Mean, Median, Mode Calculator
Analyze your data with our comprehensive statistics calculator. Enter a list of numbers and instantly get mean (average), median (middle value), mode (most frequent), standard deviation, variance, range, and more.
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How to Use
- 1 Enter your numbers — Type or paste your data set. Numbers can be separated by commas, spaces, or new lines.
- 2 Choose population or sample — Select whether your data represents an entire population or a sample for accurate standard deviation calculation.
- 3 View all statistics — See mean, median, mode, sum, count, range, min, max, standard deviation, and variance instantly.
- 4 Review sorted data — See your numbers sorted from smallest to largest, helpful for understanding the distribution.
- 5 Copy results — Use the copy button to export all statistics for use in reports or other applications.
💡 Pro Tip: Copy data directly from Excel or Google Sheets — numbers will be parsed correctly whether separated by tabs, commas, or line breaks!
Frequently Asked Questions
What's the difference between mean, median, and mode?
Mean is the average (sum divided by count). Median is the middle value when data is sorted. Mode is the most frequently occurring value. Each tells you something different about your data — mean can be skewed by outliers, median is more robust, and mode shows the most common value.
When should I use population vs sample standard deviation?
Use population standard deviation when your data includes every member of the group you're studying (like all students in a class). Use sample standard deviation when your data is a subset of a larger group (like surveying 100 people to represent a city). Sample uses n-1 in the denominator to correct for bias.
What if there's no mode or multiple modes?
If all values appear only once, there is no mode (the data is amodal). If multiple values tie for most frequent, all of them are modes (multimodal). Our calculator displays all modes when there are ties.
What does standard deviation tell me?
Standard deviation measures how spread out your data is from the mean. A low standard deviation means values cluster close to the average, while a high standard deviation means values are spread over a wider range. It's useful for understanding variability in your data.