beginner 20 minutes

Percentiles and Quartiles

Master percentiles, quartiles, and the five-number summary. Learn to interpret relative standing and identify outliers using the IQR method.

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What Are Percentiles?

A percentile indicates the percentage of data values that fall at or below a given value. Percentiles describe relative standing within a dataset.

Understanding Percentiles

If your score is at the 75th percentile:

  • 75% of scores are at or below yours
  • 25% of scores are above yours
  • You performed better than approximately 3/4 of test-takers

Common applications:

  • Standardized test scores (SAT, GRE)
  • Growth charts for children
  • Income distributions
  • Performance rankings

Calculating Percentiles

Finding the Percentile of a Value

To find what percentile a value xx represents:

Percentile Rank

Percentile Rank=Number of valuesxTotal number of values×100\text{Percentile Rank} = \frac{\text{Number of values} \leq x}{\text{Total number of values}} \times 100

Calculating Percentile Rank

Data (sorted): 52, 58, 63, 67, 71, 74, 78, 82, 85, 91

What percentile is a score of 74?

Values ≤ 74: 52, 58, 63, 67, 71, 74 → 6 values Total values: 10

Percentile=610×100=60th percentile\text{Percentile} = \frac{6}{10} \times 100 = 60\text{th percentile}

A score of 74 is at the 60th percentile.

Finding a Value at a Given Percentile

To find the value at the PPth percentile:

Locating a Percentile

L=P100×(n+1)L = \frac{P}{100} \times (n + 1)

Where:

  • LL = position (location) in the sorted data
  • PP = desired percentile
  • nn = number of data points
Finding the 40th Percentile

Data (sorted): 12, 18, 23, 27, 31, 35, 42, 48, 55, 62 (n = 10)

Find the 40th percentile:

L=40100×(10+1)=0.4×11=4.4L = \frac{40}{100} \times (10 + 1) = 0.4 \times 11 = 4.4

Position 4.4 means: 40% of the way between the 4th and 5th values.

  • 4th value = 27
  • 5th value = 31

P40=27+0.4×(3127)=27+1.6=28.6P_{40} = 27 + 0.4 \times (31 - 27) = 27 + 1.6 = 28.6

The 40th percentile is 28.6.

Quartiles: Special Percentiles

Quartiles divide data into four equal parts:

QuartilePercentileMeaning
Q125thFirst quartile - 25% below
Q250thSecond quartile = Median
Q375thThird quartile - 75% below
Quartiles Visualized
|-------|-------|-------|-------|
Min    Q1     Q2     Q3     Max
      (25%)  (50%)  (75%)
       ↓      ↓      ↓
     25%    50%    75%
     below  below  below

Each section contains 25% of the data.

Calculating Quartiles

Method 1: Using Percentile Formula

  • Q1 = 25th percentile
  • Q2 = 50th percentile (median)
  • Q3 = 75th percentile

Method 2: Median of Halves

  1. Find the median (Q2)
  2. Q1 = median of the lower half
  3. Q3 = median of the upper half
Finding Quartiles (Odd n)

Data (sorted): 3, 7, 12, 15, 18, 21, 24, 28, 33 (n = 9)

Step 1: Find Q2 (median)

  • Middle position = (9+1)/2 = 5th value
  • Q2 = 18

Step 2: Find Q1 (median of lower half)

  • Lower half: 3, 7, 12, 15
  • Q1 = (7 + 12)/2 = 9.5

Step 3: Find Q3 (median of upper half)

  • Upper half: 21, 24, 28, 33
  • Q3 = (24 + 28)/2 = 26

Quartiles: Q1 = 9.5, Q2 = 18, Q3 = 26

Finding Quartiles (Even n)

Data (sorted): 5, 8, 12, 15, 19, 22, 26, 31 (n = 8)

Step 1: Find Q2 (median)

  • Q2 = (15 + 19)/2 = 17

Step 2: Find Q1 (median of lower half)

  • Lower half: 5, 8, 12, 15
  • Q1 = (8 + 12)/2 = 10

Step 3: Find Q3 (median of upper half)

  • Upper half: 19, 22, 26, 31
  • Q3 = (22 + 26)/2 = 24

Quartiles: Q1 = 10, Q2 = 17, Q3 = 24

The Five-Number Summary

The five-number summary provides a compact description of a distribution:

Five-Number Summary
  1. Minimum (Min)
  2. First Quartile (Q1)
  3. Median (Q2)
  4. Third Quartile (Q3)
  5. Maximum (Max)
Five-Number Summary

Data: 12, 18, 23, 27, 31, 35, 42, 48, 55, 62, 71, 85

MeasureValue
Minimum12
Q125
Median38.5
Q358.5
Maximum85

Interpretation:

  • Range: 85 - 12 = 73
  • Middle 50% of data is between 25 and 58.5
  • The distribution appears slightly right-skewed (larger gap above median)

Interquartile Range (IQR)

The IQR measures the spread of the middle 50% of data.

Interquartile Range

IQR=Q3Q1IQR = Q_3 - Q_1

Calculating IQR

Given Q1 = 25 and Q3 = 58.5:

IQR=58.525=33.5IQR = 58.5 - 25 = 33.5

The middle 50% of values spans 33.5 units.

Why Use IQR?

