1. Public Health Methodologies
Biostatistics
drrkb@hotmail.com

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4. Data
• Data is a collection of facts, such as values or
measurements.
OR
• Data is information that has been translated into
a form that is more convenient to move or
process.
OR
• Data are any facts, numbers, or text that can be
processed by a computer.
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5. Statistics
Statistics is the study of the collection,
summarizing, organization, analysis, and
interpretation of data.
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6. Vital statistics
Vital statistics is collecting, summarizing,
organizing, analysis, presentation, and
interpretation of data related to vital events
of life as births, deaths,
marriages, divorces,
health & diseases.
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7. Biostatistics
Biostatistics is the application of statistical
techniques to scientific research in health-
related fields, including medicine, biology,
and public health.
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8. Descriptive Statistics
The term descriptive statistics refers to
statistics that are used to describe. When
using descriptive statistics, every member of a
group or population is measured. A good
example of descriptive statistics is the Census,
in which all members of a population are
counted.
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9. Inferential or Analytical Statistics
Inferential statistics are used to draw
conclusions and make predictions based on the
analysis of numeric data.
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10. Types of Data
• Raw or Primary data: when data collected
having lot of unnecessary, irrelevant & un
wanted information
• Treated or Secondary data: when we treat &
remove this unnecessary, irrelevant & un
wanted information
• Cooked data: when data collected not
genuinely and is false and fictitious
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11. Types of Data – cont.
• Ungrouped data: when data presented or observed individually. For
example if we observed no. of children in 6 families
2, 4, 6, 4, 6, 4
• Grouped data: when we grouped the identical data by frequency.
For example above data of children in 6 families can be grouped as:
No. of children Families
2 1
4 3
6 2
or alternatively we can make classes:
No. of children Frequency
2-4 4
5-7 2
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12. Variable
A variable is something that can be
changed, such as a characteristic or value. For
example age, height, weight, blood pressure
etc
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13. Types of Variable
Independent variable: is typically the
variable representing the value being
manipulated or changed. For example
smoking
Dependent variable: is the observed result of
the independent variable being manipulated.
For example ca of lung
Confounding variable: is associated with both
exposure and disease. For example age is
factor for many events
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