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Measures of Spread

Two data sets can have exactly the same mean and still look nothing alike — one tightly clustered, one scattered everywhere. A measure of spread describes how far apart the values in a data set are, which is the half of the story a measure of center leaves out.

Algebra 1 uses three measures of spread: the range, the interquartile range (IQR), and the standard deviation. The range is the fastest to compute, the IQR is the most resistant to outliers, and the standard deviation is the most complete.

The three measures of spread

Range: maximum - minimum. One subtraction, but fragile — a single extreme value changes it completely.

Interquartile range: IQR=Q3Q1IQR = Q_3 - Q_1, the spread of the middle half of the data. Because it ignores the top and bottom quarters, outliers cannot touch it.

Standard deviation: the typical distance of a value from the mean. A small standard deviation means the values huddle near the mean; a large one means they scatter. In Algebra 1 you usually interpret it or let a calculator compute it rather than grinding it out by hand.

A box plot makes the difference between range and IQR visible: the whiskers reach the minimum and maximum (the range), while the box runs only from Q1Q_1 to Q3Q_3 (the IQR, the middle half).

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Finding quartiles

Order the data and find the median. Then Q1Q_1 is the median of the lower half and Q3Q_3 is the median of the upper half. When the data set has an odd number of values, leave the overall median out of both halves.

For 3,5,6,8,10,12,153, 5, 6, 8, 10, 12, 15 the median is 88. The lower half is 3,5,63, 5, 6, so Q1=5Q_1 = 5; the upper half is 10,12,1510, 12, 15, so Q3=12Q_3 = 12; and IQR=125=7IQR = 12 - 5 = 7.

Which measure to trust

Pair your measure of spread with your measure of center. Symmetric data with no outliers: mean with standard deviation. Skewed data or data with outliers: median with IQR, because the extreme values pull both the mean and the range but leave the median and IQR alone.

Worked examples

Example 1: find the range

Find the range of 23, 9, 17, 31, 1223,\ 9,\ 17,\ 31,\ 12.

Find the extremesmaximum=31,minimum=9\text{maximum} = 31,\quad \text{minimum} = 9
Subtract319=2231 - 9 = 22

Answer: Range =22= 22

Example 2: find the IQR

Find the interquartile range of 3, 5, 6, 8, 10, 12, 153,\ 5,\ 6,\ 8,\ 10,\ 12,\ 15.

The data is in order; the median is the middle valuemedian=8\text{median} = 8
Take the median of the lower half 3,5,63, 5, 6Q1=5Q_1 = 5
Take the median of the upper half 10,12,1510, 12, 15Q3=12Q_3 = 12
SubtractIQR=125=7IQR = 12 - 5 = 7

Answer: IQR=7IQR = 7

Example 3: same range, different spread

Set A is 10, 10, 10, 10, 2010,\ 10,\ 10,\ 10,\ 20 and Set B is 10, 12, 15, 18, 2010,\ 12,\ 15,\ 18,\ 20. Compare their spreads.

Both ranges are the same2010=1020 - 10 = 10
Find each IQR: Set A has Q1=10Q_1 = 10, Q3=10Q_3 = 10, so IQR=0IQR = 0; Set B has Q1=12Q_1 = 12, Q3=18Q_3 = 18, so IQR=6IQR = 6
Set A's middle half does not vary at all — its spread comes from one value, 2020

Answer: Same range, but Set B's values are genuinely more spread out (IQR=6IQR = 6 vs. 00)

Try one yourself

Common questions

Why is the IQR better than the range when there are outliers?

The range depends only on the two most extreme values, which is exactly where outliers live. The IQR is built from Q1Q_1 and Q3Q_3, the edges of the middle half, so an outlier at either end never enters the calculation.

What does a standard deviation of 0 mean?

Every value in the data set is identical. No value sits any distance from the mean, so the typical distance is 00. Any variation at all makes the standard deviation positive.

Do I include the median when splitting the data into halves?

With an odd number of values, no — set the middle value aside and take the median of each remaining half. With an even number of values, the data splits cleanly into two halves and nothing is left out.

Can two data sets have the same center but different spreads?

Yes, easily. 9,10,119, 10, 11 and 0,10,200, 10, 20 both have a mean of 1010, but the second set is far more spread out. That is exactly why you report a measure of spread alongside a measure of center.

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