1. BBADMC
102
BWU-BBD-21-014

3. Introduction to Boxplot
What is Box plot
Representing the data
Via Boxplot
Affect on Mean, Median, Mode
Example & theory
What Are The Outlier
Definition & Example
Types of outliers
Describing 3 types
Reason for Outliers
4 reason for outliers
How to Find Outliers
Steps & Example
SLIDE 3
SLIDE 16
SLIDE 15
SLIDE 11
SLIDE 10
SLIDE 7
SLIDE 14

4. What Are The Outliers ?
Outliers are extreme values.
Extremely high or low values in a data set.
In a data set outliers may include sample maximum or minimum or
both.
It indicate that distribution is heavy tailed or highly skewed.

5. Q1. For Example.
1.5, 2.1, 2.5, 3, 3.1, 3.7, 4.1, 5, 9.5

6. Q3. For Example.
15, 1, 3, 3.5, 2.1, 4.2, 3.1, 5
Q2. For Example.
1, 3, 5, 6, 7, 9, 10, 12, 22

7. Outliers
Global
Outlier
Contextual
Outlier
Collective
Outlier
Types of outliers ?

8. a. Global outliers .
when a data object differ from the rest of the given data
kkkset, it is considered to be global outliers.
b. Contextual outliers.
A contextual is a data object anomalous within its context
kkkor its neighborhood.
c. Collective outliers.
if a collection of related data instance is anomalous with
kkkrespect to the entire data set, it is termed as a collective
kkkoutliers.

9. a. Global outlier c. Collective outlier
b.
Contextual
outlier

10. Reason For Outliers ?
 Data entry error.
 Instrumental error.
 System faults.
 Measurement error.

11. How To Identify Outliers ?
A data value less than Q1 – 1.5(IQR) or greater
than Q3 + 1.5(IQR) can be considered an
outlier.

12. Steps To Find Outliers
Arrange the data in order from lowest to highest and find Q1 and Q3.
Find the interquartile range (IQR) Q3 – Q1.
Multiply IQR by 1.5.
Subtract step 3 from Q1 and add in Q3.
Check the data set for any data value that is smaller than Q1 – 1.5(IQR) or
larger than Q3 + 1.5(IQR)

13. 1. Arrange the data & find Q1, Q3 .
7, 10, 11, 15, 25, 30, 35, 68
Q1. = 10.5 Q3 = 32.5
2. Find the IQR (Q3 – Q1)
= 32.5 – 10.5
= 22
3. Multiply IQR by 1.5
= 33
4. Subtract IQR from Q1 & add in Q3 10.5 – 33 = -22.5
32.5 + 33 = 65.5
5. Check the data set for any data value that is smaller than Q1 – 1.5(IQR) or larger than Q3 + 1.5(IQR).
68 is the outliers
Example
10, 11, 15, 25, 35, 30, 7, 68

14. Box Plots At A Glance
Outliers
Outliers
Min.
value
Max.
value
Q3
Q2
&
Median
Q1
Q3 – Q1
IQR

15. Represent In Box Plot
Q1. = 10.5
Q2 = 20
Q3 = 32.5
Outlier = 68
Min value = 7
Max value = 35
7(Min)
10.5(Q1 ) 20(Q2 ) 25(Q3)
35(Max)
68(Outliers)
Median

16. Affect On Mean, Median, Mode.

17. Without
Outlier
With Outlier

18. Affects
Mode is not affected by outlier.
Median is also not so affected.
Mean is more affected as mean depends on average of all data.
• Low outlier tend to shift mean more negatively than median.
• High outlier tend to shift mean more positively than median.

19. QUOTE
 
A single death is a
tragedy; a million deaths
is a statistics.
- Joseph Stalin
Thank you…