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BIOSTATISTICS
CONTENTS
 Introduction
 Definition
 Branches of Biostatistics
 Uses/ application of biostatistics
 Some important terms
 Sampling
 Collection of data
 Presentation of data
- disribution
 Summarization of data
- measures of central tendency
- dispersion
- probability
 Summary
 References
09/06/2025 2
introduction
 Statistics has been derived from the Latin
word status.
 Statistics today refers to either quantitative
information or to a method of dealing with
quantitative or qualitative information.
 Statistics may be defined as the discipline
concerned with the treatment of numerical
data derived from group of individuals.
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 BIOSTATISTICS
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Is a method of collection, organizing,
analyzing, tabulating and interpretation
of data related to living organisms and
human beings.
Bios ( life)
Metron
(measured)
Biometry
(measurement
of life)
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“When you can measure what you are speaking
about and express it in numbers, you know
something about it but when you cannot
measure, when you cannot express it in
numbers, your knowledge is of meagre and
unsatisfactory kind.”
- LORD KELVIN
Branches of Biostatistics
• Descriptive Biostatistics
 Methods of producing quantitative summaries
of information in biological sciences.
Tabulation and Graphical presentation
Branches of Biostatistics…
Inferential Biostatistics
Methods of making generalizations about a
larger group based on information about a sample
of that group in biological sciences.
Primarily performed in two ways:
• Estimation
• Testing of hypothesis
Uses/ APPLICATIONS of
biostatistics
 In Physiology and Anatomy:
1. To define what is normal or healthy for a
population and to find limits of normality in
variables.
2. To find the difference between means and
proportions of normal at two places or in
different periods.
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 In Pharmacology:
1. To find the action of drug.
2. To compare the action of two different drugs
or two successive dosages of the same drug.
3. To find the relative potency of a new drug
with respect to a standard drug.
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 In Medicine:
1. To compare the efficacy of a particular drug,
operation or line of treatment.
2. To find an association between two
attributes.
3. To identify signs and symptoms of a disease
or syndrome.
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• Most people have heard the statistic that Heart
disease is the leading cause of death in America today*.
• But how do we know this fact to be true?
• Where did that information come from?
* [source: Center for Disease Control, USA]
In medicine
• Back in 1948, when a lot wasn't known about the factors
leading to heart disease and stroke, a health research
study -- known as the Framingham Heart Study -- was
done on 5,209 people living in the town of Framingham,
Mass.
• These participants hadn't developed any known
symptoms of cardiovascular disease and hadn't had a
stroke or heart attack.
In medicine
• They agreed to be followed over a period of time to
help researchers learn what factors lead to both
conditions.
• The study was landmark in several ways. It showed
that there was no one cause for getting a heart attack,
and combining information about several risk factors
could estimate the risk of someone getting the disease.
In medicine
• Thanks to the Framingham Study, (which is still going
on today), we now know the major risk factors that
lead to cardiovascular disease.
• To reach these conclusions, researchers simply
followed the numbers -- the Biostatistics numbers to
be exact.
In medicine
Clinical medicine
• Documentation of medical history of diseases.
• Planning and conduct of clinical studies.
• Evaluating the merits of different procedures.
• In providing methods for definition of ‘normal’ and
‘abnormal’.
Preventive medicine
• To provide the magnitude of any health problem in
the community.
• To find out the basic factors underlying the ill-health.
• To evaluate the health programs which was
introduced in the community(success/failure).
• To introduce and promote health legislation.
 In Community Medicine and Public health:
1. To test usefulness of sera and vaccines in the
field. –
% of attacks or death among vaccinated
subjects is compared with that among non
vaccinated.
2. In epidemiological studies – the role of
causative factors is statistically tested.
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USES OF STATISTICS IN DENTAL SCIENCE:
1. To find the statistical difference between means of
two groups. Ex: Mean plaque scores of two groups.
2. To assess the state of oral health in the community
and to determine the availability and utilization of
dental care facilities.
3. To indicate the basic factors underlying the state of
oral health by diagnosing the community and find
solutions to such problems.
Uses of statistics in dental science:
4. To determine success or failure of specific oral
health care programs or to evaluate the program
action.
5. To promote oral health legislation and in creating
administrative standards for oral health care delivery.
Some important terms
 VARIABLE:
A general term for any feature of the unit
which is observed or measured is a variable.
 It is a characteristic that takes on different
values in different persons, places or things.
It is denoted as X and notation for orderly
series as X1, X2,X3….Xn. The suffix n is
symbol for number in the series.
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Types of variables
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Variable
Quantitativ
e
Ordinal Discrete Continuous
Qualitative
Attribute
 CONSTANT:
These are quantities that do not vary.
Eg:π = 3.141
е = 2.718
They do not require statistical study.
In biostatistics, mean, standard deviation,
standard error, correlation coefficient and
proportion of a particular population are
considered as constant.
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 OBSERVATION:
An event and its measurements.
Eg: blood press – event
120mmHg – measurement
 OBSERVATIONAL UNIT:
The source that gives observations such as
object, person, etc.
In medical stats the term individuals or
subjects is used more often.
09/06/2025 23
 DATA:
A set of values recorded on one or more
observational units.
 PARAMETER:
It is a summary value or constant of a
variable that describes the population such
as mean, variance, correlation coefficient,
proportion etc.
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09/06/2025 25
Data
Nomina
l data
Ordinal
data
Interval
data
Ratio
data
Measurement
scales
Nomina
l scale
Ordinal
scale
Interval
scale
Ratio
scale
 STATISTIC:
It is a summary value that describes the
sample such as its mean, standard deviation,
standard error, correlation coefficient,
proportion etc.
This value is calculated from the sample and
is often applied to population but may or may
not be valid estimate of population.
Parameter and statistic are often used as
synonyms.
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 PARAMETRIC TEST:
It is one in which population constants as
described above are used such as mean,
variances, etc. and data tend to follow one
assumed or established distributions such as
normal, binomial, Poisson etc.
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 NON PARAMETRIC TEST:
Tests such as χ2 test in which no constant of a
population is used.
