KIN 610 - Spring 2026
  • Overview
  • Syllabus
  • Assignments
    • Attendance & Participation
    • Weekly Quizzes
    • Major Takeaways
    • Lab Assignments
    • ePortfolio
    • Exams

    • Exam 1
    • Exam 1 Study Guide
  • Weekly Materials
    • Week 2
    • Measurement

    • Week 3
    • Central Tendency
    • Variability

    • Week 4
    • Normal Curve

    • Week 5
    • Probability and Sampling Error
    • Hypothesis Testing

    • Week 6
    • Correlation and Regression

    • Week 7
    • Multiple Correlation and Regression

    • Week 8
    • Comparing Two Means

    • Labs
    • Lab 1: Data Collection
  • Resources

On this page

  • 1 Prepare
    • 1.1 Chapter Overview
    • 1.2 Multimedia Resources
    • 1.3 Read the Chapter
  • 2 Practice
    • 2.1 Frequently Asked Questions
    • 2.2 Test your Knowledge
  • 3 Participate
  • 4 Perform
    • 4.1 Apply Your Learning
    • 4.2 Lab Assignment
    • 4.3 Additional Resources
      • 4.3.1 Related Chapters

Chapter 4: Measures of Central Tendency

Student Resources

ImportantHow to study this chapter

I use the 4 “P’s” framework to help you learn the material in this chapter: Prepare, Practice, Participate, and Perform. To increase the chances to succeed in this course, I strongly encourage you to complete all four “P’s” for each chapter.

1 Prepare

1.1 Chapter Overview

This chapter covers measures of central tendency—the mode, median, and mean. These statistics help us identify the “typical” or “central” value in a dataset, which is essential for describing and comparing groups in movement science research.

1.2 Multimedia Resources

The following table provides access to video and slide resources for this chapter. Click the links to open them in an overlay for better viewing on all devices.

Multimedia Resources
Resource Description Link
Long Video Overview A detailed video explaining the key concepts of mode, median, mean, and how to choose the right measure of central tendency. 🔗 Watch Video
Slide Overview PDF PDF slides that serve as an overview of this chapter. Read these before the textbook to introduce the main concepts and vocabulary. 🔗 View Slides
Slide Deck HTML Interactive HTML slides for class. During class, the instructor controls the presentation; after class, review at your own pace. 🔗 Open Slides
Slide Deck PDF PDF version of the slide deck for download and offline viewing. 🔗 Download PDF

1.3 Read the Chapter

Read (Weir & Vincent, 2021, p. Ch4) and (Furtado, 2026, p. Ch5) - optional but recommended - to understand mode, median, mean, and when to use each measure of central tendency.

To succeed in this course, you must read the textbook chapters assigned for each topic. This is the only way to learn the material in depth.

Once done, proceed to the next section to practice what you learned.

2 Practice

Practicing what you learned in the chapter is essential to mastering the material. Below are some resources to help you practice the material in this chapter.

2.1 Frequently Asked Questions

Measures of central tendency are statistics that identify a single value that represents the center or typical score in a distribution. The three main measures are the mode (most frequent value), median (middle value), and mean (arithmetic average).

Use the mode when: - You have nominal (categorical) data - You want to identify the most common or popular value - You’re interested in the most typical category The mode is the only measure of central tendency appropriate for nominal data.

Use the median when: - You have ordinal data or skewed distributions - There are extreme outliers that would distort the mean - You want a value that represents the “middle” of the dataset The median is resistant to outliers and works well with non-normal distributions.

Use the mean when: - You have interval or ratio scale data - The distribution is roughly symmetric (not heavily skewed) - You plan to use the data in further statistical calculations The mean is the foundation for many advanced statistics but is sensitive to outliers.

The mean is calculated using all values in the dataset, so extreme scores (outliers) can pull it away from the center of most of the data. For example, if most athletes run the 100m in 11-12 seconds but one runs it in 20 seconds, the mean will be higher than most individual times.

The mean is the arithmetic average (sum of all values divided by the number of values). The median is the middle value when data are arranged in order. In symmetric distributions, they’re similar. In skewed distributions, the mean gets pulled toward the tail while the median stays near the center of the data.

To calculate the mean: 1. Add up all the values in your dataset 2. Divide by the number of values Formula: \(\bar{x} = \frac{\sum x}{n}\)

To find the median: 1. Arrange all values in order from smallest to largest 2. If you have an odd number of values: the median is the middle value 3. If you have an even number of values: the median is the average of the two middle values

Distribution shape refers to how data are spread out—symmetric, skewed left, skewed right, or multimodal. It matters because the shape tells you which measure of central tendency is most appropriate and helps you interpret your data correctly.

In a right-skewed (positively skewed) distribution: - The mode is at the peak (lowest value) - The median is in the middle - The mean is pulled toward the long right tail (highest value) Order: Mode < Median < Mean

2.2 Test your Knowledge

Take this low-stakes quiz to test your knowledge of the material in this chapter. This quiz is for practice only and will help you identify areas where you may need additional review.

