Frequency Distribution Calculator
Group your data into frequency distribution classes. Enter the range of your data and desired number of classes to get class widths, boundaries, and expected frequencies for histogram construction.
A frequency distribution organizes raw data into classes (intervals), making it easier to see patterns and construct histograms.
Key concepts: The class width is calculated as (max - min) / number of classes, rounded up for clean boundaries. Each class covers an equal interval, and every data point falls into exactly one class. The expected frequency per class (assuming uniform distribution) is n / k, where n is the number of data points and k is the number of classes.
Choosing the right number of classes: Too few classes hides the shape of the distribution; too many makes it noisy. Sturges' rule (k = 1 + 3.322 x log10(n)) is a common guideline. For 50 data points, it suggests about 7 classes. The square root rule (k = sqrt(n)) is another popular choice.