Data do not follow any specific distribution
and no assumptions are made in non
parametric tests.
Eg. To classify good, better and best you
allocate arbitrary numbers or marks to each
category.
population
 In statistics population means the totality of
the individual observations about which
inferences are to be made.
 Populations can be finite or infinite.
 Samples of varied size can be drawn carefully
with appropriate procedures from their
populations which are either finite or
infinite.
09/06/2025 29
sample
 It is a part of the population.
 It is a small collection of observations from
some larger aggregate about which we want
to have information.
 Samples drawn should be representative of
the population.
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Larger the sample, better is the degree of representation of the
sample selected.
sampling
 Samples can be drawn from the entire
population through various procedures.
 Sampling can be:
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Probability
sampling
Non probability
sampling
 Probability sampling
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Simple
random
sampling
Systematic
sampling
Stratified
random
sampling
Cluster
sampling
Multistage
sampling
Multiphase
sampling
 Non probability sampling:
09/06/2025 33
Heterogeneous
sampling
Homogenous
sampling
Structured
sampling
Haphazard
sampling
1. Simple random sampling
 UNRESTRICTED RANDOM SAMPLING
 Applicable when population is small,
homogenous and readily available.
 Used mainly in experimental medicine or
clinical trials to check the efficacy of a
particular drug.
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Principle : every unit of the population has an equal chance
of being selected.
 To ensure randomness of selection 2 methods
are available:
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Lottery method
Random number
procedure
2. Systematic sampling
 Simple procedure.
 Utilized when a complete list of population
from which sample is to be drawn is
available.
 Systematic procedure is followed to choose a
sample by taking every Kth
house or patient
where k refers to the sample interval which is
calculated by the following formula:
K = total population/sample size desired
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Merits of systematic
sampling
1. Procedure is simple and convenient for use.
2. Relatively time to be devoted and labor
needed are small.
3. If the population is sufficiently large and
homogenous and if the numbering of the
subjects is available, this method can
provide good results.
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An element of randomness is introduced into this kind of sampling by randomly
selecting from the first K units, the unit with which to start. – RANDOM
START.
Sample so chosen is sometimes called as “Every K’th systematic sample”
3.Stratified random sampling
 Followed when the population is not
homogenous.
 Population under study is first divided into
homogenous groups called strata and the
sample is drawn from each stratum at
random in proportion to its size.
 Gives more representative sample than
simple random sampling in a given large
population.
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Merits of stratified
random sampling
1. Gives greater accuracy.
2. Gives better representation to each strata
compared to simple random sampling.
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4. Cluster sampling
 Cluster is a group consisting of units such
as villages, wards, blocks, factories,
workshops etc.
 Simple random sampling or systematic
sampling procedure is utilized for
selection of clusters.
 After the selection of clusters randomly,
enumeration of individuals in the cluster
is carried out.
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 If the cluster consists of natural groupings
and if they are geographic regions it is
referred to as AREA SAMPLING.
MERITS:
1. Simple and time saving.
DEMERITS:
2. Costlier.
3. Provides figures with higher standard errors
than other procedures.
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5. Multistage sampling
 Refers to sampling procedures carried out in
several stages using random sampling
techniques.
 Employed in large scale, country wise or
region wise surveys.
 Stage wise sampling procedures are to be
utilized for selection of households or
subjects.
09/06/2025 42
6. Multiphase sampling
 Here part of information is collected from
whole sample and part from the sub sample.
 Numbers in 2nd
and 3rd
phase will become
successively smaller and smaller.
MERITS:
1. Less costly.
2. Less laborious.
3. More purposeful.
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Purposive sampling
 If a sample is not randomly selected it is
called purposive sampling.
 Here the chances of any element being
selected are either unknown or guaranteed to
be 0% or 100%.
 It provides better descriptive data.
 Are used in early stages of any branch of
knowledge as the focus is on what the
researchers will seek to explain.
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Types of purposive
sampling
09/06/2025 45
• Selected from things or people which are in some way
alike in a relevant detail.
• Quota sampling
Heterogenous
• Extreme – selecting a group of people with a quality
which lies at the top or bottom of the range of such
qualities found in general population.
• Rare – those which contain a quality or qualities found
only rarely.
Homogenou
s
• Strategic informant sampling – selecting
people whom you think can give you the
most information.for eg comm leaders etc.
• Snowball sampling
Structured
• Is merely one which is readily available.
Haphazard
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Demerits:
1. Serious discrepancies b/w sample &
population.
2. Investigator biases likely to occur.
3. Results cannot be generalized.
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Good Morning
BIOSTATISTICS
Collection of data
 Can be of two types:
1. Primary data
2. Secondary data
09/06/2025 50
Primary data
09/06/2025 51
Observation Interview
Questionnaires Schedules
1. observation
 Used in studies relating to behavioral
sciences.
 Merits:
1. Elimination of subjective bias.
2. Information obtained relates to what is
currently happening.
3. Independent of respondent’s willingness.
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 Demerits:
1. Expensive.
2. Information provided is limited.
3. Unforeseen factors may interfere.
4. Some people are rarely accessible to direct
observation.
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Types of observation
09/06/2025 54
Structured
Unstructured
Uncontrolle
d
Controlled
Participant
observation
Non
participant
observation
Disguised
observation
Merits of participant
type of observation
 Researcher is able to record the natural
behavior of the group.
 Researcher can gather information which
could not easily be obtained if he observes in
a disinterested manner.
 Researcher can even verify the truth of
statements.
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2.Interview method
09/06/2025 56
Personal
interview
Telephone
interview
Personal interview
 Can be of 2 types:
1. Direct personal investigation
2. Indirect oral investigation
09/06/2025 57
structured unstructured
09/06/2025 58
Focused
• Focus
attention on
the given
experience of
the
respondent
and its effects.
Clinical
• Concerned
with broad
underlying
feelings or
motivation or
with the
course of
individuals life
experience
Non Directive
• Simply
encourage the
respondent to
talk about the
given topic
with a bare
minimum
questioning.
merits
09/06/2025 59
More information and in greater depth
Interviewer can overcome resistance of
respondents.
