Don't lose your points!
Sign up and save them.
Interpreting Data: Central Tendency and Variability

Interpreting Data: Central Tendency and Variability

  • Understand the difference between measures of central tendency and measures of variability in data sets.
  • Understand the importance of discussing measures of central tendency and variability in data interpretation.

In this lesson, students are introduced to the concepts of central tendency and variability in data sets. Data are simply observations in the form of measurements, such as length, mass, counts, percentages, survey responses, and so forth. Scientists rely on data to understand the natural world and develop theories, but data must be interpreted in order to be useful. When we interpret data, we are "making sense of" data. This lesson covers the basics of how data can be analyzed and interpreted.

See More
Fast, Free College Credit

Developing Effective Teams

Let's Ride
*No strings attached. This college course is 100% free and is worth 1 semester credit.

28 Sophia partners guarantee credit transfer.

263 Institutions have accepted or given pre-approval for credit transfer.

* The American Council on Education's College Credit Recommendation Service (ACE Credit®) has evaluated and recommended college credit for 25 of Sophia’s online courses. More than 2,000 colleges and universities consider ACE CREDIT recommendations in determining the applicability to their course and degree programs.


Data Interpretation: Overview

The activities in this lesson should introduce you to the key concepts in the skill of data interpretation. You should complete these activities in a timely manner. Please consult your class calendar for details.

Interpreting Data: What do you know?

What does variability tell us about a data set?

This hands-on activity will help you to see how variability and central tendency are used in data interpretation. View the .pdf and check in with the teacher before you begin. All of your work should be recorded in your lab notebook, including each section of the lab (Question, Beginning Ideas, summary of procedure, etc.).

Full Screen

Introduction to Interpreting Data

Check for Understanding

After watching the introduction, complete this concept map to check your understanding of the main ideas and vocabulary.

Full Screen

How do we measure central tendency and variability, and what do they mean?

So, what are measures of central tendency and variability, and what do they tell us? For this task, you must create a product that DEFINES central tendency and variability and explores different measures of both. The statistics can get VERY complicated, so you should stick to the basics: mean, median, range, standard deviation, standard error of the mean, and r-squared (for best-fit lines). You can use any resources that you like for research, and you can choose your own product. If you're not sure what you'd like to do, here are a few suggestions:

  • Create a foldable with 2 sides (measures of central tendency, measures of variability). For each side, research different ways that we measure and discuss what the measurement tells us.
  • Make digital bumper stickers using Google Slides. Be sure to explain the symbols and text on each sticker.
  • Develop a game that requires players to match characteristics and examples to different measures.

For this assignment, you do NOT need to know exactly how to calculate each measure. The goal of this lesson is to understand why central tendency and variability are important and what these measures tell us. You can learn how to calculate these measures in future lessons.


In your lab notebook, add your thoughts on data interpretation to your skills concept map. Include any vocabulary words and main ideas that you think are important to remember. Also, if you have any questions, be sure to record them and follow up!

  • What activities did you complete during this lesson?
  • What are the most important ideas that you encountered in this lesson? Make a bullet list of 3-5 ideas.
  • How do you think you could use your new knowledge of data interpretation in science and in life?