Confidence Interval From Raw Data
A confidence interval turns a raw sample into a practical range. It estimates where the true population mean may sit. The calculator starts with each value you paste. It then cleans the list, counts the valid values, and finds the sample mean. It also measures spread with the sample standard deviation.
Why Raw Data Matters
Raw data keeps the calculation transparent. You do not need to compute the mean first. You can paste survey scores, lab readings, delivery times, test results, or production measurements. The tool shows the values used after optional trimming. This helps you find mistakes before trusting the interval.
Choosing the Right Method
Use the t method when the population standard deviation is unknown. This is the normal choice for most sample studies. Use the z method when you already know the population standard deviation from reliable historical data. The automatic method selects z only when a population deviation is supplied. Otherwise, it uses the t method. Higher confidence levels make wider intervals. Lower levels make narrower intervals.
What The Results Mean
The lower bound and upper bound form the estimated range. If many similar samples were taken, the selected percentage of intervals would contain the true mean. The margin of error is the distance from the sample mean to either bound. A larger sample usually lowers the margin. A larger standard deviation usually raises it.
Advanced Settings
The finite population correction is useful when your sample is a meaningful part of a small population. Enter the total population size when sampling without replacement. The trimming option removes equal percentages from both tails. It can reduce the effect of extreme errors. Use it carefully. Trimming changes the question being answered.
Good Practice
Always inspect the sample size. Very small samples can produce wide intervals. Check the raw values for units and typing errors. Avoid mixing different groups unless that is your goal. Report the method, confidence level, sample size, mean, standard deviation, and interval. These details make your statistical result clear, repeatable, and easier to review.
Exports save the same results for later use. The CSV file suits spreadsheets. The report file suits sharing. Keep both with your raw notes, so your workflow stays organized and documented.