Introduction to biostatistics

INTRODUCTION TO
BIOSTATISTICS
Mr. Shivam Dixit
Tutor cum Statistician
Department of Community Medicine

STATISTICS
Definition:- Statistics is a science and art which
deals with collection, classification, tabulation,
presentation, analysis and drawing conclusions
from numerical data.
Statistic:- Weight of one person.
Statistics:- Weight of hundred persons.

BIOSTATISTICS
Definition:- When statistics is applied in biology
(including human biology, medicine and public
health.it is known as biostatistics.
It is generally used to refer recorded data such as
number of patient attending a hospital, no. of road
accidents, etc.
Francis Galton (1822-1911) has been called the
father of Biostatistics.

Cont..
Medical Statistics:-
Medical Statistics deals with application of
statistical methods to the study of disease,
efficacy of vaccine etc.
Health Statistics:-
Health Statistics deals with application of
statistical methods to varied information of
public health importance.

Cont..
Vital Statistics:-
Vital statistics is the ongoing collection by
government agencies of data relating to vital
event such as births, deaths, marriage, divorces,
which are deemed reportable by local health
authorities.

IMPORTANCE OF STATISTICS
• Essential for people into research management
or graduate study in a specialized area.
• Persons active in research will find that a basic
statistics is useful in conducting clinical studies
and field surveys.
• Also effective presentation of their finding in
report in journals, and at professional meeting.

Data and its collection
A collective recording of the observations,
either numerically or otherwise is called as
“Data”.

Types of data
Two types of data:
1. Primary Data
2. Secondary Data

Primary Data
It is the data collected by a particular person or
organization for his or her own use from the
primary sources.
Method of Collecting Primary Data
 Direct personal observation
 Indirect oral investigation
 Investigation through schedules

Secondary Data
It is the data collected by some other person for
his on her own use but the investigator can also
it.
Sources of Secondary Data
Published official report
Journal and Newspaper
Local Government publication
 University and Research Institute publication.

Distinction between Primary and
Secondary Data
Primary data Secondary data
1.Primary data are Original, Collected First
time.
1.Secondry data are not Original, i.e. they
are already in existence and are used by
the investigator.
2.Primary data are like the Raw material. Secondary data are in the form of finished
product. They have passed through
statistical methods.
3.Primary data are according to the object
of investigation and are used without
correction.
3.Secondary data are corrected for some
other purpose and are corrected before
use.
4.The collection of Primary data require
large sum energy and time.
4.Secondary data are easily available from
secondary sources (Published or
Unpublished).

Variables
A variables is an attributes that describes a
person, place, or thing.
Qualitative vs Quantitative Variables:-
Variables can be classified as Qualitative
(Categorical) or Quantitative (Numeric).

Qualitative variables
Variables that yield observations on which
individuals can be categorized according to some
characteristics or quality are referred to as
qualitative variables.
Or
Qualitative variables a take on values that are
names or labels.
Example:- Sex(Male/Female),
Occupation(Unemployed/Employed), Marital
status(Married/Single), Education
Level(High/Medium/Low).

Quantitative variables
Variables that yield observations that can be
measured are considered to be quantitative
variables.
Or
Quantitative variables are numeric. They represent
a measurable quantity.
Example:- Age, Income, Height, Body temperature,
Weight.
Quantitative data are of two types:
1. Discrete Data
2. Continuous Data

Quantitative variables
Discrete Data
The no. of children in a family, blood sugar, blood
pressure are termed as discrete data, they must
always be whole no.
Continuous Data
In which the measurement can be made to a
precise value(fixed value) example:- temperature,
height, weight (17℃, 162.2 cm, 57.3kg).

Cont..
The following table illustrates the same:-
Quantitative variables Qualitative variables
Height (cm/feet) Short/Medium/Tall
Weight(kg/pound) Underweight/Normal
weight/Overweight
Blood sugar(mg%) Non-diabetic/Diabetic
Blood pressure(mm) Normal blood
pressure/Hypertension
Haemoglobin(mg%) Non-anaemic / Anaemic

Univariate & Biavariate Data
Statistical data are often classified according to the
no. of variables being studied.
Univariate Data
When we conduct a study that looks at only one
variables, we say that we are working with
Univariate data.
For Example:- we conduct a survey to estimate the
average weight of MBBS 2nd Year students in ESIC
medical college. Since we are only working with one
variable (weight), we would be working with
Univariate data.

