← ACARA Digital Technologies Years 7–8

Deciding what to do with an outlier

Check if an outlier is a typing error or a real extreme value. Fix errors, keep real values, and compare results with and without it. Never delete data just to fit your story.

Part of: ACARA Digital Technologies Years 7–8 — Analysing and Visualising Data — Module 35, ACARA Digital Technologies Years 9–10 — Analysing and Visualising Data — Module 41

Understanding Deciding what to do with an outlier in ACARA Digital Technologies Years 7–8

What it does: A typing error is fixed to the true value found in the source, so the data becomes accurate again. A real extreme value is kept. The median stays steady, so comparing it with the mean shows how much the outlier changes the result. 0.9 seconds is not humanly possible, so it is almost certainly an error. Always investigate before deciding. Deleting data just to fit a story is dishonest and creates bias. Decisions about outliers need a real reason. The IQR rule only flags possible outliers. It does not tell you to remove them. You still need to investigate. Being open about an outlier and its effect lets readers trust your conclusions.

Common mistakes: A typing error should be corrected using the source record, not deleted. It should read: IF typing error THEN fix it. You should report the effect of the outlier by showing both means, with and without it. Showing only one hides the effect. It should be: Report both means.

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Free printable worksheet with full answer key — or add this module to a class and your students practise it interactively.

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This module's key terms are also in a printable crossword (Modules 302–324) and word search (Modules 261–324).

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Learning
Duo
A class survey shows one student's height as 1750 cm. What should you do first?
Keep it, because every number in a data set must stay exactly as typedInvestigate: it is probably a typing error for 175 cm, so check the source and fix it
Matches
Delete row 7 because it ruins my trend line
↓
Deleting data just to fit your story is dishonest. The outlier was not checked first.
Applying
Meanings
Term
Investigate the outlier
Meaning
Check if an outlier is a typing error or a real extreme value. Fix errors, keep real values, and compare results with and without it. Never delete data just to fit your story.
Practice
=AVERAGE(D2:D8)-AVERAGEIF(D2:D8,"<20")
Testing
Gaps
=(B2:B9,">200")
Check Answer
Spots
2check the source record
3IF typing error THEN delete it

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Quick Questions

1. A class survey shows one student's height as 1750 cm. What should you do first?
A. Investigate: it is probably a typing error for 175 cm, so check the source and fix it ✓
B. Keep it, because every number in a data set must stay exactly as typed
An impossible value like 1750 cm is likely a typing error. Check the original source and correct it rather than leaving it in.
2. A shop's sales data has one day with sales far higher than usual. The receipts confirm it was a real Christmas Eve rush. What do you do?
A. Delete it, because it is much bigger than the other values
B. Keep it, because it is a real extreme value, and mention it in your report ✓
A real extreme value is genuine data. Delete it only if there is a good reason, and never just because it is unusual.
3. Which approach shows the effect of an outlier on your results?
A. Calculate the mean with the outlier and again without it, then compare ✓
B. Calculate the mean once and hope the outlier does not matter
Comparing results with and without the outlier shows how much it changes the answer, so you can report that effect honestly.
4. Your data shows one runner finishing a 100 m sprint in 0.9 seconds. The most likely explanation is:
A. A real world record that you should keep without checking
B. A typing error, such as 9.0 or 10.9, which you should check against the source ✓
0.9 seconds is not humanly possible, so it is almost certainly an error. Always investigate before deciding.
5. Your graph does not support your argument because of one unusual point. Is it okay to delete that point so the graph fits your story?
A. No. Only remove data if you can show it is an error, and explain what you did ✓
B. Yes. Removing awkward points makes the conclusion clearer
Deleting data just to fit a story is dishonest and creates bias. Decisions about outliers need a real reason.

Match the Pairs

=AVERAGE(B2:B30)-AVERAGEIF(B2:B30,"<>"&MAX(B2:B30)) → Compare the mean with and without the biggest value to see how much one outlier pulls the result
=IF(B7>100,"Check source","OK") → Flag a suspicious value so you can investigate it instead of deleting it
If the outlier is a typing error, correct it using the original record (for example 950 should be 95) → B7 = 95
Report the effect of a real outlier by finding the median, which is less affected by it, next to the mean → =MEDIAN(B2:B30)
Delete row 7 because it ruins my trend line → Deleting data just to fit your story is dishonest. The outlier was not checked first.
Mia scored 950 out of 100, so keep it as real data → A mark of 950 out of 100 is impossible, so it is almost certainly a typing error, not a real value.

Key Term

Investigate the outlier
Check if an outlier is a typing error or a real extreme value. Fix errors, keep real values, and compare results with and without it. Never delete data just to fit your story.

Fill in the Blanks

1. =COUNTIF(B2:B9,">200")
Hint: Type the function that counts how many cells meet a condition, to see how many values are suspiciously high.
2. =IF(B2>$F$1,"Check","OK")
Hint: Type the comparison operator that tests whether a value is greater than the limit, so it gets flagged for investigation.
3. =MEDIAN(B2:B9)
Hint: Type the function that finds the middle value, so you can compare it with the mean when an outlier is present.
4. =F2+1.5*(F2-F1)
Hint: Type the multiplier from the IQR rule that sets the upper fence for outliers.
5. =AVERAGE(B2:B9)-AVERAGEIF(B2:B9,"<200")
Hint: Type the arithmetic operator that finds the difference between the mean with the outlier and the mean without it.

Spot the Error

Question 1
A outlier ← 980
B check the source record
C IF typing error THEN delete it
D ELSE keep the value
E report the effect
Line C — A typing error should be corrected using the source record, not deleted. It should read: IF typing error THEN fix it.
Question 2
A Mean with outlier is 95
B Mean without it is 60
C The outlier raises the mean
D Report only the mean of 60
Line D — You should report the effect of the outlier by showing both means, with and without it. Showing only one hides the effect. It should be: Report both means.
Question 3
A Age column: 15, 16, 15, 160
B 160 is a real age, so keep it
C Check the survey form
D Correct 160 to 16
Line B — No student is 160 years old, so it is most likely a typing error. It should say 160 is likely a typing error, which leads to checking and correcting it.
Question 4
A Sprint times: 13, 14, 13, 9.6
B Check the timing record
C 9.6 was recorded correctly
D Change 9.6 to 13 to match
Line D — The record confirms 9.6 is a real extreme value. Real values must be kept, not changed to fit the pattern. It should be: Keep 9.6 and note it is real.
Question 5
A mean ← AVERAGE(B2:B9)
B median ← AVERAGE(B2:B9)
C Compare the two results
D Report the effect of B9
Line B — The median must be found with MEDIAN, not AVERAGE. Using AVERAGE twice gives the same result, so you cannot compare the effect of the outlier. It should be: median ← MEDIAN(B2:B9).

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