Module 9 · Lesson 18 of 22
Quartiles, interquartile range, and mean deviation
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Learning objectives
- Compute quartiles, IQR and mean absolute deviation in a free spreadsheet.
- Use robust summaries for skewed garment data.
- Flag exploratory outliers without automatic deletion.
Core idea
Quartiles split ordered data into four parts; IQR = Q3 − Q1 summarises the middle 50%; mean absolute deviation is the mean distance from a declared centre.
Spreadsheet lab
- Q1 = =QUARTILE.INC(A2:A31, 1); Q3 = =QUARTILE.INC(A2:A31, 3).
- IQR = Q3 − Q1.
- MAD (about mean) = =AVERAGE(ABS(A2:A31 - AVERAGE(A2:A31))) entered as array.
- Outlier fences (exploratory only): below Q1 − 1.5·IQR or above Q3 + 1.5·IQR.
Garment-factory example
Repair minutes per garment on a skewed style: Q1 = 3.0, median = 4.5, Q3 = 8.0 → IQR = 5.0. Points beyond Q3 + 1.5·IQR = 15.5 are flagged for cause investigation, not deleted.
Method
- Choose median/IQR when data are skewed.
- State the quartile convention (inclusive vs exclusive).
- Investigate flagged points; delete only with cause.
Common mistakes
- Deleting flagged points to make results 'look nicer'.
- Using different quartile conventions between reports.
Knowledge check
Pick one answer per question. Explanations appear after you submit.
1. Which pair of functions produce Q1 and Q3?
2. A point beyond Q3 + 1.5·IQR should be:
Author: NOSK.life · Last reviewed: 2026-07-21