Outlier Detection Examples: 46 Problems with Answers
Start with the recap, study the fully worked examples, then use the practice problems to
check your understanding of Outlier Detection.
This page combines explanation, solved examples, and follow-up practice so you can move
from recognition to confident problem-solving in Statistics.
Concept Recap
Outlier detection is the process of identifying data points that are unusually far from the rest of the dataset, using techniques like the IQR rule, z-scores, or visual inspection of box plots and scatter plots. These anomalous values may indicate measurement errors, data entry mistakes, or genuinely extreme observations.
Outliers are data points that don't fit the pattern. A 7-foot student in a class of average heights, or a $10 million house in a neighborhood of $300k homes. They may be errors or genuinely unusual.
Read the first worked example with the solution open so the structure is clear.
Try the practice problems before revealing each solution.
Use the related concepts and background knowledge badges if you feel stuck.
What to Focus On
Core idea:Outlier Detection asks how a value or feature behaves inside the full distribution.
Common stuck point:Students often know a procedure related to outlier detection but skip the recognition step: Am I interpreting the whole distribution or a value position inside it, rather than just computing a single summary? That leads to a calculation or graph that looks reasonable but answers a different question.
Sense of Study hint:Ask: Am I interpreting the whole distribution or a value position inside it, rather than just computing a single summary?
Common Mistakes to Watch For
Before you work through the examples, skim the mistake guide so you know which shortcuts and
sign errors to avoid.
A normally distributed quality test has mean 100, SD 10. How likely is a true measurement above 130, under the ∣z∣>3 rule?
Example 3
easy
The data set is: 10, 12, 11, 13, 12, 14, 11, 50. Identify the outlier and explain how you know.
Example 4
medium
Test scores: 72, 75, 78, 80, 82, 85, 88, 90, 92, 95. A new student's score of 25 is added. How does this outlier affect the mean and median?
Practice Problems
Try these problems on your own first, then open the solution to compare your method.
Example 1
easy
By the IQR rule, an outlier lies below Q1−1.5⋅IQR or above which bound?
Example 2
easy
A data set has Q1=10 and Q3=20. Find the IQR.Find the IQR from this box plot.
Example 3
easy
With Q1=10, Q3=20, IQR=10, find the lower fence Q1−1.5⋅IQR.Find the lower fence Q₁ − 1.5·IQR.
Example 4
easy
With Q1=10, Q3=20, IQR=10, find the upper fence Q3+1.5⋅IQR.Find the upper fence Q₃ + 1.5·IQR.
Example 5
easy
Fences are −5 (lower) and 35 (upper). Is the value 40 an outlier?Fences are −5 and 35. Is 40 an outlier?
Example 6
easy
Using z-scores, a common rule flags a value as an outlier when ∣z∣ exceeds what threshold?
Example 7
easy
Should you always delete an outlier as soon as you find one?
Example 8
easy
A box plot shows an isolated point far beyond the right whisker. What does it represent?
Example 9
medium
Data: 3,5,7,8,9,12,50 has Q1=5, Q3=12. Is 50 an outlier by the IQR rule?Is 50 an outlier? (Q₁
Example 10
medium
Data with Q1=20, Q3=40. What are both IQR-rule fences?Find both IQR-rule fences for Q₁
Example 11
medium
A value is 8, the mean is 20, and the SD is 4. Is it an outlier by the ∣z∣>3 rule?
Example 12
medium
Data: 1,2,2,3,3,3,4,100. Which value is the obvious outlier and why?
Example 13
medium
An outlier of 100 is removed from a small data set. What happens to the mean and the SD?
Example 14
medium
Why might using ONLY the z-score method miss outliers in a skewed data set?
Example 15
medium
Data: 5,6,7,8,9 with Q1=6, Q3=8. Is the maximum value 9 an outlier?Is the maximum value 9 an outlier? (Q₁
Example 16
medium
A scatter plot point sits far from an otherwise tight linear trend. What is it called and what might it indicate?
Example 17
medium
Data 4,6,8,10,12 has Q1=5, Q3=11. Are there any outliers by the IQR rule?Are there any IQR-rule outliers? (Q₁
Example 18
challenge
Data: 2,4,6,8,10,12,14,16 with Q1=5, Q3=13. Find both fences and state whether any value is an outlier.
Example 19
challenge
For data 10,12,14,16,18,20,100 with Q1=12, Q3=20, show 100 is an outlier and explain why the mean is a poor center here.Is 100 an outlier? (Q₁
Example 20
challenge
Explain why the IQR rule is more robust to extreme values than the z-score rule (one concise reason).
Example 21
easy
A data set has Q1=30 and Q3=50. Find the IQR.Find the IQR. (Q₁
Example 22
easy
With Q1=30,Q3=50,IQR=20, what is the upper fence?Find the upper fence. (Q₁
Example 23
easy
With Q1=30,Q3=50,IQR=20, what is the lower fence?
Example 24
easy
The mean is 50, SD is 5. Compute the z-score for x=70.
Example 25
easy
True or false: outliers should always be removed before analysis.
Example 26
easy
Data: 4,5,6,7,8,9,100. Which value is most likely an outlier?
Example 27
medium
A value has z-score −2.5 in a roughly normal distribution. By the ∣z∣>3 rule, is it an outlier?
Example 28
medium
Data: {1,2,3,4,5,6,7,8,9,50}. Find Q1,Q3, and check if 50 is an outlier.Find Q₁, Q₃, and check if 50 is an outlier.
Example 29
medium
In a strongly right-skewed distribution, IQR-rule outliers tend to appear on which side more often?
Example 30
medium
For Q1=12,Q3=20, is 30 an outlier by the IQR rule?
Example 31
medium
A z-score is calculated as z=−3.4 for some value x. What does that mean?
Example 32
medium
A box plot shows the median near the BOX bottom, a short lower whisker, and one point far above the upper whisker. Most likely shape and outliers?What shape does this box plot suggest, and what is the isolated point?
Example 33
hard
Data {2,4,4,5,6,7,8,9,12} has Q1=4,Q3=8. Identify any IQR-rule outliers.Identify any IQR-rule outliers. (Q₁
Example 34
hard
A teacher records 30 students' typing speeds. A z-score ∣z∣>3 rule flags two values. What should the teacher do?
Example 35
hard
Why does the IQR rule generally identify FEWER outliers than the ∣z∣>3 rule for skewed data?
Example 36
hard
With Q1=25,Q3=75, find both IQR-rule fences.
Example 37
hard
A modified IQR rule uses fences at Q1−3⋅IQR and Q3+3⋅IQR. Compared to the standard 1.5⋅IQR rule, what does it flag?
Example 38
medium
For ages of attendees at a children's birthday party, the value 42 appears next to a long list of values from 4 to 10. Is 42 likely an outlier?
Example 39
hard
For data {0.5,1,1.2,1.5,1.8,2,2.2,5} with Q1=1.1,Q3=2.1, is 5 an outlier?Is 5 an outlier? (Q₁
Example 40
challenge
A data set of 50 values is symmetric and approximately normal with μ=0,σ=1. Roughly how many values would you expect to be flagged by the ∣z∣>3 rule?
Example 41
medium
A scientist records reaction times (ms): 245, 260, 255, 270, 250, 980, 265, 258. Use the 1.5×IQR rule to determine if 980 is an outlier. Should it be removed from the analysis?
Example 42
hard
A data set has mean xˉ=100 and standard deviation s=15. Using the z-score method, determine whether the values 60, 145, and 155 are outliers (using the threshold ∣z∣>2).