Variables

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# Variables - PowerPoint PPT Presentation

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.

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## Variables

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Presentation Transcript

### 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

Independent

Effect

modifier

Confounding

Dependent

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

How much?

- Dichotomous

- Multichotomous

- Score

- Categorical

Who, How, where, when, What,…etc.?

- Numerical

discrete

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

Composite variable

Quantitative

Quantitative

Qualitative

Qualitative

Data Presentation

Tabular

Diagrammatic

Data Presentation

Variable

Table

Chart

Frequency

Pie

Nominal

-

-

Percentage

Column or Bar

-

-

Frequency

Pie

Ordinal

-

-

Percentage

Column or Bar

-

-

Cumulative

Linear

-

-

Ogive

frequency

-

Cumulative

-

percentage

Frequency

Histogram

Interval

-

-

Percentage

Frequency

-

-

Cumulative

-

polygon

Ogive

frequency

-

Cumulative

-

percentage

Mean, SD

Scatter

Continuous

-

-

Mean,

Box plot

-

-

95

%CI

Column Chart

All categories

Single Category

%

Bar Chart

All categories

Single Category

%

Linear Chart

Ogive

(Cumulative Percentage)

Percentage

Stages of Breast Cancer

Tabular Presentation of Quantitative Data

or

Variable

Total

Mean

SD

95

% CI

Age

47

42

.

1

.

38

.

2

-

46

.

0

13 5

(years)

Box-whisker plot

80

70

60

AGE in years

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.