Greater flexibility
Observation method can as well be applied to
recording verbal answers to various questions.
Personal information can as well be obtained
easily.
Samples can be more controlled more effectively.
Interviewer can control which persons will answer the questions.
Interviewer may catch the informant off guard and thus may secure the most
spontaneous reactions than would be the case if mailed questionnaire is used.
Language of interview can be adopted to the ability or educational level of the
person interviewed.
Interviewer can collect supplementary information about the respondent’s
personal characteristics and environment which is of great value in interpreting
results.
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demerits
09/06/2025 61
Very expensive Possibility of bias
Certain types of
respondents such as
important officials
may not be easily
approachable
More time
consuming specially
when the sample is
large and recalls
upon the
respondents are
necessary
Presence of
interviewer on the
spot may over
stimulate the
respondent .
Organisation
required for
selecting , training
and supervising staff
is more complex
with formidable
problems
Interviewing at times
may also introduce
systematic errors.
Effective interview
presupposes proper
rapport with
respondents that
would facilitate free
and frank responses
Pre- requisites and basic
tenets of interviewing
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1. Interviewers should be carefully selected, trained and briefed.
2. They should be honest, sincere, hardworking, impartial and must
possess the technical competence and necessary practical
experience.
3. Occasional field checks should be made to ensure that interviewers
are neither cheating nor deviating from instructions given to perform
their job efficiently.
4. The approach should be friendly, courteous, conversational and
unbiased.
5. Interviewer should not show disapproval or surprise of a respondents
answer but he must keep the direction of interview in his own hand,
discouraging irrelevant conversation and must make all possible
effort to keep respondent on the track.
Telephone interviews
 Merits:
1. More flexible in comparison to mailing
methods.
2. Is faster than other methods.
3. Cheaper than personal interviewing method.
4. Recall is easy, callbacks are simple and
economical.
5. Replies can be recorded without causing
embarrassment to the respondents.
6. Higher rate of response than mailing
method.
09/06/2025 63
7. Interviewer can explain requirements more
easily.
8. At times access can be gained to respondents
who otherwise cannot be contacted for one
reason or another.
9. No field staff is required.
10.Representative and wider distribution of
sample is possible.
09/06/2025 64
Demerits of telephone
interviews
1. Little time is given to respondents for
considered answers.
2. Surveys are restricted to respondents who
have telephone facilities.
3. Extensive geographical coverage may get
restricted by cost considerations.
09/06/2025 65
4. It is not suitable for intensive surveys where
comprehensive answers are required to
various questions.
5. Possibility of bias of the interviewer is
relatively more.
6. Questions have to be short and to the point.
09/06/2025 66
3. Collection of data
through questionnaires
 Used in big enquiries.
 Adopted by private individuals, research
workers, private and public organizations
and even by governments.
 A questionnaire consists of a set of questions
printed or typed in a definite order on a form
or set of forms.
 The questionnaire is mailed to the
respondents who are expected to read and
understand questions and answer them on
their own.
09/06/2025 67
Merits of questionnaire
survey
09/06/2025 68
1. Low cost even when business is large and widely spread geographically
2. Free from bias of the interviewer, answers are in respondents words.
3. Respondents have adequate time to give well thought out answers.
4. Respondents who are not easily approachable, can also be reached
conveniently.
5. Large samples can be made use of and thus the results can be made
more dependable.
Demerits of
questionnaire method
09/06/2025 69
1. Low rate of return of duly filled in questionnaires, bias due to no-
response is often indeterminate.
2. Can be used only when the respondents are educated and co-
operating.
3. The control over questionnaire may be lost once it is sent.
4. There is inbuilt inflexibility because of the difficulty of amending the
approach once questionnaires have been dispatched.
5. Possibility of ambiguous replies or omission of replies altogether to
certain questions.
6. Difficult to know whether willing respondents are truly representative.
7. Slowest of all methods.
Aspects of a questionnaire
 General form:
 Question sequence:
09/06/2025 70
structured
unstructured
Questions to be avoided:
1. Questions that put too great a strain on the memory or
intellect of the respondent.
2. Questions of a personal character.
3. Questions related to personal wealth etc.
Question sequence should always go from the general to the more
specific.
The answer given to a given question is a function not only of specific
question but of all previous questions as well.
 Question formulation and wording:
Should be simple.
Should be easily understood.
Should be concrete and should conform to
the respondent’s way of thinking.
09/06/2025 71
Multiple choice
or closed
questionnaire
Open ended
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Open ended:
What sports or other physical activities do you
undertake each week on a regular basis?
Closed ended:
For each of the following sports tick if you regularly spend more
than 30 mins each week in that activity?
a. Walking
b. Jogging
c. Cycling
d. Swimming
Open ended
questionnaire
Closed ended
questionnaire
Subject recall Reduced Enhanced
Accuracy of
response
Easier to express
complex situations
Difficult to
investigate
complex situations
Coverage May pick up
anticipated
situation
Will miss areas not
anticipated
Size of
questionnaire
May need fewer
lines of text
May need many
pages of text
Analysis More complex Simpler
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Essentials of a good
questionnaire
09/06/2025 74
• Should be short and simple.
• Questions should proceed in logical sequence moving from easy to more difficult
questions.
• Personal and intimate questions should be left to the end.
• Technical and vague expressions capable of different interpretations should be avoided in
a questionnaire.
• Questions may be dichotomous, multiple choice or open ended.
• There should be some control questions in the questionnaire which indicate reliability of
the respondent.
• There should be provision for indications of uncertainty.
• The physical appearance of the questionnaire affects the cooperation the researcher
receives from the recipients.
QUNITAMENSIONAL
QUESTIONNAIRE DESIGN
 First introduced by Gallow in 1947.
 Useful for studying attitudes and opinions.
09/06/2025 75
Open ended questionnaire are formulated to elicit
awareness of the issue in question and general
attitudes towards it.
A closed ended question follows to capture
information on specific attitudes to the subjects.
