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VariablesSherine 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
“A variable is any quantity that varies. Any attribute, phenomenon or event that can have different values”
Definition Of Variable
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
Interdependent
Correlation
Interdependent
Role Of Variable
Independent Dependent
Independent
DependentConfounding
Independent
Dependent
Effect modifier
Association
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 VariableOrdered qualitative categories
Score birth order
Categorical social class
Numerical discrete
parity
Continuous Variable
0 321-2 -1-3
0 1 2 3
Numerical Discrete
Continuous & Numerical Discrete Variables
Types of Variables- Quantitative
- Dichotomous- Multichotomous- Score- Categorical
- Numerical discrete
How much?
How many?
Who, How, where, when, What,…etc.?
Age in years:
Height in cm:
Gender:1) male, 2) female
Data Collection Tool
Social class:1) low, 2) middle, 3) high
.
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 ReductionContinuous: 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
Quantitative
Qualitative
Single variables
Composite variable
Quantitative
Qualitative
Data Presentation
Tabular Diagrammatic
Variable Table ChartNominal - Frequency
- Percentage - Pie - Column or Bar
Ordinal - Frequency - Percentage - Cumulative
frequency - Cumulative
percentage
- Pie - Column or Bar - Linear - Ogive
Interval - Frequency - Percentage - Cumulative
frequency - Cumulative
percentage
- Histogram - Frequencypolygon
- Ogive
Continuous - Mean, SD - Mean,95 %CI
- Scatter - Box plot
Data Presentation
Frequency TableFamilyPlanning
Freq (no.)
%
None 98 49.0Pills 65 32.5IUDs 22 11.0Others 15 7.5Total 200 100.0
Pie ChartOthers7.5%
None49.0%
IUDS11.0%
Pills32.5%
Column Chart
0%20%40%60%80%
100%
City A City B
None PillsIUDs Others
32,5
20,5
0
10
20
30
40
City A City B
Pill Users
Single CategoryAll categories%
Bar Chart
0%20%40%60%80%100%
City A
City B
None PillsIUDs Others
Single CategoryAll categories
32,5
20,5
0 10 20 30 40
Pill Users
City A
City B
%
Frequency and Cumulative Frequency Table
Breastcancer
Freq(no.)
% Cum.Freq
Cum%
Stage I 64 32.0 64 32.0
Stage II 58 29.0 122 61.0
Stage III 43 21.5 165 82.5
Stage IV 35 17.5 200 100.0
Total 200 100.0 200 100.0
Linear Chart
0
10
20
30
40
I II III IV
020406080
100
I II III IV
Ogive(Cumulative Percentage)
Percentage
Stages of Breast Cancer
Frequency and Cumulative Frequency Table for Variable of Interval
Freq(no.)
% Cum.Freq
Cum%
20-29 9 19.1 9 19.1
30-39 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 IntervalHistogram Polygon
Class Boundaries(1)
Boundaries(2)
Midpoint
Lower Upper Lower Upper
20-29 20 30 19.5 29.5 24.530-39 30 40 29.5 39.5 34.540-49 40 50 39.5 49.5 44.550-59 50 60 49.5 59.5 54.560-69 60 70 59.5 69.5 64.5
05
101520253035
19.5- 29.5- 39.5- 49.5- 59.5-69.5
Histogram
05
101520253035
20- 30- 40- 50- 60-70
% %
Frequency Polygon
010203040
24,5 34,5 44,5 54,5 64,5
%
Tabular Presentation of Quantitative Data
Variable Total Mean SD 95% CI
Age(years)
47 42.1 13 5. 38.2 -46.0
or
Scatter Diagram
0
20
40
60
80
100
0 10 20 30 40 50
Age in years
Wei
ght
in k
gm
Box-whisker plot
2027N =
SEX
FemaleMale
AG
E in
yea
rs8070605040302010
ConclusionThe 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.