Learn on PengiBig Ideas Math, Course 1Chapter 9: Statistical Measures

Lesson 4: Measures of Variation

In this Grade 6 lesson from Big Ideas Math Course 1, Chapter 9, students learn how to describe the spread of a data set using measures of variation, including range, quartiles, and interquartile range (IQR). Students practice finding the range by subtracting the least value from the greatest, identifying the first and third quartiles by finding the medians of the lower and upper halves of ordered data, and calculating the IQR as Q3 minus Q1. These skills help students interpret how spread out or clustered a set of real-world data values are.

Section 1

Introduction to Measures of Variation

Property

A measure of center for a numerical data set summarizes all of its values with a single number, while a measure of variation describes with a single number how its values vary.
The first, and easiest, measure is the range. This is given by the difference between the highest and lowest data values.
While easy to compute, it only tells us how far apart the extreme values are and gives no indication about the spread of the data values between the two extremes.

Examples

  • A student's test scores are 85, 92, 78, 95, and 88. The highest score is 95 and the lowest is 78. The range is 9578=1795 - 78 = 17.
  • Two basketball players' points per game are recorded. Player A: {15, 17, 16, 18}. Player B: {5, 10, 25, 30}. Player A's range is 1815=318 - 15 = 3, while Player B's is 305=2530 - 5 = 25, showing Player B's scoring is less consistent.
  • The data sets {2, 8, 8, 9, 12} and {2, 3, 4, 5, 12} both have a range of 10. However, the first set is clustered high while the second is more evenly spread, showing a limitation of using only the range.

Explanation

Measures of variability, like range, tell you about the spread of your data. While the mean or median tells you the center, variability describes if the data points are all clustered together or widely scattered apart.

Section 2

Finding the Quartiles of a Data Set

Property

Quartiles divide an ordered data set into four equal parts. The first quartile (Q1Q_1) is the median of the lower half of the data, and the third quartile (Q3Q_3) is the median of the upper half. The median of the entire data set is the second quartile (Q2Q_2).

Examples

  • For the data set {2,5,6,8,11,12,15,18}\{2, 5, 6, 8, 11, 12, 15, 18\}, the median (Q2Q_2) is 9.59.5. The lower half is {2,5,6,8}\{2, 5, 6, 8\}, so Q1=5+62=5.5Q_1 = \frac{5+6}{2} = 5.5. The upper half is {11,12,15,18}\{11, 12, 15, 18\}, so Q3=12+152=13.5Q_3 = \frac{12+15}{2} = 13.5.
  • For the data set {3,7,8,10,14,16,19}\{3, 7, 8, 10, 14, 16, 19\}, the median (Q2Q_2) is 1010. The lower half is {3,7,8}\{3, 7, 8\}, so Q1=7Q_1 = 7. The upper half is {14,16,19}\{14, 16, 19\}, so Q3=16Q_3 = 16.

Explanation

To find the quartiles, first order your data from least to greatest and find the median (the second quartile, Q2Q_2). The first quartile, Q1Q_1, is the median of the data points that are less than Q2Q_2. The third quartile, Q3Q_3, is the median of the data points that are greater than Q2Q_2. These values are essential for understanding the spread of the data and for calculating the interquartile range.

Section 3

Finding the Interquartile Range (IQR)

Property

The interquartile range (IQR) is the difference between the third quartile (Q3Q_3) and the first quartile (Q1Q_1).

IQR=Q3Q1IQR = Q_3 - Q_1

Examples

  • For a data set with a first quartile of Q1=10Q_1 = 10 and a third quartile of Q3=25Q_3 = 25, the interquartile range is 2510=1525 - 10 = 15.
  • If the quartiles of a data set are Q1=38.5Q_1 = 38.5 and Q3=52Q_3 = 52, the interquartile range is 5238.5=13.552 - 38.5 = 13.5.