An open ended question is placed next to explore
justifications for their attitudes
This is followed by a closed ended question to tap the
intensity with which they hold attitudes.
09/06/2025 76
4. Collection of data
through schedules
 This method requires the selection of
enumerators for filling up schedules or
assisting respondents to fill up schedules.
 The enumerators should be trained to
perform their job well and the nature and
scope of investigation should be explained to
them thoroughly.
09/06/2025 77
 Enumerators should be intelligent and must
possess the capacity of cross examination in
order to find the truth.
 They should be honest, hard working, patient
and have perseverance.
09/06/2025 78
Difference between
questionnaires and schedule
09/06/2025 79
Schedule Questionnaire
Cost High Low
Response rate Higher Lower
Completion of
questionnaire
High Low
Complexity of
questions
Can be high Should be minimized
Interviewer bias May be present Not relevant
Interviewer variability May be present Not relevant
Total study duration Considerably fast Slow
Collection of secondary
data
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Published
data
Unpublished
data
 Published data:
09/06/2025 81
1. Various publications of central, state or local
govts.
2. Various publications of foreign govts or of
international bodies and their subsidiary
organizations.
3. Technical and trade journals.
4. Books, magazines and newspapers.
5. Reports and publications of various
associations
6. Reports prepared by research scholars,
universities.
7. Public records and statistics, historical
documents and other sources of information.
 Unpublished data:
09/06/2025 82
1. Diaries, letters.
2. Unpublished biographies and autobiographies.
3. May be available with scholars, research
workers, trade associations, labor bureaus and
other public or private individuals or
organizations.
 Secondary data should possess following
characteristics:
Reliability of data
Suitability of data
Adequacy of data
09/06/2025 83
84
PRESENTATION OF DATA
Objectives
• make the data simple
• concise, meaningful,
• interesting and
• helpful in further analysis.
Two main methods of presenting data:
• Tabulation and
• Diagrams
85
TABULATION
• The first step in presenting data
• Principles of tabulation:
– Table should be numbered
– Title- brief & self explanatory
– Headings of columns and rows- clear & concise
– Data must follow an order;
alphabetical/magnitude/geographical/chronological etc.
– Should not be too large & confusing
– Footnotes for any other relevant information
86
• Advantages
• Disadvantages
• Types of tables
– Simple tables
– Frequency distribution tables
87
Simple table
Table No.1: Number of students attending PCD lectures
Lecture no. No.of students
I 100
II 95
III 88
IV 75
Note: During the academic year 2007-’08
88
• Data is split into groups/classes
• Class intervals & frequency
• The no of class intervals - between 5 and 20.
• The class intervals - at equal width.
• Clearly defined class limits – to avoid ambiguity.
e.g. 0-4, 5-9, 10-14, Etc.
• Clearly defined headings
• Units of measurement should be specified.
• It is used to tabulate the quantitative data
Frequency distribution table
89
Marks obtained Frequency
0-10 0
11-20 16
21-30 32
31-40 46
41-50 6
Total 100
Table 2. Marks obtained by III BDS students
in PCD in II internal assessment
Note: During the academic year 2007-’08
90
Diagram
• Extremely useful
• Attractive to the eyes,
• Give a bird's eye view of the entire data,
• Have a lasting impression
• Facilitate comparison of data relating to
different time periods and regions.
91
TYPES OF DIAGRAMS
• Bar Diagram
• Multiple Bar
• Component Bar Diagram
• Proportional Bar Diagram
• Histogram
• Frequency Polygon
• Pie Diagram
• Line diagram
• Cartograms or Spot Map
• Pictogram
92
Basic requirements
• Self explanatory
• Simple and consistent with the data.
• Values of the variables - on horizontal or X-axis and the
frequency - vertical line or Y-axis.
• No too many lines on the graph, should not look clumsy.
• The scale of presentation – right hand top corner of the
graph.
• The details of the variables and frequencies should be
presented on the axes.
93
Bar Diagram
• Represents qualitative data.
• Frequency distribution of one variable.
• Width of the bar remains the same
• The length varies
according to the
frequency in each category.
• Bars - vertical or
horizontal.
Limitations
• Represent only one variable
• Cannot be used for comparison
94
Multiple Bar
• Compare qualitative data with respect to a single variable.
• Facilitates comparison.
– Eg: sex ­
wise or with respect to time or region.
• Each category of the variable have a set of bars of the same
width corresponding to the different sections without any gap in
between the width and the length corresponds to the frequency.
95
Component Bar Diagram:
• Represents qualitative data.
• Both, the number of cases in major groups as
well as the subgroups simultaneously
• Cases of the major group drawn
• Each rectangle is divided according to no in
the subgroups.
97
PIE DIAGRAM
• The frequency of the group is shown in a circle.
• Degree of angle denotes the frequency.
• Instead of comparing the length of bar , the
areas of segments are compared.
Males
Females
98
Line diagram:
• To present continuous data
• Useful to study changes of values in the
variable over time
• X-axis: Hours, days, weeks, months or years
• Y-axis: Value of any quantity pertaining to X-
axis
99
Histogram
• Quantitative data of continuous type.
• Bar diagram without gap between the bars.
• Represents a frequency distribution of
continuous data.
100
Frequency Polygon
• Frequency distribution of quantitative data
• a point is marked over the mid-point of the class
interval, corresponding to the frequency.
• points are connected by straight lines.
• The first point and last point are joined to the
midpoint of previous and next class respectively.
• To compare two or more frequency distributions, lines
of different types are drawn on the same graph.
101
Scatter diagram
Fig.--. Height and Weight of 20 students of CODS
0
10
20
30
40
50
60
70
80
3 4 5 6 7
Height in feet
Weight
in
KGs
Weight
102
Spot Map
• show geographical distribution of
frequencies of a characteristic.
