This document is a slide presentation about data and its types given by Dr. Athar Khan. The presentation defines different types of data including nominal, ordinal, discrete, and continuous data. It provides examples of each type of data and discusses how quantitative data can be transformed into qualitative data. The objectives are to classify data, describe how different types of data are measured, and discuss techniques for data collection.

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‫الرحيم‬ ‫الرحمن‬ ‫اهلل‬ ‫بسم‬
DR ATHAR KHAN - LCMD

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DATA & ITS TYPES
Dr. Athar Khan
MBBS, MCPS, DPH, MBA, DCPS-HPE, DCPS-HCSM,
PGD-Statistics, PhD Scholar
Associate Professor
Department of Community Medicine
Liaquat College of Medicine & Dentistry
DR ATHAR KHAN - LCMD

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LEARNING OBJECTIVES
1. Classify data with examples
2. Describe the process of measurement of various
types of data
3. Discuss techniques and procedure to deal with
data collection
DR ATHAR KHAN - LCMD

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• Values of observations that have been collected. OR
• Data are the raw materials of statistics. OR
• Data consist of discrete observations of attributes or
events that carry little meaning when considered alone.
OR
• Data is raw facts and figures
unprocessed(meaningless)
DATA
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Definition
• Data observed or collected directly from first-hand
experience is called Primary data.
• Published data and the data collected in the past or
other parties is called Secondary data.
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Sources of
data
Records Surveys Experiments
Comprehensive Sample
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Population
 The complete collection of all elements (scores,
people, measurements, and so on) to be studied.
The collection is complete in the sense that it
includes all subjects to be studied.
• A population is a set of persons (objects) having a
common observable characteristics.
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 Census
• The collection of data from every member of the
population.
 Sample
• A sub-collection of elements drawn from a population.
• A sample is a subset of a population.
DefinitionsDefinition
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POPULATION
SAMPLE
Sample: a subset of a population
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 A numerical measurement describing some characteristic
of a population
POPULATION
PARAMETER
PARAMETER
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Definitions
A numerical measurement describing some characteristic
of a sample.
SAMPLE
STATISTICS
STATISTICS
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16. Slide 16VARIABLE
• Obtaining information on specific characteristics e.g.
age, height, weight are referred to as variable.
• A variable is any measured characteristic or attribute
that differs for different subjects. For example, if the
weight of 30 subjects were measured, then weight
would be a variable.
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DATA
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Continuous
Types of Data/Variable
Quantitative Data Qualitative Data
Discrète
Nominal
Ordinal
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Qualitative (Categorical) data
•Observations by which individuals can be
categorized according to some characteristic or
quality.
•Example: gender (male/female) of LCMD students.
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NOMINAL
Characterized by data that consist of names,
identifiers, labels, or categories only. The data
cannot be arranged in an ordering scheme (such as
low to high)
Example: survey responses (yes, no)
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Involves data that may be arranged in some order,
ascending or descending
Example: Course grades A, B, C, D, or F
ORDINAL
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Quantitative (Numerical) data
•Numbers representing counts or measurements.
•Example: weights of LCMD students
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They must be integers i.e. whole numbers.
0, 1, 2, 3, . . .
Example: The number of students in 4th Year MBBS
Quantitative DataDISCRETE
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Values in fractions or decimals.
Example: weight of LCMD students
CONTINUOUS
2 3
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 May be Interval or Ratio Type
• Interval: there is no absolute zero point e.g. temperature
• RatiO: there is a true zero point (zero means zero)
CONTINUOUS
0 Kg
320
F or 273K
0 0
C
0 lb
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DEPENDENT- HEIGHT
INDEPENDENT-AGE
WIEGHT
PHYSICAL ACTIVITY
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44. Slide 44Transformation of Data
• Quantitative data can be transformed into qualitative
data
• Example:
• Age in years - Quantitative data
• < 20 years
• 20 – 50 years Qualitative data
• > 50 years
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Summary
 Nominal - categories only
 Ordinal - categories with some order
 Discrete – whole numbers
 Continuous - decimals
DISCRETE
CONTINUOUS
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THANK YOU
DR ATHAR KHAN - LCMD