# What are measures of central tendency? - [ ] Values that describe the spread of data - [x] Values that describe the central characteristics of a set of data - [ ] Values that describe the relationship between variables - [ ] Values that describe the shape of a distribution # Which measure of central tendency is the score that occurs most frequently? - [x] Mode - [ ] Median - [ ] Mean - [ ] Range # How do you find the median when you have an odd number of scores? - [ ] Add all scores and divide by the number of scores - [x] Arrange scores in order and select the middle score - [ ] Find the most frequently occurring score - [ ] Average the two middle scores # What is the formula for calculating the mean? - [ ] The middle score when arranged in order - [ ] The most frequently occurring score - [x] X̄ = ΣX/N (sum of all scores divided by the number of scores) - [ ] The difference between the highest and lowest scores # In a normal distribution, how do the mode, median, and mean relate to each other? - [ ] They are always different values - [ ] The mean is always larger than the median - [x] They all fall at or near the same value - [ ] The mode is always the smallest value # In a positively skewed distribution, what is the order of the measures from left to right? - [ ] Mean, median, mode - [x] Mode, median, mean - [ ] Median, mode, mean - [ ] Mode, mean, median # When should you use the median instead of the mean? - [ ] When you have nominal data - [ ] When the distribution is perfectly normal - [x] When the distribution is badly skewed or has extreme scores - [ ] When you need to perform further calculations # Which measure of central tendency uses all available information from the data? - [ ] Mode - [ ] Median - [x] Mean - [ ] Range # What does the symbol Σ represent in statistical formulas? - [ ] The mean of a population - [ ] The median value - [x] Sum of (add up all the values) - [ ] The mode # Which measure of central tendency is most appropriate for nominal (categorical) data? - [x] Mode - [ ] Median - [ ] Mean - [ ] All three are equally appropriate # What symbol represents the mean of a sample? - [ ] μ (mu) - [x] X̄ (X-bar) - [ ] Σ (sigma) - [ ] M (capital M) # How do extreme scores (outliers) affect the mean? - [ ] They have no effect on the mean - [ ] They only affect the mean if there are multiple outliers - [x] They can have a large effect, pulling the mean toward them - [ ] They only affect the mean in small samples # What is the geometric mean used for? - [ ] Finding the middle score in a distribution - [ ] Calculating the most frequent score - [x] Analyzing positively skewed or log-normal data - [ ] Determining the range of scores # If you have the following scores: 5, 7, 9, 9, 12, what is the mode? - [ ] 5 - [ ] 7 - [x] 9 - [ ] 12 # When calculating the mean, how many decimal places should you round to? - [ ] Always round to whole numbers - [ ] Round to the same decimal places as the original data - [x] Round to one decimal place beyond the precision of the original data - [ ] Use as many decimal places as possible

3 Participate

This section includes activities and discussions that will be completed during class time. Your active participation is essential for deepening your understanding of the material.

TipIn-Class Activities

During class, we will: - Calculate and compare measures of central tendency for real movement science data - Analyze distribution shapes and discuss their implications - Work through examples of choosing appropriate measures for different data types - Discuss how outliers affect different measures of central tendency

4 Perform

4.1 Apply Your Learning

Now that you’ve prepared, practiced, and participated, it’s time to demonstrate your mastery of the material through assignments and assessments.

WarningNote to Students

I strongly encourage you to complete the previous “Ps” (Prepare, Practice, Participate) before attempting any assignments or assessments associated with this chapter.

4.2 Lab Assignment

Complete Lab 1: Central Tendency and Variability to apply what you’ve learned about measures of central tendency (mode, median, mean) and variability (range, variance, standard deviation).

View Lab 1

TipLab Instructions
  1. Download the Word document above (click to open, then save to your computer)
  2. The document has two parts:
    • Part 1: Instructions - Read this section for assignment details, grading rubric, and resources
    • Part 2: Your Answers - Complete all questions in this section
  3. Complete all questions in Part 2 using SPSS to analyze the Core Dataset
  4. Include your SPSS outputs by pasting as images or tables
  5. Delete Part 1 (Instructions) before submitting - submit only Part 2 (Your Answers)
  6. Submit your completed lab via Canvas

Note: This lab integrates concepts from both Chapter 4 (Central Tendency) and Chapter 5 (Variability), as these concepts should be reported together in practice.

4.3 Additional Resources

4.3.1 Related Chapters

  • Chapter 5: Measures of Variability

References

Furtado, O., Jr. (2026). Statistics for movement science: A hands-on guide with SPSS (1st ed.). https://drfurtado.github.io/sms/
Weir, J. P., & Vincent, W. J. (2021). Statistics in kinesiology (5th ed.). Human Kinetics.

© 2026 Dr. Ovande Furtado Jr. | CC BY-NC-SA