PICTOGRAM
ILLETERATES
PRIMARY EDU
GRADUATES
09/06/2025 104

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MAIN 2._biostatistics.pptx biostatistics

  • 2. CONTENTS  Introduction  Definition  Branches of Biostatistics  Uses/ application of biostatistics  Some important terms  Sampling  Collection of data  Presentation of data - disribution  Summarization of data - measures of central tendency - dispersion - probability  Summary  References 09/06/2025 2
  • 3. introduction  Statistics has been derived from the Latin word status.  Statistics today refers to either quantitative information or to a method of dealing with quantitative or qualitative information.  Statistics may be defined as the discipline concerned with the treatment of numerical data derived from group of individuals. 09/06/2025 3
  • 4.  BIOSTATISTICS 09/06/2025 4 Is a method of collection, organizing, analyzing, tabulating and interpretation of data related to living organisms and human beings. Bios ( life) Metron (measured) Biometry (measurement of life)
  • 5. 09/06/2025 5 “When you can measure what you are speaking about and express it in numbers, you know something about it but when you cannot measure, when you cannot express it in numbers, your knowledge is of meagre and unsatisfactory kind.” - LORD KELVIN
  • 6. Branches of Biostatistics • Descriptive Biostatistics  Methods of producing quantitative summaries of information in biological sciences. Tabulation and Graphical presentation
  • 7. Branches of Biostatistics… Inferential Biostatistics Methods of making generalizations about a larger group based on information about a sample of that group in biological sciences. Primarily performed in two ways: • Estimation • Testing of hypothesis
  • 8. Uses/ APPLICATIONS of biostatistics  In Physiology and Anatomy: 1. To define what is normal or healthy for a population and to find limits of normality in variables. 2. To find the difference between means and proportions of normal at two places or in different periods. 09/06/2025 8
  • 9.  In Pharmacology: 1. To find the action of drug. 2. To compare the action of two different drugs or two successive dosages of the same drug. 3. To find the relative potency of a new drug with respect to a standard drug. 09/06/2025 9
  • 10.  In Medicine: 1. To compare the efficacy of a particular drug, operation or line of treatment. 2. To find an association between two attributes. 3. To identify signs and symptoms of a disease or syndrome. 09/06/2025 10
  • 11. • Most people have heard the statistic that Heart disease is the leading cause of death in America today*. • But how do we know this fact to be true? • Where did that information come from? * [source: Center for Disease Control, USA] In medicine
  • 12. • Back in 1948, when a lot wasn't known about the factors leading to heart disease and stroke, a health research study -- known as the Framingham Heart Study -- was done on 5,209 people living in the town of Framingham, Mass. • These participants hadn't developed any known symptoms of cardiovascular disease and hadn't had a stroke or heart attack. In medicine
  • 13. • They agreed to be followed over a period of time to help researchers learn what factors lead to both conditions. • The study was landmark in several ways. It showed that there was no one cause for getting a heart attack, and combining information about several risk factors could estimate the risk of someone getting the disease. In medicine
  • 14. • Thanks to the Framingham Study, (which is still going on today), we now know the major risk factors that lead to cardiovascular disease. • To reach these conclusions, researchers simply followed the numbers -- the Biostatistics numbers to be exact. In medicine
  • 15. Clinical medicine • Documentation of medical history of diseases. • Planning and conduct of clinical studies. • Evaluating the merits of different procedures. • In providing methods for definition of ‘normal’ and ‘abnormal’.
  • 16. Preventive medicine • To provide the magnitude of any health problem in the community. • To find out the basic factors underlying the ill-health. • To evaluate the health programs which was introduced in the community(success/failure). • To introduce and promote health legislation.
  • 17.  In Community Medicine and Public health: 1. To test usefulness of sera and vaccines in the field. – % of attacks or death among vaccinated subjects is compared with that among non vaccinated. 2. In epidemiological studies – the role of causative factors is statistically tested. 09/06/2025 17
  • 18. USES OF STATISTICS IN DENTAL SCIENCE: 1. To find the statistical difference between means of two groups. Ex: Mean plaque scores of two groups. 2. To assess the state of oral health in the community and to determine the availability and utilization of dental care facilities. 3. To indicate the basic factors underlying the state of oral health by diagnosing the community and find solutions to such problems.
  • 19. Uses of statistics in dental science: 4. To determine success or failure of specific oral health care programs or to evaluate the program action. 5. To promote oral health legislation and in creating administrative standards for oral health care delivery.
  • 20. Some important terms  VARIABLE: A general term for any feature of the unit which is observed or measured is a variable.  It is a characteristic that takes on different values in different persons, places or things. It is denoted as X and notation for orderly series as X1, X2,X3….Xn. The suffix n is symbol for number in the series. 09/06/2025 20
  • 21. Types of variables 09/06/2025 21 Variable Quantitativ e Ordinal Discrete Continuous Qualitative Attribute
  • 22.  CONSTANT: These are quantities that do not vary. Eg:π = 3.141 е = 2.718 They do not require statistical study. In biostatistics, mean, standard deviation, standard error, correlation coefficient and proportion of a particular population are considered as constant. 09/06/2025 22
  • 23.  OBSERVATION: An event and its measurements. Eg: blood press – event 120mmHg – measurement  OBSERVATIONAL UNIT: The source that gives observations such as object, person, etc. In medical stats the term individuals or subjects is used more often. 09/06/2025 23
  • 24.  DATA: A set of values recorded on one or more observational units.  PARAMETER: It is a summary value or constant of a variable that describes the population such as mean, variance, correlation coefficient, proportion etc. 09/06/2025 24
  • 26.  STATISTIC: It is a summary value that describes the sample such as its mean, standard deviation, standard error, correlation coefficient, proportion etc. This value is calculated from the sample and is often applied to population but may or may not be valid estimate of population. Parameter and statistic are often used as synonyms. 09/06/2025 26
  • 27.  PARAMETRIC TEST: It is one in which population constants as described above are used such as mean, variances, etc. and data tend to follow one assumed or established distributions such as normal, binomial, Poisson etc. 09/06/2025 27
  • 28. 09/06/2025 28  NON PARAMETRIC TEST: Tests such as χ2 test in which no constant of a population is used. Data do not follow any specific distribution and no assumptions are made in non parametric tests. Eg. To classify good, better and best you allocate arbitrary numbers or marks to each category.
