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Lucy Sarah Blaisse Flores-Anas
Discussant
EDUCATION 309 – STATISTICS FOR
EDUCATIONAL RESEARCH
TOPIC: MEASURES OF VARIABILITY -
QUARTILE DEVIATION
• Quantiles are the extensions of the median
concept because they are values which divide a
set of data into equal parts.
a. Median – divides the distribution into two
equal parts.
b. Quartile – divides the distribution into four
equal parts.
c. Decile – divides the distribution into ten equal
parts.
d. Percentile – divides the distribution into one
hundred equal parts.
Quartiles are values in a given set of distribution
that divide the data into four equal parts. Each set
of scores has three quartiles. These values can be
denoted by Q1, Q2 and Q3.
 First quartile - Q1 (lower quartile) – The middle
number between the smallest number and the
median of the data set (25th Percentile).
 Second quartile - Q2 – The median of the data
that separates the lower and upper quartile
(50th Percentile).
 Third quartile - Q3 – (upper quartile)
The middle value between the
and the highest value of the
data set (75th Percentile).
• The difference between the upper
and lower quartiles is called the
Interquartile range. (IQR = Q3-Q1)
• Quartile deviation or Semi-
interquartile range is one-half the
difference between the first and
the third quartiles. (QD = Q3-Q1/2)
GETTING THE QUARTILE DEVIATION
FROM UNGROUPED DATA
• In getting the quartile deviation from ungrouped data,
the following steps are used in getting the quartiles:
• Arrange the test scores from highest to lowest.
• Assign serial numbers to each score. The first serial
number is assigned to the lowest test score, while the last
serial number is assigned to the highest test score.
• Determine the first quartile (Q1). To be able to locate Q1,
divide N by 4. Use the obtained value in locating the
serial number of the score that falls under Q1.
• Determine the third quartile (Q3), by dividing 3N by 4.
Locate the serial number corresponding to the obtained
answer. Opposite this number is the test score
corresponding to Q3.
• Subtract Q1 from Q3 and divide the difference by 2.
Score
Serial
Number
17
17
26
27
30
30
31
37
N = 8
1
2
3
4
5
6
7
8
Consider the test Scores table below:
𝑁
4
=
8
4
= 2
Q1 = (
17+ 26
2
)
= 21.5
QD = (
𝑄3−𝑄1
2
)
= (
30.5−21.5
2
)
= 4.5
3𝑁
4
=
3(8)
4
= 6
Q3 = (
30+31
2
)
= 30.5
GETTING THE QUARTILE DEVIATION
FROM GROUPED DATA
1. Cumulate the frequencies from the bottom to
the top of the grouped frequency distribution.
2. For the first quartile, use the formula
L = exact lower limit if the Q1 class
N/4 = locator of the Q1 class
N = total number of scores
CF = cumulative frequency below
the Q1 class
i = class size/interval
where:
Q1 =L +
𝑵
𝟒
− 𝑪𝑭
𝒇
(i)
3. For the third quartile, use the formula
Q3 = L +
𝟑𝑵
𝟒
− 𝑪𝑭
𝒇
(i)
L = exact lower limit if the Q3 class
3N/4 = locator of the Q3 class
N = total number of scores
CF = cumulative frequency below the Q3 class
i = class size/interval
where:
COMPUTATION OF THE QUARTILE
DEVIATION FOR GROUPED TEST SCORES
Classes
Frequency
(f)
Cumulative
Frequency (CF)
46-50
41-45
36-40
31-35
26-30
21-25
16-20
11-15
5
7
9
10
8
6
4
4
N = 53
53
48
41
32
33
14
8
4
𝑵
𝟒
=
𝟓𝟑
𝟒
= 13. 25
CF = 8 f = 6 L = 20.5
Q1 = L +
𝑵
𝟒
− 𝑪𝑭
𝒇
(i)
= 20. 5 +
𝟏𝟑.𝟐𝟓− 𝟖
𝟔
(5)
= 20. 5 +
𝟓.𝟐𝟓
𝟔
(5)
= 20. 5 +
𝟑𝟏.𝟓
𝟔
= 25.75
The computational procedures for determining the quartile
deviation for grouped test scores are reflected in the above table.
For the first quartile
𝟑𝑵
𝟒
=
𝟑(𝟓𝟑)
𝟒
= 40.5
CF = 32 f = 9 L = 35.5
Q3 = L +
𝟑𝑵
𝟒
− 𝑪𝑭
𝒇
(i)
= 35.5 +
𝟒𝟎.𝟓 − 𝟑𝟐
𝟓
(5)
= 35.5 +
𝟖.𝟓
𝟓
(5)
= 35.5 +
𝟒𝟐.𝟓
𝟔
= 40.22
For the third quartile
Thus QD = (
𝑸𝟑−𝑸𝟏
𝟐
)
After obtaining the first and third quartiles, we
can now compute QD.
QD = (
𝟒𝟎.𝟐𝟐−𝟐𝟓.𝟕𝟓
𝟐
)
= (
𝟏𝟒.𝟒𝟕
𝟐
)
= 7.235 or 7.24
Thank you and God Bless us all!

