Assistant Professor Department of Community Medicine Nishtar Medical college Multan

3. INTRODUCTION
DR Allah Yar Malik
M. Phil , Ph.D. Scholar
ASSISTANT PROFESSOR
Department of
Community Medicine
M.lar

4. DATA
DATA
These are simple
observations (variable) that
carry little meaning when
considered alone.
For example 100 births,
20 deaths.
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5. INFORMATION: Data is transformed
into information by adding, reducing,
summarizing and adjusting the data so
that comparison over time and place
becomes possible, e.g.,
Birth rate = 40 / 1,000 pop. of a
particular city per year.
Death rate = 10 / 1,000 pop. of a
particular city per year.
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6. INTELLIGENCE
It is transformation of
information through integration
& processing with experience
& perception. Intelligence
helps in future policy making,
planning & administration.
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7. i) Growth rate 2.4 % per year(Information). It
will lead to population explosion
(Intelligence).
ii) High average global temperature
(Information). It will lead to melting of ice
at poles & flooding at low lying areas
(Intelligence)
(Park)
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8. Sources of
data
Records Surveys Experiments

9. Quantitative
continuous
Types of variables
Quantitative variables Qualitative variable
Quantitative
descrete
Qualitative
nominal
Qualitative
ordinal

10. Quantitative Data
Continuous Variable
- Height
- Weight
- Blood Pressure ....
Discrete Variable ^
- # of kids
- # of marriages
- # of patients you Examined
Measurement
Scale >
No
Measurement
Scale
1
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11. 2. QUANTITATIVE DATA
It can be continuous in which there is
no gap e.g., weight, height,
temperature & blood pressure etc.
(There is decimal in the values). Or it
can be discrete e.g., number of
patients, marks obtained by
students,
(Ilyas. BK Mahajan)
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12. Quantitative or Numerical Data
Height of Participants in
cm
- 140, 160, 170, 180..

13. Types of DATA
What is your age?
S. # Age (years)
1 25
2 27
3 34
4 28
5 33
6 56
7 29
Precisely
1 25.475
2 27.687
0.00 I-------------------1 100.00
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14. Quantitative Discrete
How many kids do you have?
0, 1, 2, 2.7©
2.7 ? ^ Not possible
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15. Note: Usually descriptive analysis of this
type of data: (statistical calculation used
are): mean, range , standard deviation
and correlation. ‘t’ test is applied as test
of significance. This type of data is
presented by table and graphs like
histograms, frequency polygons, line
graphs and scatter graphs.
(BK Mahajan)
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16. Qualitative Data
What's the color of your car?
- Black
- Green I
- Red
- Blue
How do you feel today?
- Bad ©
- Not so good
- Ok
-Good
-Very Good
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17. Qualitative Data
Nominal - names, no order
Ordinal - order, order, has to be
an order
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18. ii) ORDINAL DATA: Categories can be
classified one above the other. e.g.
Height: tall, medium, short.
(c.f. height in meters which is continuous
data)
Economic status: rich, middle, poor.
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19. Note: Descriptive analysis of qualitative data
or discrete data like number of patients
is:
Frequency and percentage & usually test of
significance applied is
“Chi square test”, or standard error of
proportion.
This type of data is presented by table and
diagrams like bar charts, pie charts,
pictograms and maps. 19

20. Quantitative
continuous
Types of variables
Quantitative variables Qualitative variable
Quantitative
descrete
Qualitative
nominal
Qualitative
ordinal

21. Classify the following data ∕ variable
Height: tall, medium, short.
Blood sugar
Addict
Low Birth Weight
Weight in KG
Number of kids.
Marks obtained
Diseased
Height in feet 21

22. Height: tall, medium, short. Qualit. ordinal
Blood sugar: Quantitative, continuous data.
Addicts: Qualitative data.
Low Birth weight: Qualitative data.
Weight in KG: Quantitative, continuous data.
No. of kids: Quantitative Discrete. Discrete
Marks obtained: Quantitative data. Discrete
Diseased: Qualitative data.
Height in Feet: Quantitative, continuous
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23. TRANSFORMATION OF DATA
Continuous Data can be transformed to
Categorical Data e.g.
Weight of new born:
Low → < 2.5 Kg
Normal → 2.5 - 4 Kg
Over weight → > 4 Kg
(Chi square Test can now be
applied) (Ref. : Iliyas 7th Edition)
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24. VARIABLE:
The observations we record in a
study/research are known as variable. So
all types of data can be labeled as
variable.
Types of variable
i) Independent Variables:
Factors that influence the other
e.g. type of food, sanitation & smoking
etc.
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25. ii) Dependent variable: That is influenced by
independent variable e.g.
malnutrition, diarrhea Cancer etc.
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26. Evidence-based Chiropractic 26
Statistical terms (cont.)
• Independent variables
– Precede dependent variables in time
– Are often manipulated by the researcher
– The treatment or intervention that is used in a
study
• Dependent variables
– What is measured as an outcome in a study
– Values depend on the independent variable

27. MCQ 2010/S
The first variable is contingent upon the the
second variable; it is called:
a) dependent variable b) independent v
c) predictive d) definite v
e) none
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28. a
(contingent means dependent)
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29. Question
Smoking leads to cancer. But the incidence
of cancer is higher in middle age as
compared to young age.
Classify age, smoking and cancer as
independent, dependent and confounding
variable.
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30. KEY
In this example smoking is independent
variable; cancer is dependent variable &
age is confounding factor.
Note: The term variable is some time used
for data.
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31. Q. Weight (in kilogram) of the new born is
classified as continuous data.
How you can convert this to
qualitative(categorical) data?
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32. KEY
Categories Weight
Low weight < 2.5 Kg
Normal 2.5 - 4 Kg
Over weight > 4 Kg
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34. THANK YOU