INTRODUCTION

DR Allah Yar Malik M. Phil , Ph.D. Scholar ASSISTANT PROFESSOR

Department of Community Medicine

M.larin

Community Medicine

DATADATA

These are simple observations (variable) that carry little meaning when considered alone.

For example 100 births, 20 deaths.

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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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INTELLIGENCEIt is transformation of information through integration & processing with experience & perception. Intelligence helps in future policy making, planning & administration.

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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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Sources of data

Records Surveys Experiments

Quantitative continuous

Types of variables

Quantitative variables Qualitative variables

Quantitative descrete

Qualitative nominal

Qualitative ordinal

Quantitative Data

Continuous Variable- Height- Weight- Blood Pressure ....

Discrete Variable ^- # of kids- # of marriages- # of patients you Examined

Measurement

Scale >

No

Measurement Scale

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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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Quantitative or Numerical Data

Height of Participants in cm- 140, 160, 170, 180..

Types of DATAWhat is your

age?S. # Age (years)

1 252 273 344 285 336 567 29

Precisely1 25.4752 27.687

0.00 I-------------------1 100.00

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Quantitative DiscreteHow many kids do you

have?0, 1, 2, 2.7©2.7 ? ^ Not possible

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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)15

Qualitative DataWhat'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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Qualitative DataNominal - names, no orderOrdinal - order, order, has to be an order

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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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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.

(Ilyas. BK Mahajan)

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Quantitative continuous

Types of variables

Quantitative variables Qualitative variables

Quantitative descrete

Qualitative nominal

Qualitative ordinal

Classify the following data ∕ variable

Height: tall, medium, short. Blood sugarAddictLow Birth WeightWeight in KG Number of kids.Marks obtainedDiseasedHeight in feet

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Height: tall, medium, short. Qualit. ordinalBlood sugar: Quantitative, continuous data.Addicts: Qualitative data.Low Birth weight: Qualitative data.Weight in KG: Quantitative, continuous data.No. of kids: Quantitative Discrete. DiscreteMarks obtained: Quantitative data. DiscreteDiseased: Qualitative data.Height in Feet: Quantitative, continuous 22

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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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 variablei) Independent Variables:

Factors that influence the other e.g. type of food, sanitation & smoking

etc.

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ii) Dependent variable: That is influenced by independent variable e.g.

malnutrition, diarrhea Cancer etc.

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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

MCQ 2010/S

The first variable is contingent upon the the second variable; it is called:

a) dependent variable b) independent vc) predictive d) definite ve) none

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a(contingent means dependent)

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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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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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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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KEY

Categories Weight Low weight < 2.5 Kg

Normal 2.5 - 4 KgOver weight > 4 Kg

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THANK YOU