method of data presentation biostatics pptx

METHODS
OF
REPRESENTATION OF
DATA
1

TABLE OF CONTENT
2
1. Introduction
a) What do you mean by data
b) Types of statistical data
i. Qualitative data
ii. Quantitative data
2. Methods of representation of data
a) Tabulation
b) Drawings/Graphs
I. Presentation of Quantitative data through graphs
i. Histogram
ii. Frequency Polygon
iii. Frequency Curve
iv. Line chart or graph
v. Cumulative frequency diagram
vi. Scatter/Dot diagram

TABLE OF CONTENT
3
II. Presentation of Qualitative data through graphs
i. Bar diagram
ii. Pie/Sector diagram
iii. Pictogram/Picture diagram
iv. Map diagram / Spot map
3. Summary
4. Conclusion

INTRODUCTION
5
 DATA :
 Data, the plural of datum ,are facts expressed in
numerical terms .
 Information in raw or unorganized form (such as
alphabets, numbers, or symbols) that refer to, or
represent, conditions, ideas, or objects.

INTRODUCTION Contd.
6
Statistical data can be divided into broad
categories :
1. Qualitative data
2. Quantitative data
Dixit JV.Principles and practice of biostatistics.4th ed.In:M/s Banarsidas bhanot publishers
2009.chapter-2.Collection and presentation of data.p.5-24

INTRODUCTION Contd.
7
1. Qualitative Data :
 Is also called as enumeration data.
 It represents a particular quality or attribute.
 These are expressed as numbers without units of
measurements.
 Examples : Religion,Sex,blood group, (Tall/Short)
etc
Dixit JV.Principles and practice of biostatistics.4th ed.In:M/s Banarsidas bhanot publishers
2009.chapter-2.Collection and presentation of data.p.5-24

INTRODUCTION Contd.
8
2. Quantitative Data:
 Is also called as measurement data.
 These are expressed as number with or without units
of measurements.
 Example : Height in cm,Weight in kg,Blood pressure
(mm of Hg)

NEED FOR PRESENTATION OF DATA
9
 The information collected from various sources is
called as raw data .
 It does not lead to any understanding of the situation
 Hence it should be compiled, classified & presented in
a purposive manner to bring out important points
clearly and strikingly

10
PRINCIPLES OF PRESENTATION OF
DATA

PRINCIPLES OF PRESENTATION OF DATA
11
 Data should be presented in such a way that data
should:
 arouse interest in reader
 Become concise without losing important details.
 Become simple & meaningful
 Facilitate further statistical analysis
 Define problem & suggest the solution too.

12
METHODS OF REPRESENTATION OF
DATA

DATA
13
There are two important methods for
presenting the data:
1. Tabulation
2. Diagrams/Graphs

METHODS OF REPRESENTATION OF DATA
14
1. TABULATION:
 Tables are simple devices used for presentation of
statistical data
General principles that are accepted for table
construction:
 Tables should be as simple as possible
 It should be self-explanatory
 Each row & column should be labeled concisely & clearly

DATA
15
1. TABULATION Contd.:
 Table must be numbered
 Title should be clear,concise,and to the point.
 Tables should not be too large
 Foot notes be given wherever necessary providing
additional information, source or explanatory
notes.

TYPES OF TABLES
16
1. Master Table
2. Simple Table
3. Frequency Distribution Table

TYPES OF TABLES
17
1. Master Table:
 They are tables, which contain all the data obtained
from a survey.
Sl.No. Age Sex Education D M F DMF PI
001
002
003
004

TYPES OF TABLES
18
2. Simple Table
 They are one way tables which supply answers to
questions about one characteristic of data only.

TYPES OF TABLES
19
 Example of a simple table :
Number of students in colleges of RSS
Trust in 2011.
Name Of College No.Of Students
Dental College 540
Nursing College 675
College of Physiotherapy 586
College of Management 1025
Total 2826

TYPES OF TABLES
20
3. Frequency Distribution Table
 The simplest table is a two column frequency table
 The first column lists the classes into which the data
are grouped
 The second column lists the frequency for each
classification

TYPES OF TABLES
21
3. Frequency Distribution Table Contd.:
Example of a Frequency Distribution table :
Anemia in boys and girls of RV Dental College
Sex Type Of Anemia Total
Mild Moderate Severe
Boys 615 85 15 260
Girls 190 120 45 355
Total 350 205 60 615

Table Of Content
22
1. Introduction
a) Tabulation
b) Drawings/Graphs
I. Presentation of Quantitative data through
graphs
II. Presentation of Qualitative data through
graphs
3. Summary
4. Evaluation Of Learning Objective
5. Conclusion

