, it shows that we can be 99% confident the true mean lies within that range.
Example #3
=CONFIDENCE.T(0.10, 5, 20)
In this case, the function calculates the confidence interval with a significance level of 0.10 (90% confidence), a standard deviation of 5, and a sample size of 20. If the result is 1.478, this indicates the population mean falls within that range with 90% confidence.
Error handling
- NUM!: This error occurs if the ‘alpha’ value is less than or equal to 0 or greater than or equal to 1. Make sure ‘alpha’ is always between 0 and 1.
- DIV/0!: This error appears when ‘size’ is less than 1. Ensure that your sample size is at least 1 to avoid this error.
- VALUE!: This error is displayed when non-numeric values are supplied for any of the function arguments. Ensure that ‘alpha’, ‘standard_dev’, and ‘size’ are all numeric.