Number List Statistics

Compute mean, median, mode, variance and more from a list of numbers

What is it and how does it work?

Analysing a list of numbers quickly — finding the sum, average, minimum, maximum, range, count, and basic statistical measures — is one of the most common data tasks in everyday work. Whether you're checking sales figures, averaging survey responses, totalling a list of expenses, or verifying sensor readings, this tool accepts a raw list of numbers (one per line, or comma-separated) and instantly returns all the key statistics without needing a spreadsheet.

Beyond the basics, this tool also provides median, mode, variance, standard deviation, and percentiles. These measures reveal the shape of a dataset: whether values cluster around the mean or spread widely, whether there are outliers, and whether the distribution is symmetric. For quick exploratory data analysis without opening Excel or Python, this tool covers the full descriptive statistics workflow.

Common use cases

• Monthly expense check: paste 12 monthly expense totals, get the sum (annual), average (monthly benchmark), and see if any month is a statistical outlier beyond 2 standard deviations.
• Student grade analysis: enter a class's test scores to find the class average, median, highest and lowest scores, and identify the range — without needing a grade book spreadsheet.
• Sensor data validation: copy a column of sensor readings from a log file, check the mean and standard deviation, and identify any readings outside 3σ that may indicate sensor errors.

Frequently asked questions

What is the difference between mean and median?

The mean (average) sums all values and divides by count. The median is the middle value when sorted. The median is more robust to outliers: for incomes {$30k, $30k, $35k, $40k, $1M}, the mean is ~$227k but the median is $35k — a much better representation of a "typical" income.

What is the difference between population and sample standard deviation?

Population SD divides by N; sample SD divides by N-1 (Bessel's correction). Use sample SD when your list is a sample from a larger population (the common case). Use population SD only when you have every value in the entire population. Most stats tools default to sample SD.

What does the mode tell me?

Mode is the most frequently occurring value. It's most useful for discrete data (e.g., survey ratings on a 1–5 scale) where you want to know the most common response. A dataset can be unimodal (one mode), bimodal (two equal peaks), or have no mode if all values are unique.

What is interquartile range (IQR) and why does it matter?

IQR is Q3 − Q1 (the range of the middle 50% of values). It's a measure of spread that is resistant to outliers. The standard box-plot outlier rule flags values below Q1 − 1.5×IQR or above Q3 + 1.5×IQR as potential outliers — a quick way to identify anomalous data points.

Data

CSV Viewer · Data Faker · List Sorter · Array / Set Operations · Duplicate Line Finder · Tally Counter