That’s something to look for when comparing box plots, especially when the medians are similar. Short boxes mean their data points consistently hover around the center values. The same thing can be said about the boxes. Larger ranges indicate wider distribution, that is, more scattered data. Together with the box, the whiskers show how big a range there is between those two extremes. The lines coming out from each box extend from the maximum to the minimum values of each set. If both median lines lie within the overlap between two boxes, we will have to take another step to reach a conclusion about their groups. If the median line of box A lies outside of box B entirely, then there is likely to be a difference between the two groups.īoxes overlap but don’t spread past both medians: groups are likely to be different. These are the medians, the “middle” values of each group. If they overlap, move on to the lines inside the boxes. Non-overlapping boxes, groups are different. If two boxes do not overlap with one another, say, box A is completely above or below box B, then there is a difference between the two groups. They represent the interquartile range, or the middle half of the values in each group. The key information you want to get when reading box plots is: are these groups different, and if so, how? To quickly compare box plots, look for these things: The boxes: But box plots are not always intuitive to read. They manage to carry a lot of statistical details - medians, ranges, outliers - without looking intimidating. box-and-whiskers plots, are an excellent way to visualize differences among groups. Lathe 3 is performing with relatively less variation than Lathe 2 however, it is centered on the lower side of the specification and is making shafts below specification.Box plots, a.k.a.Lathe 2 appears to have excess variation, and is making shafts below the minimum diameter.Lathe 1 appears to be making good parts, and is centered in the tolerance.The design specification is 18.85 +/- 0.1 mm.ĭiameter measurements from a sample of shafts taken from each roughing lathe are displayed in a box and whisker plot in Figure 2.įigure 2 Box and Whisker Plot Lathe Comparison Example Suppose you wanted to compare the performance of three lathes responsible for the rough turning of a motor shaft. Right figure: For comparison, a histogram of the data is also shown, showing the frequency of each value in the data set. The median value is displayed inside the "box." The maximum and minimum values are displayed with vertical lines ("whiskers") connecting the points to the center box. Left figure: The center represents the middle 50%, or 50th percentile of the data set, and is derived using the lower and upper quartile values. The data represented in box and whisker plot format can be seen in Figure 1.
Note: For a data set with an even number of values, the median is calculated as the average of the two middle values.
You can also download the box and whisker plot template. The procedure to develop a box and whisker plot comes from the five statistics below. Data from duplicate machines manufacturing the same products.Similar features on one part, such as camshaft lobes.Data from before and after a process change.Test scores between schools or classrooms.Sources that are related to each other in some way. Use box and whisker plots when you have multiple data sets from independent Plots allow for comparison of data from different categories for easier, more effectiveĭecision-making. Why Use a Box and Whisker Plot?īox and whisker plots are very effective and easy to read, as they can summarize dataįrom multiple sources and display the results in a single graph. Plot can provide additional detail while allowing multiple sets of data to be displayed in the same graph. In most cases, a histogram analysis provides a sufficient display, but a box and whisker Quality Glossary Definition: Box and whisker plotĪlso called: box plot, box and whisker diagram, box and whisker plot with outliersĪ box and whisker plot is defined as a graphical method of displaying variation in a set of data.