In this article:

Ensure your sample data is organized in Google Sheets. You should know your sample's mean, standard deviation, and size. If you don't have the mean and standard deviation, you can calculate them using =AVERAGE(range) and =STDEV(range) functions respectively, where range is your data range.

Decide on the confidence level you want to use for your interval (e.g., 90%, 95%, 99%). The confidence level reflects how sure you are that the true mean falls within the calculated interval. Remember, a 95% confidence level has an alpha of 0.05 (1 - 0.95).

With your data organized and your confidence level chosen, you can now use the CONFIDENCE.T function. The syntax is:

**=CONFIDENCE.T(alpha, standard_dev, size)**

Where:

**alpha:**The significance level (1 - confidence level). For a 95% confidence level, alpha is 0.05.**standard_dev:**The standard deviation of your sample.**size:**The sample size.

The CONFIDENCE.T function will return the margin of error. To find the confidence interval, you need to subtract and add this margin to the sample mean:

**Lower bound:** Sample Mean - Margin of Error

**Upper bound: **Sample Mean + Margin of Error

You can do this directly in your spreadsheet by referencing the cell containing the sample mean and the cell with the CONFIDENCE.T function result.

Let's use actual numbers to calculate the confidence interval using the CONFIDENCE.T function in a simulated environment.

**Sample mean (x̄):**75 inches (mean height of a sample of basketball players)**Standard deviation (s):**8 inches**Sample size (n):**25 players**Confidence level:**95% (which means alpha (α) = 1 - 0.95 = 0.05)

We have our sample mean in cell B1, our standard deviation in cell B2, and our sample size in cell B3, and we're calculating a 95% confidence interval (B4).

The syntax is: **=CONFIDENCE.T(0.05, B2, B3)**

Our margin of error (B6) would thus be 3.302237699.

We will then calculate the lower bound and upper bounds:

Lower bound: =B1 - B6

Upper bound: =B1 + B6

The margin of error calculated is approximately 3.30 inches. Therefore, the confidence interval for the true population mean height of basketball players, with 95% confidence, is between 71.70 inches and 78.30 inches.

This means we can be 95% confident that the true average height of the population of basketball players falls within this range.

We hope that this article has helped you and given you a better understanding of how to calculate confidence intervals in Google Sheets. If you enjoyed this article, you might also like our articles on how to do a sensitivity analysis in Google Sheets and how to assign a task in Google Sheets.