A histogram is a statistical report chart that uses a series of vertical bars of varying heights to represent data distribution. The horizontal axis represents data ranges, and the vertical axis shows frequency, making it easy to visualize the shape and spread of your data.
Histograms are widely used in quality management, data analysis, and scientific research. In quality management, histograms help determine if a process is stable. In data analysis, they reveal distribution characteristics such as normality, skewness, and outliers.
The number of bins directly affects the histogram's appearance. Too few bins obscure data features, while too many create noise. Common methods include Sturges' formula (k=1+3.322\u00d7log\u2081\u2080n), Square Root method (k=\u221an), and Rice Rule (k=2\u00d7n^1/3). This tool supports automatic calculation and manual setting.
Count mode shows the number of data points in each interval. Relative frequency mode shows the proportion of data points in each interval. Density mode divides frequency by interval width, making the total area equal to 1, which is useful for comparing with probability density functions.
A histogram has no gaps between bars and shows the frequency distribution of continuous data. A bar chart has gaps between bars and compares values across different categories.
Enable the normal fit line. If the histogram shape closely matches the fit curve, your data is approximately normally distributed. You can also check the skewness and kurtosis values.
This tool runs in your browser and supports thousands of data points. Very large datasets may slow down rendering — consider sampling first.