Explanation

The interquartile range, or IQR, measures the spread of the middle half of your data. To find the IQR, you first need to identify the first quartile (Q1Q_1) and the third quartile (Q3Q_3). The IQR is then calculated by simply subtracting the value of Q1Q_1 from the value of Q3Q_3. This value represents the range of the central 50% of the data and is less sensitive to extreme values, or outliers, than the total range.

Lesson overview

Expand to review the lesson summary and core properties.

Expand

Section 1

Introduction to Measures of Variation

Property

A measure of center for a numerical data set summarizes all of its values with a single number, while a measure of variation describes with a single number how its values vary.
The first, and easiest, measure is the range. This is given by the difference between the highest and lowest data values.
While easy to compute, it only tells us how far apart the extreme values are and gives no indication about the spread of the data values between the two extremes.

Examples

  • A student's test scores are 85, 92, 78, 95, and 88. The highest score is 95 and the lowest is 78. The range is 9578=1795 - 78 = 17.
  • Two basketball players' points per game are recorded. Player A: {15, 17, 16, 18}. Player B: {5, 10, 25, 30}. Player A's range is 1815=318 - 15 = 3, while Player B's is 305=2530 - 5 = 25, showing Player B's scoring is less consistent.
  • The data sets {2, 8, 8, 9, 12} and {2, 3, 4, 5, 12} both have a range of 10. However, the first set is clustered high while the second is more evenly spread, showing a limitation of using only the range.

Explanation

Measures of variability, like range, tell you about the spread of your data. While the mean or median tells you the center, variability describes if the data points are all clustered together or widely scattered apart.

Section 2

Finding the Quartiles of a Data Set

Property

Quartiles divide an ordered data set into four equal parts. The first quartile (Q1Q_1) is the median of the lower half of the data, and the third quartile (Q3Q_3) is the median of the upper half. The median of the entire data set is the second quartile (Q2Q_2).

Examples

  • For the data set {2,5,6,8,11,12,15,18}\{2, 5, 6, 8, 11, 12, 15, 18\}, the median (Q2Q_2) is 9.59.5. The lower half is {2,5,6,8}\{2, 5, 6, 8\}, so Q1=5+62=5.5Q_1 = \frac{5+6}{2} = 5.5. The upper half is {11,12,15,18}\{11, 12, 15, 18\}, so Q3=12+152=13.5Q_3 = \frac{12+15}{2} = 13.5.
  • For the data set {3,7,8,10,14,16,19}\{3, 7, 8, 10, 14, 16, 19\}, the median (Q2Q_2) is 1010. The lower half is {3,7,8}\{3, 7, 8\}, so Q1=7Q_1 = 7. The upper half is {14,16,19}\{14, 16, 19\}, so Q3=16Q_3 = 16.

Explanation

To find the quartiles, first order your data from least to greatest and find the median (the second quartile, Q2Q_2). The first quartile, Q1Q_1, is the median of the data points that are less than Q2Q_2. The third quartile, Q3Q_3, is the median of the data points that are greater than Q2Q_2. These values are essential for understanding the spread of the data and for calculating the interquartile range.

Section 3

Finding the Interquartile Range (IQR)

Property

The interquartile range (IQR) is the difference between the third quartile (Q3Q_3) and the first quartile (Q1Q_1).

IQR=Q3Q1IQR = Q_3 - Q_1

Examples

  • For a data set with a first quartile of Q1=10Q_1 = 10 and a third quartile of Q3=25Q_3 = 25, the interquartile range is 2510=1525 - 10 = 15.
  • If the quartiles of a data set are Q1=38.5Q_1 = 38.5 and Q3=52Q_3 = 52, the interquartile range is 5238.5=13.552 - 38.5 = 13.5.

Explanation

The interquartile range, or IQR, measures the spread of the middle half of your data. To find the IQR, you first need to identify the first quartile (Q1Q_1) and the third quartile (Q3Q_3). The IQR is then calculated by simply subtracting the value of Q1Q_1 from the value of Q3Q_3. This value represents the range of the central 50% of the data and is less sensitive to extreme values, or outliers, than the total range.