Box Plots

Statistics · Axiom Academy

Visual summaries of data distribution through the five-number summary Before we can create a box plot, we need the five-number summary of our data. This consists of: Minimum: The smallest value in the dataset Q1 (First Quartile): The median of the lower half of the data (25th percentile) Median (Q2): The middle value that splits the data in half (50th percentile) Q3 (Third Quartile): The median of the upper half of the data (75th percentile) Maximum: The largest value in the dataset Let's visualize how we identify these values from a dataset. Once we have the five-number summary, we construct the box plot using these components: The Box: Extends from Q1 to Q3, containing the middle 50% of the data The Median Line: A line inside the box showing Q2 The Whiskers: Lines extending from the box to the minimum and maximum values IQR (Interquartile Range): The length of the box (Q3 - Q1) Watch how we transform the five-number summary into a complete box plot. Box plots help us identify outliers - values that fall far from the rest of the data. We use the IQR method: Any data point below the lower fence or above the upper fence is considered an outlier. When outliers exist, the whiskers extend to the most extreme non-outlier values, and outliers are plotted as individual points.

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