Histograms

Statistics · Axiom Academy

Visualizing the distribution of quantitative data with bins and frequencies A histogram takes raw data points and organizes them into bins (intervals). Each bar's height represents the frequency (count) of data points in that bin. Watch as we transform individual data points into a histogram: Bins: Intervals that group data (e.g., 0-10, 10-20) Frequency: Number of data points in each bin Bar Height: Represents the frequency The choice of bin width dramatically affects how we interpret the data. Too few bins hide important patterns, while too many bins create noise. See how different bin widths reveal different aspects of the same dataset: 3. Frequency vs Relative Frequency Histograms can display either frequency (count) or relative frequency (proportion/percentage). Relative frequency helps compare datasets of different sizes. Watch the transformation from frequency to relative frequency: Histograms reveal the shape of your data distribution: symmetric, skewed left, skewed right, uniform, or bimodal. Observe different distribution shapes: Symmetric: Mirror image around the center (e.g., normal distribution) Right-Skewed: Tail extends to the right (positive skew) Left-Skewed: Tail extends to the left (negative skew)

This is the written version of the interactive lesson above. See the full Statistics course.