Calculate mean, median, mode, range and sum of any set of numbers.
An average calculator quickly computes the arithmetic mean of a set of numbers. Simply enter your values and our online mean calculator adds them all up and divides by the count to give you the average. It also shows the sum, count, minimum, maximum, and range — giving you a complete picture of your dataset in seconds. This works the same way whether you're averaging a handful of numbers or a long list of large figures - the calculator adds every value and divides by the total count regardless of how many entries there are.
A weighted average gives more importance to some values than others. Formula: Weighted Average = Σ(value × weight) / Σ(weights). Used in GPA calculation (credit hours are the weights), exam score calculation (different components have different weights), and investment portfolio average returns (amount invested is the weight).
A moving average (rolling average) is calculated by averaging a fixed number of data points and moving the window forward one point at a time. For example, a 7-day moving average of daily sales smooths out day-to-day fluctuations to show the underlying trend. Moving averages are widely used in stock market technical analysis (50-day MA, 200-day MA), weather forecasting, and economic data analysis.
Averages are used in every field. In education: calculating class average scores, student GPA. In business: average revenue per user, average order value, average customer lifetime value. In health: average blood pressure, average blood sugar readings. In sports: batting average, goals per game, average lap time. Our mean calculator handles all these scenarios with ease.
What most people call "the average" is technically the mean — the sum of all values divided by how many values there are — but two other measures of central tendency, median and mode, often give a more accurate picture of a "typical" value, especially when a dataset contains extreme outliers. Median (the middle value when data is sorted) is far less affected by outliers than mean, which is why household income statistics are usually reported as medians rather than means, since a small number of extremely high earners would otherwise skew the mean upward and misrepresent the typical household's situation.
Mode (the most frequently occurring value) is most useful for categorical data or when identifying the single most common outcome matters more than a calculated central value — like identifying the most common shoe size sold rather than an average shoe size, which wouldn't correspond to an actual purchasable size.
A classic illustration: if nine people in a room earn $50,000 and one person earns $5,000,000, the mean income is over $500,000, wildly misrepresenting what a "typical" person in that room actually earns, while the median remains $50,000, accurately reflecting the experience of the majority. Understanding which average is appropriate for a given dataset, based on whether outliers are likely to be present, is essential for interpreting statistics accurately rather than being misled by a technically correct but contextually misleading number.
The average (mean) is calculated by adding all values together and dividing by the count of values. It represents the central value of a dataset.
In common usage, average usually means the arithmetic mean. However, median (middle value) and mode (most common value) are other types of averages.
Weighted average = Sum of (value × weight) / Sum of weights. Used when some values are more important than others, like calculating GPA.
The average is misleading when data has extreme outliers. For example, if 9 people earn a modest salary and 1 person earns a very high salary, the average salary looks much higher than what most people actually earn.
Enter all your scores or values from the previous year above, and the calculator instantly returns the average across that full data set.
Enter each percentage or numeric value above separated as individual entries, and the calculator computes the overall average across all of them instantly.