Mean Plot: Definition

Descriptive Statistics >

mean plot
Mean plot of three BMI groups comparing time to ascend stairs.


A mean plot is a plot which shows the mean, and sometimes also the standard deviation, of data. It’s used to analyze the way in which the mean varies across different groups of data or between samples.

Setting up a Mean Plot

The vertical axis in a mean plot is typically the group mean. The horizontal axis is usually the group identifier (in the above image, the identifier is which BMI group the participants are in). In samples taken over time, this horizontal axis might show time.

At the overall mean, a reference line might be plotted.

The points representing the mean of each sample may be connected as in a line plot, like the one above, or they may remain unconnected. Each point may given an error bar or band representing the standard deviation. An error bar or diamond could also be used to represent confidence intervals.

Use of a Mean Plot

A mean plot can tell us whether there were any shifts in location, what the magnitude of any shifts might be, and if there are any distinct patterns. They allow us to check assumptions we might make of our data pool staying generally constant—or not—over time and location.

For instance, a mean plot might be useful if, after collecting health data in a survey conducted in a New Jersey suburb over 50 years, you wanted to check whether or not the income level had remained generally constant. A quick plot would give you an immediate understanding of the situation, and allow you to pinpoint any changes.

References

NIST/SEMATECH e-Handbook of Statistical Methods. Exploratory Data Analysis Techniques. Retrieved from https://www.itl.nist.gov/div898/handbook/eda/section3/meanplot on May 6, 2018.

Cheng, Wei. Graphical Representation of Mean Measurement Over Time. SAS Global Forum 2007, Paper 041-2007. Retrieved from http://citeseerx.ist.psu.edu/viewdoc/download;jsessionid=3418FA640144F989EFC2233423C2FDED?doi=10.1.1.176.2809&rep=rep1&type=pdf on May 6, 2018


Comments? Need to post a correction? Please Contact Us.