Univariate & Bivariate Data
Biavariate Data
When we conduct a study that examines the
relationship between two variables, we are
working with Bivariate Data.
For Example:- we conduct a study to see if there
were a relationship between the height and
weight of MBBS 2nd year students. Since we are
working with two variables (Height and weight)
we would be working with bivariate data.

Application of Biostatistics
1. In Physiology & Anatomy
 Define limits of normality in variables (Pulse
rate, BP)
 Find difference between means (Mean height
of Gujarat boys < Mean height of boys in
Punjab)
 Find Correlation between height and weight-
whether weight increase or decrease
proportionately with height.

Application of Biostatistics
2. In Pharmacology
 Find action of a drug
 Compare two drugs
3. In Medicine
 Compare two treatment modalities
4. In Community Medicine and Public Health
 Test usefulness of vaccines (attack rates)
 Role of causative factors in disease

Applications and uses of Biostatistics as
figures
 Leading causes of death
 Important causes of sickness
 Rise and Fall of particular disease
 Age and sex composition of population
 Levels or standards of health reached

Sources of Data
The main sources of collection of medical
statistics are experiment, survey, records.
Experiment
Experiment are performed in various
departments like physiology, biochemistry etc.
The results are employed in the preparation of
dissertation etc… for publication.

Sources of Data
Surveys
Surveys are carried out by health workers in the
field to know the magnitude of the problem for
the implementation of control measures.
Records
These are the registers or books maintained
over a long period for vital statistics like birth
deaths marriage etc.

Other Sources of Health Information
1.Census
2.Registration of vital events
(a)The Central Birth and Death Registration
Act,1969
(b)Lay Reporting(Village Chokidar, house any
person)
3.Sample Registration System(SRS)
4.Notification of Diseases
5.Hospital Records

Sources of Health Information
6. Disease Registers
7.Record Linkage
8.Epidemilogical surveillance
9.Other health service records
10.Environment health data
11.Health manpower statistics
12Population surveys

Census
The census is an important source of health
information. It is taken in most countries of the
world at regular intervals, usually of 10 years.
 A census is defined by the United Nations as “
the total process of collecting compiling and
publishing demographic, economic and social
data pertaining at a specified time or times, to
all persons in a country.”

Census
The first regular census in India was taken in
1881, and other took place at 10-years
intervals.
The last census was held in March 2011.
The legal basis of the census is provided by
the census Act of 1948.
The Supreme officer whose directs, guides
and operates the census in the Census
Commissioner for India.

Sample Registration System(SRS)
A Sample Registration System (SRS) was initiated
in the mid 1960s to provide reliable estimates of
birth and death rates at the National and State
level. The SRS is a dual-record system, consisting
of continuous enumeration of births and deaths
by an enumerator and an independent survey
every 6 months by an investigator and
supervisor.

Common statistical terms
1. Variable: A characteristic that takes on different
values in different persons/place/thing
 Weight, Height etc….
2. Observation: An event and its measurement
 BP(event)-120 mm Hg (measurement)
3. Data: A set of values recorded or one or more
observational units
4. Population: Entire group of people or study event

Common statistical terms
5. Sample: Part of a population
6. Sample unit: Each member of a population
7.Parameter: Summary value calculated from a
sample and applied to the population

Symbols commonly used in statistics
= : Equal to
> : Greater than
< : Less than
Z : The no. of standard deviation from
the mean
% : Percent
𝜋 : Pearson’s correlation coefficient

Cont..
𝜌 : Spearman’s correlation coefficient
O : Observed no.
E : Expected no.
d.f. : Degree of freedom
K : No. of groups or classes
P : Probability

Problem
Which of the following statement are true?
1.All variable can be classified as quantitative or
categorical variables.
2.Categorical variable can be continuous
variables.
3.Quantitative variables can be discrete
variables.
(a) Only 1. (b)only 2. (c)only 3. (d) 1 and 2.
(e)1 and 3.

Introduction to biostatistics

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