MeasureAffected by Outliers?Best For
RangeYes (very sensitive)Quick overview
Standard DeviationYes (somewhat)Symmetric distributions
IQRNo (resistant)Skewed data, outliers present

Detecting Outliers with IQR

An outlier is an observation unusually far from other values. The IQR method defines outliers as:

Outlier Boundaries (Fences)

Lower fence=Q11.5×IQR\text{Lower fence} = Q_1 - 1.5 \times IQR Upper fence=Q3+1.5×IQR\text{Upper fence} = Q_3 + 1.5 \times IQR

Values outside these fences are outliers.

Identifying Outliers

Data: 2, 15, 18, 21, 24, 27, 30, 33, 36, 42, 98

Step 1: Find quartiles

  • Q1 = 18, Q3 = 36
  • IQR = 36 - 18 = 18

Step 2: Calculate fences

  • Lower fence = 18 - 1.5(18) = 18 - 27 = -9
  • Upper fence = 36 + 1.5(18) = 36 + 27 = 63

Step 3: Identify outliers

  • Below -9? No values
  • Above 63? 98 is an outlier!

Also note: 2 is low but not an outlier (2 > -9)

Extreme Outliers

Some analysts distinguish mild and extreme outliers:

  • Mild outlier: Beyond 1.5 × IQR but within 3 × IQR
  • Extreme outlier: Beyond 3 × IQR

Comparing Distributions with Percentiles

Percentiles allow fair comparison across different scales.

Comparing Test Scores

Student A: 720 on Math SAT (75th percentile) Student B: 28 on ACT Math (75th percentile)

Different tests, different scales, but same relative performance! Both scored better than 75% of test-takers.

Box Plots: Visualizing the Five-Number Summary

A box plot (box-and-whisker plot) displays the five-number summary graphically.

Box Plot Structure
     Min        Q1      Q2        Q3        Max
      |---------|========|=========|---------|
     12        25      38.5       58.5      85
               |_______ IQR _______|
                      = 33.5

Components:

  • Box: From Q1 to Q3 (contains middle 50%)
  • Line inside box: Median
  • Whiskers: Extend to min and max (within fences)
  • Points beyond whiskers: Outliers

Interpreting Box Plots

FeatureInterpretation
Box widthSpread of middle 50% (IQR)
Box positionWhere the middle of data lies
Median line positionSymmetry within middle 50%
Whisker lengthsSpread of data tails
Points beyondOutliers

Skewness from box plots:

  • Symmetric: Median centered, equal whiskers
  • Right-skewed: Median closer to Q1, longer right whisker
  • Left-skewed: Median closer to Q3, longer left whisker

Deciles and Other Quantiles

Quantiles divide data into equal parts:

NameDivisionsCommon Percentiles
Quartiles4 parts25th, 50th, 75th
Quintiles5 parts20th, 40th, 60th, 80th
Deciles10 parts10th, 20th, …, 90th
Percentiles100 parts1st through 99th
Deciles

The 3rd decile (D3) = 30th percentile

Meaning: 30% of values fall below this point

Real-World Application

Pediatric Growth Charts

A child’s weight is at the 60th percentile for their age.

Interpretation:

  • 60% of children that age weigh less
  • 40% weigh more
  • The child is slightly above average but within normal range

Concern thresholds:

  • Below 5th percentile: May indicate underweight
  • Above 95th percentile: May indicate overweight

Pediatricians track percentiles over time—the trend matters more than a single measurement.

Income Distribution Analysis

U.S. household income percentiles (approximate):

PercentileIncome
25th (Q1)$35,000
50th (Median)$70,000
75th (Q3)$125,000
90th$200,000
99th$500,000+

IQR = 125,000125,000 - 35,000 = $90,000

The large gap between median and mean (mean ≈ $95,000) indicates right skew—high earners pull the mean up.

Summary

In this lesson, you learned:

  • Percentiles indicate relative standing (percent at or below)
  • Quartiles divide data into four equal parts (Q1, Q2, Q3)
  • The five-number summary includes Min, Q1, Median, Q3, Max
  • IQR = Q3 - Q1 measures spread of middle 50%
  • Outliers are beyond 1.5 × IQR from quartiles
  • Box plots visualize the five-number summary
  • Percentiles enable comparison across different scales
  • Median and IQR are resistant to outliers

Practice Problems

1. For the data: 5, 8, 12, 15, 18, 22, 25, 29, 33, 40

  • Find Q1, Q2, Q3, and IQR
  • Are there any outliers?

2. A student’s standardized test scores:

  • Math: 85th percentile
  • Reading: 70th percentile
  • Science: 92nd percentile

In which subject did they perform best relative to other students?

3. Given the five-number summary: 10, 25, 45, 60, 95

  • Calculate the IQR
  • Find the outlier fences
  • Would a value of 8 be an outlier? What about 100?
Click to see answers

1.

  • Q1 = (8 + 12)/2 = 10
  • Q2 = (18 + 22)/2 = 20
  • Q3 = (29 + 33)/2 = 31
  • IQR = 31 - 10 = 21

Outlier fences:

  • Lower: 10 - 1.5(21) = -21.5
  • Upper: 31 + 1.5(21) = 62.5

No outliers (all values between -21.5 and 62.5)

2. Science (92nd percentile) - they performed better than 92% of students, compared to 85% in Math and 70% in Reading.

3.

  • IQR = 60 - 25 = 35
  • Lower fence = 25 - 1.5(35) = 25 - 52.5 = -27.5
  • Upper fence = 60 + 1.5(35) = 60 + 52.5 = 112.5
  • 8 is NOT an outlier (8 > -27.5)
  • 100 is NOT an outlier (100 < 112.5)

Next Steps

Now that you understand percentiles and quartiles:

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