Average Calculator
Enter numbers separated by commas, spaces, newlines, or semicolons. Non-numeric text is ignored automatically.
Enter Your Numbers
Type or paste a set of numbers above — separated by commas, spaces, or new lines — to instantly see the mean, median, mode, standard deviation, and a full statistical breakdown.
How to Use This Calculator
Choose Your Mode
Select 'Simple Average' for a standard dataset, or 'Weighted Average' if some values count more than others — for example, grades with different credit hours. For simple mode, also choose whether to paste your numbers in bulk or add them one at a time using the list builder.
Enter Your Numbers
For bulk mode, type or paste your numbers in the text area. They can be separated by commas, spaces, newlines, semicolons, or any mix — the calculator automatically detects and extracts all valid numbers and ignores non-numeric text. For list mode, type each number and press Enter or click the + button. In weighted mode, enter each value alongside its weight.
Review Your Results
Results update automatically as you type. The main result shows the arithmetic mean. Scroll down to see all statistics: median, mode, min, max, range, population and sample standard deviations, geometric mean, harmonic mean, and root mean square. The distribution chart shows each value color-coded by whether it falls above or below the mean, with outliers highlighted.
Export or Share
Use 'Copy Results' to copy all statistics to your clipboard for pasting into a document or email. Click 'Export CSV' to download a spreadsheet-compatible file with all results. Use 'Print' for a clean printed record. Adjust the decimal places selector to control precision across all displayed values.
Frequently Asked Questions
What is the difference between mean, median, and mode?
The mean (average) is computed by adding all values and dividing by the count. It is sensitive to extreme values (outliers). The median is the middle value in a sorted dataset — half the values fall below it and half above. It is resistant to outliers and better represents 'typical' values in skewed distributions like incomes or house prices. The mode is the value that appears most frequently; a dataset can have no mode (all values unique), one mode (unimodal), or several modes (bimodal, multimodal). For symmetric, bell-curve data, all three measures are similar. For skewed data, the median is usually a better central value than the mean.
When should I use weighted average instead of regular average?
Use a weighted average when not all values contribute equally to the overall result. Classic examples include: GPA calculation where different courses have different credit hours; portfolio returns where investments have different dollar amounts; survey results where different demographic groups need to be proportionally represented; and grade point averages where tests, quizzes, and homework have different point weights. In a weighted average, each value is multiplied by its weight, the products are summed, and the total is divided by the sum of all weights. Without weighting, a simple average would treat every item equally regardless of its importance.
What is the difference between population and sample standard deviation?
Population standard deviation (σ) is used when your dataset represents the entire population you are interested in — for example, the exact scores of all 30 students in your class. Sample standard deviation (s) is used when your dataset is a sample drawn from a larger population — for example, measuring heights of 100 people to estimate the standard deviation of all adults. The formulas differ by one step: sample standard deviation divides by n-1 instead of n (Bessel's correction). This adjustment makes the sample standard deviation an unbiased estimator of the population standard deviation, correcting for the fact that a sample tends to underestimate spread.
When is the geometric mean more appropriate than the arithmetic mean?
The geometric mean is the preferred average for quantities that are multiplied together rather than added — specifically, rates of change, growth rates, ratios, and percentages. If an investment grows by 100% in year one and falls by 50% in year two, the arithmetic mean of those percentage changes (+25%) suggests growth, but the geometric mean (0%) correctly reflects that you end up where you started. For averaging annual percentage growth rates, price index changes, or population growth rates, always use the geometric mean. Note that the geometric mean is only defined for positive values — it cannot be computed when the dataset includes zero or negative numbers.
What does an outlier mean in the distribution chart?
In statistics, an outlier is a data point that is unusually far from the rest of the dataset. This calculator flags values as outliers when they fall more than two standard deviations away from the mean (beyond mean ± 2σ). In a normal (bell-curve) distribution, approximately 95% of values fall within two standard deviations of the mean, so values outside that range are statistically unusual. Outliers are highlighted in red in the distribution chart. Outliers can be caused by measurement errors, data entry mistakes, or they may be genuine extreme values that are important in their own right. Checking for outliers before reporting averages is a good practice.
Can I calculate the average of percentages, negative numbers, or decimals?
Yes. This calculator handles positive numbers, negative numbers, decimal values, and percentages (the percent sign is automatically stripped). For example, entering '-5, 0, 5, 10' will correctly compute a mean of 2.5, a median of 2.5, min of -5, and max of 10. For percentages like '75%, 80%, 92%', the percent signs are removed and the underlying numbers 75, 80, 92 are averaged. One caveat: the geometric mean and harmonic mean are only defined for positive non-zero values respectively. If your dataset contains zeros or negatives, those advanced means will not be displayed, but all other statistics (mean, median, mode, standard deviation, etc.) will still calculate correctly.