  • 29. population  In statistics population means the totality of the individual observations about which inferences are to be made.  Populations can be finite or infinite.  Samples of varied size can be drawn carefully with appropriate procedures from their populations which are either finite or infinite. 09/06/2025 29
  • 30. sample  It is a part of the population.  It is a small collection of observations from some larger aggregate about which we want to have information.  Samples drawn should be representative of the population. 09/06/2025 30 Larger the sample, better is the degree of representation of the sample selected.
  • 31. sampling  Samples can be drawn from the entire population through various procedures.  Sampling can be: 09/06/2025 31 Probability sampling Non probability sampling
  • 32.  Probability sampling 09/06/2025 32 Simple random sampling Systematic sampling Stratified random sampling Cluster sampling Multistage sampling Multiphase sampling
  • 33.  Non probability sampling: 09/06/2025 33 Heterogeneous sampling Homogenous sampling Structured sampling Haphazard sampling
  • 34. 1. Simple random sampling  UNRESTRICTED RANDOM SAMPLING  Applicable when population is small, homogenous and readily available.  Used mainly in experimental medicine or clinical trials to check the efficacy of a particular drug. 09/06/2025 34 Principle : every unit of the population has an equal chance of being selected.
  • 35.  To ensure randomness of selection 2 methods are available: 09/06/2025 35 Lottery method Random number procedure
  • 36. 2. Systematic sampling  Simple procedure.  Utilized when a complete list of population from which sample is to be drawn is available.  Systematic procedure is followed to choose a sample by taking every Kth house or patient where k refers to the sample interval which is calculated by the following formula: K = total population/sample size desired 09/06/2025 36
  • 37. Merits of systematic sampling 1. Procedure is simple and convenient for use. 2. Relatively time to be devoted and labor needed are small. 3. If the population is sufficiently large and homogenous and if the numbering of the subjects is available, this method can provide good results. 09/06/2025 37 An element of randomness is introduced into this kind of sampling by randomly selecting from the first K units, the unit with which to start. – RANDOM START. Sample so chosen is sometimes called as “Every K’th systematic sample”
  • 38. 3.Stratified random sampling  Followed when the population is not homogenous.  Population under study is first divided into homogenous groups called strata and the sample is drawn from each stratum at random in proportion to its size.  Gives more representative sample than simple random sampling in a given large population. 09/06/2025 38
  • 39. Merits of stratified random sampling 1. Gives greater accuracy. 2. Gives better representation to each strata compared to simple random sampling. 09/06/2025 39
  • 40. 4. Cluster sampling  Cluster is a group consisting of units such as villages, wards, blocks, factories, workshops etc.  Simple random sampling or systematic sampling procedure is utilized for selection of clusters.  After the selection of clusters randomly, enumeration of individuals in the cluster is carried out. 09/06/2025 40
  • 41.  If the cluster consists of natural groupings and if they are geographic regions it is referred to as AREA SAMPLING. MERITS: 1. Simple and time saving. DEMERITS: 2. Costlier. 3. Provides figures with higher standard errors than other procedures. 09/06/2025 41
  • 42. 5. Multistage sampling  Refers to sampling procedures carried out in several stages using random sampling techniques.  Employed in large scale, country wise or region wise surveys.  Stage wise sampling procedures are to be utilized for selection of households or subjects. 09/06/2025 42
  • 43. 6. Multiphase sampling  Here part of information is collected from whole sample and part from the sub sample.  Numbers in 2nd and 3rd phase will become successively smaller and smaller. MERITS: 1. Less costly. 2. Less laborious. 3. More purposeful. 09/06/2025 43
  • 44. Purposive sampling  If a sample is not randomly selected it is called purposive sampling.  Here the chances of any element being selected are either unknown or guaranteed to be 0% or 100%.  It provides better descriptive data.  Are used in early stages of any branch of knowledge as the focus is on what the researchers will seek to explain. 09/06/2025 44
  • 45. Types of purposive sampling 09/06/2025 45 • Selected from things or people which are in some way alike in a relevant detail. • Quota sampling Heterogenous • Extreme – selecting a group of people with a quality which lies at the top or bottom of the range of such qualities found in general population. • Rare – those which contain a quality or qualities found only rarely. Homogenou s
  • 46. • Strategic informant sampling – selecting people whom you think can give you the most information.for eg comm leaders etc. • Snowball sampling Structured • Is merely one which is readily available. Haphazard 09/06/2025 46
  • 47. Demerits: 1. Serious discrepancies b/w sample & population. 2. Investigator biases likely to occur. 3. Results cannot be generalized. 09/06/2025 47
  • 50. Collection of data  Can be of two types: 1. Primary data 2. Secondary data 09/06/2025 50
  • 51. Primary data 09/06/2025 51 Observation Interview Questionnaires Schedules
  • 52. 1. observation  Used in studies relating to behavioral sciences.  Merits: 1. Elimination of subjective bias. 2. Information obtained relates to what is currently happening. 3. Independent of respondent’s willingness. 09/06/2025 52
  • 53.  Demerits: 1. Expensive. 2. Information provided is limited. 3. Unforeseen factors may interfere. 4. Some people are rarely accessible to direct observation. 09/06/2025 53
  • 54. Types of observation 09/06/2025 54 Structured Unstructured Uncontrolle d Controlled Participant observation Non participant observation Disguised observation
  • 55. Merits of participant type of observation  Researcher is able to record the natural behavior of the group.  Researcher can gather information which could not easily be obtained if he observes in a disinterested manner.  Researcher can even verify the truth of statements. 09/06/2025 55
  • 57. Personal interview  Can be of 2 types: 1. Direct personal investigation 2. Indirect oral investigation 09/06/2025 57 structured unstructured
  • 58. 09/06/2025 58 Focused • Focus attention on the given experience of the respondent and its effects. Clinical • Concerned with broad underlying feelings or motivation or with the course of individuals life experience Non Directive • Simply encourage the respondent to talk about the given topic with a bare minimum questioning.
