Learn on PengienVision, Mathematics, Grade 6Chapter 8: Display, Describe, and Summarize Data

Lesson 5: Summarize Data Using Measures of Variability

In this Grade 6 enVision Mathematics lesson, students learn how to choose the most appropriate measures of center and variability — mean, median, mode, MAD, and IQR — to accurately describe a data set. Students explore how the presence of outliers determines whether the mean or median better represents the data, and correspondingly whether MAD or IQR is the better measure of variability. Real-world quiz score examples guide students through analyzing data distribution, clustering, and spread to justify their statistical choices.

Section 1

Interquartile Range (IQR)

Property

The interquartile range (IQR) measures the spread of the middle 50% of a data set. To find the IQR:

  1. Find Q1 (the median of the lower half of the data)
  2. Find Q3 (the median of the upper half of the data)
  3. Calculate: IQR = Q3 - Q1

Examples

Section 2

Introduction to Mean Absolute Deviation (MAD)

Property

Once we have calculated the mean for a set of data, we want to have some sense of how the data are arranged around the mean.
The mean absolute deviation (MAD) is calculated this way: for each data point, calculate its distance from the mean.
Now the MAD is the mean of this new set of numbers.
When we use the mean and the MAD to summarize a data set, the mean tells us what is typical or representative for the data and the MAD tells us how spread out the data are.
The MAD tells us how much each score, on average, deviates from the mean, so the greater the MAD, the more spread out the data are.

Examples

  • For the data set {3, 5, 6, 10}, the mean is 3+5+6+104=6\frac{3+5+6+10}{4} = 6. The distances from the mean are 36=3|3-6|=3, 56=1|5-6|=1, 66=0|6-6|=0, and 106=4|10-6|=4. The MAD is 3+1+0+44=2\frac{3+1+0+4}{4} = 2.
  • Two friends track their nightly sleep. Alex's hours are {7, 8, 9} and Ben's are {5, 8, 11}. Both have a mean of 8 hours. Alex's MAD is 1+0+130.67\frac{1+0+1}{3} \approx 0.67. Ben's MAD is 3+0+33=2\frac{3+0+3}{3} = 2. Ben's sleep is more spread out.
  • A bowler's scores are {150, 155, 160}. The mean is 155. The deviations are 150155=5|150-155|=5, 155155=0|155-155|=0, and 160155=5|160-155|=5. The MAD is 5+0+533.33\frac{5+0+5}{3} \approx 3.33, showing high consistency.

Explanation

The Mean Absolute Deviation (MAD) measures how spread out your data is. A small MAD means all the numbers are bunched up close to the average. A large MAD means the numbers are widely scattered far from the average.

Book overview

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Chapter 8: Display, Describe, and Summarize Data

  1. Lesson 1

    Lesson 1: Recognize Statistical Questions

  2. Lesson 2

    Lesson 2: Summarize Data Using Mean, Median, Mode, and Range

  3. Lesson 3

    Lesson 3: Display Data in Box Plots

  4. Lesson 4

    Lesson 4: Display Data in Frequency Tables and Histograms

  5. Lesson 5Current

    Lesson 5: Summarize Data Using Measures of Variability

  6. Lesson 6

    Lesson 6: Choose Appropriate Statistical Measures

  7. Lesson 7

    Lesson 7: Summarize Data Distributions

Lesson overview

Expand to review the lesson summary and core properties.

Expand

Section 1

Interquartile Range (IQR)

Property

The interquartile range (IQR) measures the spread of the middle 50% of a data set. To find the IQR:

  1. Find Q1 (the median of the lower half of the data)
  2. Find Q3 (the median of the upper half of the data)
  3. Calculate: IQR = Q3 - Q1

Examples

Section 2

Introduction to Mean Absolute Deviation (MAD)

Property

Once we have calculated the mean for a set of data, we want to have some sense of how the data are arranged around the mean.
The mean absolute deviation (MAD) is calculated this way: for each data point, calculate its distance from the mean.
Now the MAD is the mean of this new set of numbers.
When we use the mean and the MAD to summarize a data set, the mean tells us what is typical or representative for the data and the MAD tells us how spread out the data are.
The MAD tells us how much each score, on average, deviates from the mean, so the greater the MAD, the more spread out the data are.

Examples

  • For the data set {3, 5, 6, 10}, the mean is 3+5+6+104=6\frac{3+5+6+10}{4} = 6. The distances from the mean are 36=3|3-6|=3, 56=1|5-6|=1, 66=0|6-6|=0, and 106=4|10-6|=4. The MAD is 3+1+0+44=2\frac{3+1+0+4}{4} = 2.
  • Two friends track their nightly sleep. Alex's hours are {7, 8, 9} and Ben's are {5, 8, 11}. Both have a mean of 8 hours. Alex's MAD is 1+0+130.67\frac{1+0+1}{3} \approx 0.67. Ben's MAD is 3+0+33=2\frac{3+0+3}{3} = 2. Ben's sleep is more spread out.
  • A bowler's scores are {150, 155, 160}. The mean is 155. The deviations are 150155=5|150-155|=5, 155155=0|155-155|=0, and 160155=5|160-155|=5. The MAD is 5+0+533.33\frac{5+0+5}{3} \approx 3.33, showing high consistency.

Explanation

The Mean Absolute Deviation (MAD) measures how spread out your data is. A small MAD means all the numbers are bunched up close to the average. A large MAD means the numbers are widely scattered far from the average.

Book overview

Jump across lessons in the current chapter without opening the full course modal.

Continue this chapter

Chapter 8: Display, Describe, and Summarize Data

  1. Lesson 1

    Lesson 1: Recognize Statistical Questions

  2. Lesson 2

    Lesson 2: Summarize Data Using Mean, Median, Mode, and Range

  3. Lesson 3

    Lesson 3: Display Data in Box Plots

  4. Lesson 4

    Lesson 4: Display Data in Frequency Tables and Histograms

  5. Lesson 5Current

    Lesson 5: Summarize Data Using Measures of Variability

  6. Lesson 6

    Lesson 6: Choose Appropriate Statistical Measures

  7. Lesson 7

    Lesson 7: Summarize Data Distributions