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.