  • 59. merits 09/06/2025 59 More information and in greater depth Interviewer can overcome resistance of respondents. Greater flexibility Observation method can as well be applied to recording verbal answers to various questions. Personal information can as well be obtained easily.
  • 60. Samples can be more controlled more effectively. Interviewer can control which persons will answer the questions. Interviewer may catch the informant off guard and thus may secure the most spontaneous reactions than would be the case if mailed questionnaire is used. Language of interview can be adopted to the ability or educational level of the person interviewed. Interviewer can collect supplementary information about the respondent’s personal characteristics and environment which is of great value in interpreting results. 09/06/2025 60
  • 61. demerits 09/06/2025 61 Very expensive Possibility of bias Certain types of respondents such as important officials may not be easily approachable More time consuming specially when the sample is large and recalls upon the respondents are necessary Presence of interviewer on the spot may over stimulate the respondent . Organisation required for selecting , training and supervising staff is more complex with formidable problems Interviewing at times may also introduce systematic errors. Effective interview presupposes proper rapport with respondents that would facilitate free and frank responses
  • 62. Pre- requisites and basic tenets of interviewing 09/06/2025 62 1. Interviewers should be carefully selected, trained and briefed. 2. They should be honest, sincere, hardworking, impartial and must possess the technical competence and necessary practical experience. 3. Occasional field checks should be made to ensure that interviewers are neither cheating nor deviating from instructions given to perform their job efficiently. 4. The approach should be friendly, courteous, conversational and unbiased. 5. Interviewer should not show disapproval or surprise of a respondents answer but he must keep the direction of interview in his own hand, discouraging irrelevant conversation and must make all possible effort to keep respondent on the track.
  • 63. Telephone interviews  Merits: 1. More flexible in comparison to mailing methods. 2. Is faster than other methods. 3. Cheaper than personal interviewing method. 4. Recall is easy, callbacks are simple and economical. 5. Replies can be recorded without causing embarrassment to the respondents. 6. Higher rate of response than mailing method. 09/06/2025 63
  • 64. 7. Interviewer can explain requirements more easily. 8. At times access can be gained to respondents who otherwise cannot be contacted for one reason or another. 9. No field staff is required. 10.Representative and wider distribution of sample is possible. 09/06/2025 64
  • 65. Demerits of telephone interviews 1. Little time is given to respondents for considered answers. 2. Surveys are restricted to respondents who have telephone facilities. 3. Extensive geographical coverage may get restricted by cost considerations. 09/06/2025 65
  • 66. 4. It is not suitable for intensive surveys where comprehensive answers are required to various questions. 5. Possibility of bias of the interviewer is relatively more. 6. Questions have to be short and to the point. 09/06/2025 66
  • 67. 3. Collection of data through questionnaires  Used in big enquiries.  Adopted by private individuals, research workers, private and public organizations and even by governments.  A questionnaire consists of a set of questions printed or typed in a definite order on a form or set of forms.  The questionnaire is mailed to the respondents who are expected to read and understand questions and answer them on their own. 09/06/2025 67
  • 68. Merits of questionnaire survey 09/06/2025 68 1. Low cost even when business is large and widely spread geographically 2. Free from bias of the interviewer, answers are in respondents words. 3. Respondents have adequate time to give well thought out answers. 4. Respondents who are not easily approachable, can also be reached conveniently. 5. Large samples can be made use of and thus the results can be made more dependable.
  • 69. Demerits of questionnaire method 09/06/2025 69 1. Low rate of return of duly filled in questionnaires, bias due to no- response is often indeterminate. 2. Can be used only when the respondents are educated and co- operating. 3. The control over questionnaire may be lost once it is sent. 4. There is inbuilt inflexibility because of the difficulty of amending the approach once questionnaires have been dispatched. 5. Possibility of ambiguous replies or omission of replies altogether to certain questions. 6. Difficult to know whether willing respondents are truly representative. 7. Slowest of all methods.
  • 70. Aspects of a questionnaire  General form:  Question sequence: 09/06/2025 70 structured unstructured Questions to be avoided: 1. Questions that put too great a strain on the memory or intellect of the respondent. 2. Questions of a personal character. 3. Questions related to personal wealth etc. Question sequence should always go from the general to the more specific. The answer given to a given question is a function not only of specific question but of all previous questions as well.
  • 71.  Question formulation and wording: Should be simple. Should be easily understood. Should be concrete and should conform to the respondent’s way of thinking. 09/06/2025 71 Multiple choice or closed questionnaire Open ended
  • 72. 09/06/2025 72 Open ended: What sports or other physical activities do you undertake each week on a regular basis? Closed ended: For each of the following sports tick if you regularly spend more than 30 mins each week in that activity? a. Walking b. Jogging c. Cycling d. Swimming
  • 73. Open ended questionnaire Closed ended questionnaire Subject recall Reduced Enhanced Accuracy of response Easier to express complex situations Difficult to investigate complex situations Coverage May pick up anticipated situation Will miss areas not anticipated Size of questionnaire May need fewer lines of text May need many pages of text Analysis More complex Simpler 09/06/2025 73
  • 74. Essentials of a good questionnaire 09/06/2025 74 • Should be short and simple. • Questions should proceed in logical sequence moving from easy to more difficult questions. • Personal and intimate questions should be left to the end. • Technical and vague expressions capable of different interpretations should be avoided in a questionnaire. • Questions may be dichotomous, multiple choice or open ended. • There should be some control questions in the questionnaire which indicate reliability of the respondent. • There should be provision for indications of uncertainty. • The physical appearance of the questionnaire affects the cooperation the researcher receives from the recipients.