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Education 309 – Statistics for Educational Research

  • 1. Lucy Sarah Blaisse Flores-Anas Discussant EDUCATION 309 – STATISTICS FOR EDUCATIONAL RESEARCH TOPIC: MEASURES OF VARIABILITY - QUARTILE DEVIATION
  • 2. • Quantiles are the extensions of the median concept because they are values which divide a set of data into equal parts. a. Median – divides the distribution into two equal parts. b. Quartile – divides the distribution into four equal parts. c. Decile – divides the distribution into ten equal parts. d. Percentile – divides the distribution into one hundred equal parts.
  • 3. Quartiles are values in a given set of distribution that divide the data into four equal parts. Each set of scores has three quartiles. These values can be denoted by Q1, Q2 and Q3.  First quartile - Q1 (lower quartile) – The middle number between the smallest number and the median of the data set (25th Percentile).  Second quartile - Q2 – The median of the data that separates the lower and upper quartile (50th Percentile).  Third quartile - Q3 – (upper quartile) The middle value between the and the highest value of the data set (75th Percentile).
  • 4. • The difference between the upper and lower quartiles is called the Interquartile range. (IQR = Q3-Q1) • Quartile deviation or Semi- interquartile range is one-half the difference between the first and the third quartiles. (QD = Q3-Q1/2)
  • 5. GETTING THE QUARTILE DEVIATION FROM UNGROUPED DATA • In getting the quartile deviation from ungrouped data, the following steps are used in getting the quartiles: • Arrange the test scores from highest to lowest. • Assign serial numbers to each score. The first serial number is assigned to the lowest test score, while the last serial number is assigned to the highest test score. • Determine the first quartile (Q1). To be able to locate Q1, divide N by 4. Use the obtained value in locating the serial number of the score that falls under Q1. • Determine the third quartile (Q3), by dividing 3N by 4. Locate the serial number corresponding to the obtained answer. Opposite this number is the test score corresponding to Q3. • Subtract Q1 from Q3 and divide the difference by 2.
  • 6. Score Serial Number 17 17 26 27 30 30 31 37 N = 8 1 2 3 4 5 6 7 8 Consider the test Scores table below: 𝑁 4 = 8 4 = 2 Q1 = ( 17+ 26 2 ) = 21.5 QD = ( 𝑄3−𝑄1 2 ) = ( 30.5−21.5 2 ) = 4.5 3𝑁 4 = 3(8) 4 = 6 Q3 = ( 30+31 2 ) = 30.5
  • 7. GETTING THE QUARTILE DEVIATION FROM GROUPED DATA 1. Cumulate the frequencies from the bottom to the top of the grouped frequency distribution. 2. For the first quartile, use the formula L = exact lower limit if the Q1 class N/4 = locator of the Q1 class N = total number of scores CF = cumulative frequency below the Q1 class i = class size/interval where: Q1 =L + 𝑵 𝟒 − 𝑪𝑭 𝒇 (i)
  • 8. 3. For the third quartile, use the formula Q3 = L + 𝟑𝑵 𝟒 − 𝑪𝑭 𝒇 (i) L = exact lower limit if the Q3 class 3N/4 = locator of the Q3 class N = total number of scores CF = cumulative frequency below the Q3 class i = class size/interval where:
  • 9. COMPUTATION OF THE QUARTILE DEVIATION FOR GROUPED TEST SCORES Classes Frequency (f) Cumulative Frequency (CF) 46-50 41-45 36-40 31-35 26-30 21-25 16-20 11-15 5 7 9 10 8 6 4 4 N = 53 53 48 41 32 33 14 8 4
  • 10. 𝑵 𝟒 = 𝟓𝟑 𝟒 = 13. 25 CF = 8 f = 6 L = 20.5 Q1 = L + 𝑵 𝟒 − 𝑪𝑭 𝒇 (i) = 20. 5 + 𝟏𝟑.𝟐𝟓− 𝟖 𝟔 (5) = 20. 5 + 𝟓.𝟐𝟓 𝟔 (5) = 20. 5 + 𝟑𝟏.𝟓 𝟔 = 25.75 The computational procedures for determining the quartile deviation for grouped test scores are reflected in the above table. For the first quartile 𝟑𝑵 𝟒 = 𝟑(𝟓𝟑) 𝟒 = 40.5 CF = 32 f = 9 L = 35.5 Q3 = L + 𝟑𝑵 𝟒 − 𝑪𝑭 𝒇 (i) = 35.5 + 𝟒𝟎.𝟓 − 𝟑𝟐 𝟓 (5) = 35.5 + 𝟖.𝟓 𝟓 (5) = 35.5 + 𝟒𝟐.𝟓 𝟔 = 40.22 For the third quartile
  • 11. Thus QD = ( 𝑸𝟑−𝑸𝟏 𝟐 ) After obtaining the first and third quartiles, we can now compute QD. QD = ( 𝟒𝟎.𝟐𝟐−𝟐𝟓.𝟕𝟓 𝟐 ) = ( 𝟏𝟒.𝟒𝟕 𝟐 ) = 7.235 or 7.24
  • 12. Thank you and God Bless us all!