2. Dr. Subrata Kumer Sen
MBBS, MPH, BCS (Health)
Lecturer, Community Medicine
M Abdur Rahim Medical College
Dinajpur.
3. Statistics: The science of collecting, summarizing, and
analyzing data.
Biostatistics: The science of collecting, summarizing,
and analyzing biological data.
Medical Statistics: The science of collecting,
summarizing, and analyzing medical data.
Vital Statistics: Statistics that deals with vital events.
Vital events are births, marriages, divorces, separations,
and deaths.
4. Sources of data for vital events/ statistics:
• National level- Census, BBS
• City Corporation/ Municipalities for births &
deaths
• Kaji Office for marriages, divorces, separations
• Notification of infectious diseases for deaths
• Hospital records for births & deaths
• Disease registers for deaths etc.
5. Uses of Biostatistics:
• Collection of information in the best possible scientific way.
• Simplification of huge, complex sets of data.
• Helps in the formulation of hypothesis and amplification of
ideas.
• Identification of association between two or more variables
by testing hypothesis.
• Helps in interpretation and drawing conclusion by analyzing
data
• By summarizing and presenting, helps policy makers to make
decisions based on scientific evidence.
6. Data: Data is a set of values collected during any type of scientific
investigation.
Data Classification:
Based on Source of Data:
I. Primary: Data directly collected at the field level during a study
II.Secondary: collected from another study, census data, hospital records
III.Tertiary: from textbooks.
Based on Nature of Data:
• Qualitative/ Categorical/ Nominal: Age, Sex, economical status
• Quantitative/ Numerical:
a. Continuous: Cont. spectrum/range can be fractioned (e.g. height, weight,
temperature)
b. Discrete: No continuity, Complete #, no fraction (e.g. Parity, patient
number in hospital)
7. Variable: Any characteristic which differs for one individual or
object to another.
Types:
A. According to Relationship:
1. Independent Variable
2. Intervening Variable
3. Dependent Variable
4. Confounding variable
B. According to Nature/ Characteristic:
1. Qualitative
2. Quantitative: Continuous & Discrete.
8. Measurement of Scale:
A.Qualitative-
1. Nominal (Sex, Religion)
2. Ordinal (Educational level, Economical Status)
B. Quantitative-
1. Interval (Temperature)
2. Ratio (age, height, weight)
9. Methods of Data Collection:
*Surveying Study population
*Interviewing: Face to Face, Telephone, Internet etc
*Observation: Participant, Non-participant
*Written Questionnaire
*Electronic Data Reporting
*Focus Group Discussion
*Document Review
11. Data Presentation:
A.Tabulation/ Tabular Presentation:
1. Simple Table
2. Frequency Distribution Table
B. Graphical Presentation:
1. Qualitative:
a. Bar diagram - Simple Bar Diagram, Multiple Bar diagram,
Component Bar Diagram
b. Pie/ sector chart
c. Pictogram
d. Map/ spot diagram
27. Measures of Central Tendency:
Mean: Mean is the summation of all values of a
series divided by number of values.
Median: Median is the middle most value of a
data set while arranged in ascending or
descending order.
Mode: Mode is the most frequent and repeated
values observed in a data set.
28.
29.
30. Measures of Dispersion:
Range: Simply the difference between the largest and
smallest values in a set of data.
Mean Deviation: The mean deviation is an average of
absolute deviations of individual observations from the
central value of a series.
Standard Deviation: Standard deviation is the positive
square root of the mean-square deviations of the
observations from their arithmetic mean.
31. Population: A population is entire group of subjects or total
number of items about which information is desired.
Sample: Sample is a part of population describing the
characteristics of that population. The sample is drawn should
be representative of entire population.
Sampling: Sampling is the process of selection the sample
from a defined study population.
Sampling frame: When all the members or individuals of
population are listed by numbering then it is called sampling
frame.
32. Sampling methods/Techniques:
a) Random/ Probability/ Non-purposive/ Unbiased
sampling:
i) Simple random sampling (e.g. Lottery)
ii) Systematic random sampling
iii) Stratified random sampling
iv) Multistage sampling
v) Multiphase sampling
vi) Cluster Sampling
33. b) Non- Probability sampling:
i) Convenience or Judgment sampling
ii) Quota sampling
iii) Snowball sampling