  • 75. QUNITAMENSIONAL QUESTIONNAIRE DESIGN  First introduced by Gallow in 1947.  Useful for studying attitudes and opinions. 09/06/2025 75
  • 76. Open ended questionnaire are formulated to elicit awareness of the issue in question and general attitudes towards it. A closed ended question follows to capture information on specific attitudes to the subjects. An open ended question is placed next to explore justifications for their attitudes This is followed by a closed ended question to tap the intensity with which they hold attitudes. 09/06/2025 76
  • 77. 4. Collection of data through schedules  This method requires the selection of enumerators for filling up schedules or assisting respondents to fill up schedules.  The enumerators should be trained to perform their job well and the nature and scope of investigation should be explained to them thoroughly. 09/06/2025 77
  • 78.  Enumerators should be intelligent and must possess the capacity of cross examination in order to find the truth.  They should be honest, hard working, patient and have perseverance. 09/06/2025 78
  • 79. Difference between questionnaires and schedule 09/06/2025 79 Schedule Questionnaire Cost High Low Response rate Higher Lower Completion of questionnaire High Low Complexity of questions Can be high Should be minimized Interviewer bias May be present Not relevant Interviewer variability May be present Not relevant Total study duration Considerably fast Slow
  • 80. Collection of secondary data 09/06/2025 80 Published data Unpublished data
  • 81.  Published data: 09/06/2025 81 1. Various publications of central, state or local govts. 2. Various publications of foreign govts or of international bodies and their subsidiary organizations. 3. Technical and trade journals. 4. Books, magazines and newspapers. 5. Reports and publications of various associations 6. Reports prepared by research scholars, universities. 7. Public records and statistics, historical documents and other sources of information.
  • 82.  Unpublished data: 09/06/2025 82 1. Diaries, letters. 2. Unpublished biographies and autobiographies. 3. May be available with scholars, research workers, trade associations, labor bureaus and other public or private individuals or organizations.
  • 83.  Secondary data should possess following characteristics: Reliability of data Suitability of data Adequacy of data 09/06/2025 83
  • 84. 84 PRESENTATION OF DATA Objectives • make the data simple • concise, meaningful, • interesting and • helpful in further analysis. Two main methods of presenting data: • Tabulation and • Diagrams
  • 85. 85 TABULATION • The first step in presenting data • Principles of tabulation: – Table should be numbered – Title- brief & self explanatory – Headings of columns and rows- clear & concise – Data must follow an order; alphabetical/magnitude/geographical/chronological etc. – Should not be too large & confusing – Footnotes for any other relevant information
  • 86. 86 • Advantages • Disadvantages • Types of tables – Simple tables – Frequency distribution tables
  • 87. 87 Simple table Table No.1: Number of students attending PCD lectures Lecture no. No.of students I 100 II 95 III 88 IV 75 Note: During the academic year 2007-’08
  • 88. 88 • Data is split into groups/classes • Class intervals & frequency • The no of class intervals - between 5 and 20. • The class intervals - at equal width. • Clearly defined class limits – to avoid ambiguity. e.g. 0-4, 5-9, 10-14, Etc. • Clearly defined headings • Units of measurement should be specified. • It is used to tabulate the quantitative data Frequency distribution table
  • 89. 89 Marks obtained Frequency 0-10 0 11-20 16 21-30 32 31-40 46 41-50 6 Total 100 Table 2. Marks obtained by III BDS students in PCD in II internal assessment Note: During the academic year 2007-’08
  • 90. 90 Diagram • Extremely useful • Attractive to the eyes, • Give a bird's eye view of the entire data, • Have a lasting impression • Facilitate comparison of data relating to different time periods and regions.
  • 91. 91 TYPES OF DIAGRAMS • Bar Diagram • Multiple Bar • Component Bar Diagram • Proportional Bar Diagram • Histogram • Frequency Polygon • Pie Diagram • Line diagram • Cartograms or Spot Map • Pictogram
  • 92. 92 Basic requirements • Self explanatory • Simple and consistent with the data. • Values of the variables - on horizontal or X-axis and the frequency - vertical line or Y-axis. • No too many lines on the graph, should not look clumsy. • The scale of presentation – right hand top corner of the graph. • The details of the variables and frequencies should be presented on the axes.
  • 93. 93 Bar Diagram • Represents qualitative data. • Frequency distribution of one variable. • Width of the bar remains the same • The length varies according to the frequency in each category. • Bars - vertical or horizontal. Limitations • Represent only one variable • Cannot be used for comparison
  • 94. 94 Multiple Bar • Compare qualitative data with respect to a single variable. • Facilitates comparison. – Eg: sex ­ wise or with respect to time or region. • Each category of the variable have a set of bars of the same width corresponding to the different sections without any gap in between the width and the length corresponds to the frequency.
  • 95. 95 Component Bar Diagram: • Represents qualitative data. • Both, the number of cases in major groups as well as the subgroups simultaneously • Cases of the major group drawn • Each rectangle is divided according to no in the subgroups.
  • 96. 97 PIE DIAGRAM • The frequency of the group is shown in a circle. • Degree of angle denotes the frequency. • Instead of comparing the length of bar , the areas of segments are compared. Males Females
  • 97. 98 Line diagram: • To present continuous data • Useful to study changes of values in the variable over time • X-axis: Hours, days, weeks, months or years • Y-axis: Value of any quantity pertaining to X- axis
  • 98. 99 Histogram • Quantitative data of continuous type. • Bar diagram without gap between the bars. • Represents a frequency distribution of continuous data.
  • 99. 100 Frequency Polygon • Frequency distribution of quantitative data • a point is marked over the mid-point of the class interval, corresponding to the frequency. • points are connected by straight lines. • The first point and last point are joined to the midpoint of previous and next class respectively. • To compare two or more frequency distributions, lines of different types are drawn on the same graph.
  • 100. 101 Scatter diagram Fig.--. Height and Weight of 20 students of CODS 0 10 20 30 40 50 60 70 80 3 4 5 6 7 Height in feet Weight in KGs Weight
  • 101. 102 Spot Map • show geographical distribution of frequencies of a characteristic.

Editor's Notes

  • #6: Concerned with the presentation , organisation and summarization of data
  • #7: Are used to generalize the data from sample to a larger group of patients
  • #84: Data collected and compiled from experimental work, surveys, registers or records are raw data. These are unsorted and are not much helpful for understanding the underlying trends or its meaning, so these are to be sorted & classified in to characteristic groups or classes like, according to age, sex, social class, number of DMFT, etc.
  • #88: following basic rules are to be followed: