Variables
Sherine Shawky, MD, Dr.PH
Assistant Professor
Department of Community Medicine &
Primary Health Care
College of Medicine
King Abdulaziz University
Learning Objectives
• Understand the concept of
variable
• Distinguish the types of variables
• Recognize data processing
methods
Performance Objectives
• Select the variables relevant to
study
• Perform appropriate data
transformation
• Present data appropriately
Definition Of Variable
“A variable is any quantity
that varies. Any attribute,
phenomenon or event that
can have different values”
Information Supplied
By Variables
Indices of Person
Indices of Place
Indices of Time
Specification of Variable
Clear precise standard definition
Method of measurement
Scale of measurement
Role Of Variable
Correlation
Interdependent Interdependent
Role Of Variable
Association
Independent
Dependent
Independent
Confounding
Dependent
Independent
Effect
modifier
Dependent
Types of Variables
Quantitative
(continuous)
Qualitative
(Discrete)
I- Quantitative
Variables
• Data in numerical quantities that can
assume all possible values
• Data on which mathematical
operations are possible
• Example: age, weight, temperature,
haemoglobin level, RBCs count
II- Qualitative
Variables
Qualitative variables are those
having exact values that can fall into
number of separate categories with
no possible intermediate levels
Nominal
Ordinal
1- Nominal Variable
Unordered qualitative categories
Dichotomous
(2 categories)
Multichotomous
(> 2 categories)
2- Ordinal Variable
Ordered qualitative categories
Score
birth order
Categorical
social class
Numerical
discrete
parity
Continuous & Numerical
Discrete Variables
Continuous Variable
-3 -2 -1 0 1 2 3
Numerical Discrete
0 1 2 3
Types of Variables
- Quantitative
- Dichotomous
- Multichotomous
- Score
- Categorical
- Numerical
discrete
How much?
Who, How,
where, when,
What,…etc.?
How many?
Data Collection Tool
Age in years:
Gender:
1) male, 2) female
Social class:
1) low, 2) middle,
3) high
Height in cm:
.
Data Transformation
Data
Reduction
Creation of
composite variable
Data Reduction
Example
• Data: Age from 47 individuals
• Arrange in ascending order: 20, 21,
22, 23, 23, 24, 25, 29,29, 30, 30,
34, 34, 34, 34, 34, 34, 35, 35, 36,
37, 39, 39, 40, 43, 43, 43, 46, 46,
47, 47, 48, 48, 48, 50, 52, 56, 56,
58, 59, 59, 60, 62, 64, 64, 67, 69
Data Reduction
Example (cont.)
• Calculate the range: 69-20= 49
• No. of intervals= 5
• Width of class= 49/5 = 9.8  10
• Class intervals= 20-29, 30-39,
40-49, 50-59, 60-69
Data Reduction
Continuous: 20, 21, 22…….69
Interval: 20-29, 30-39, 40-49,
50-59, 60-69
Ordinal: Twenties, Thirties,
Forties, Fifties, Sixties
Nominal: Young or Old
Creation Of
Composite Variable
Single
variables
Quantitative
Composite
variable
Quantitative
Qualitative
Qualitative
Data Presentation
Tabular
Diagrammatic
Data Presentation
Variable
Nominal
Ordinal
Interval
Continuous
Table
-
Frequency
Percentage
Frequency
Percentage
Cumulative
frequency
- Cumulative
percentage
- Frequency
- Percentage
- Cumulative
frequency
- Cumulative
percentage
- Mean, SD
- Mean,
95 %CI
Chart
-
Pie
Column or Bar
Pie
Column or Bar
Linear
Ogive
- Histogram
- Frequency
polygon
- Ogive
- Scatter
- Box plot
Frequency Table
Family
Planning
None
Pills
IUDs
Others
Total
Freq
(no.)
98
65
22
15
200
%
49.0
32.5
11.0
7.5
100.0
Pie Chart
Column Chart
All categories Single Category
%
40
100%
80%
60%
40%
20%
0%
30
32,5
20,5
20
10
0
City A City B
None
IUDs
Pills
Others
City A City B
Pill Users
Bar Chart
All categories
Single Category
City B
City B
City A
City A
0% 20%40%60%80% 100
%
None
IUDs
Pills
Others
20,5
32,5
0
10 20 30 40
%
Pill Users
Frequency and Cumulative
Frequency Table
Breast
cancer
Stage I
Freq
(no.)
64
Stage II
32.0
Cum.
Freq
64
Cum
%
32.0
58
29.0
122
61.0
Stage III
43
21.5
165
82.5
Stage IV
35
17.5
200
100.0
200
100.0
200
100.0
Total
%
Linear Chart
Percentage
Ogive
(Cumulative
Percentage)
Stages of Breast Cancer
Frequency and Cumulative Frequency
Table for Variable of Interval
20-29
Freq
(no.)
9
30-39
%
19.1
Cum.
Freq
9
Cum
%
19.1
14
29.8
23
48.9
40-49
11
23.4
34
72.3
59-59
7
14.9
41
87.2
60-69
6
12.8
47
100.0
Total
47
100.0
47
100.0
Horizontal axis For Variable of Interval
Class
20-29
30-39
40-49
50-59
60-69
Histogram
Polygon
Boundaries Boundaries
Mid
(1)
(2)
point
Lower Upper Lower Upper
20
30 19.5 29.5 24.5
30
40 29.5 39.5 34.5
40
50 39.5 49.5 44.5
50
60 49.5 59.5 54.5
60
70 59.5 69.5 64.5
Histogram
%
%
35
30
25
20
15
10
5
0
35
30
25
20
15
10
5
0
20- 30- 40- 50- 6070
19.5- 29.5- 39.5- 49.5- 59.569.5
Frequency Polygon
%
40
30
20
10
0
24,5
34,5
44,5
54,5
64,5
Tabular Presentation
of Quantitative Data
or
Variable Total Mean SD
Age
(years)
47
95% CI
42.1 13.5 38.2-46.0
Scatter Diagram
Weight in kgm
100
80
60
40
20
0
0
10
20
30
Age in years
40
50
AGE in years
Box-whisker plot
80
70
60
50
40
30
20
10
Male
Female
20
N = 27
SEX
Conclusion
The variable is the basic unit required to
perform a research. The researcher has to
select the list of variables relevant to the
study objectives, specify every piece of
information and assign its role. The type
of variable should be set in order to
allow for proper data collection,
transformation and presentation.