METHODS OF REPRESENTATION OF DATA
23
2. Diagrams/Graphs

DIAGRAMS/GRAPHS
24
 Diagrams & graphs are one of the most convincing and
appealing ways of depicting results.
They are extremely useful because:
 They are attractive to the eyes.
 Gives a bird’s eye view of the entire data.
 Has a lasting impression on the mind of the layman
 Facilitates comparison of data

DIAGRAMS/GRAPHS
25
Principles in the construction of Diagrams & Graphs:
 Every diagram must be given a title that is self
explanatory.
 It should be simple & consistent with the data.
 The no. of lines drawn in any graph should not be
many. This makes it look clumsy.
 The scale of presentation for the X-axis & Y-axis
should be mentioned

26
PRESENTATION OF QUANTITATIVE
DATA

DATA
27
 Presentation of quantitative data is through
graphs.
 The common graphs in use are:
1. Histogram
2. Frequency Polygon
3. Frequency Curve
4. Line chart or graph
5. Cumulative frequency diagram
6. Scatter/Dot diagram

PRESENTATION OF QUANTITATIVE DATA
28
1. Histogram

DATA
29
1. HISTOGRAM :
 It’s a pictorial diagram of frequency distribution.
 The histogram is a series of columns or vertical
rectangles, each having as its base one class interval,
and the frequency or number of cases in that class as
its height
 The class intervals are given on the X axis and the
frequencies along the Y axis.

30
1. HISTOGRAM Contd.:
 There is no space between the cells on a
histogram.
 This graph is not to be confused with a bar chart,
which has space between the cells.

HISTOGRAM :
31
Example : The following is the frequency distribution
of weights of 30 students of I year dental students
of a dental college . Draw a histogram to represent
the data.
Classes 45-50 50-55 55-60 60-65 65-70 Total
Frequency 3 7 12 5 3 30

Solution :
32
 For drawing a histogram we go through the steps similar to
those of a bar graph.
They are given below :
 Step 1 : On a paper, we draw two perpendicular lines and call
them horizontal and vertical axes.
 Step 2 : Along the horizontal axis, we take classes of equal
width :45–50, 50–55, ...... As the axis starts from 45–50, we
take one interval 40–45 before it and put a kink on axis
before that
 Step 3 : Choose a suitable scale on the vertical axis to
represent the frequency. It can start from 0 to 12, with a
step of 2, i.e., 0, 2, 4, 6, ...., 12, 14
 Step 4 : Draw the rectangles as shown in Fig.

34
2. FREQUENCY POLYGON:

DATA
35
2. FREQUENCY POLYGON:
 Its an area diagram of frequency distribution developed
over a histogram.
 The X axis depicts the categories of data and the Y axis
depicts the frequency of data in each category.
 Frequency polygon can be obtained from histogram by
joining mid points of blocks or rectangles of the
histogram.

FREQUENCY POLYGON:
36
EXAMPLE : The daily earnings of 100 Private dental
practioners are given below :
Daily
Earnings
in Rs.
200-300 300-400 400-500 500-600 600-700 700-800 800-900
No. of
Dental
Clinics
3 12 15 30 25 12 3

38
3. FREQUENCY CURVE :

DATA
39
3. FREQUENCY CURVE :
 As the number of observations become very large
& class intervals very much reduced, the frequency
polygon loses its angulation and gives rise to a
smooth curve known as frequency curve.
 Such frequency curves are often encountered
when we study the distribution of most of the
biological variables.

41
NOTE:
 Frequency polygon and frequency curves are same
except frequency curve is drawn using free hand
and frequency polygon is drawn using scale. (Each
point is joint using scale)

42
4. LINE CHART OR GRAPH

DATA
43
4. LINE CHART OR GRAPH
 Line charts are used to show the trend of events
with the passage of time.
 It is nothing but a frequency polygon presenting
variations by a line.
 The class interval can be a week, a month, a year or
100 years.
 Scale used can change shape of line diagram but
not its trend

LINE CHART OR GRAPH
44
EXAMPLE:
The table below shows daily temperatures for Bangalore
City, recorded for 6 days, in degrees Fahrenheit.
Temperature in Bangalore City
Day Temperature
1 43
2 53
3 50
4 57
5 59
6 67

LINE CHART OR GRAPH
45
Temperature In Bangalore City

46
5. CUMULATIVE FREQUENCY DIAGRAM/OGIVE

DATA
47
5. CUMULATIVE FREQUENCY DIAGRAM/OGIVE:
 Its also a representation of continuous and
ordered data
 In this case, the frequency of data in each
category represents the sum of the data from the
category and from the preceding category.
 Cumulative frequencies are plotted opposite the
group limits of the attribute or variable.
 These points are joined by a smooth free hand
curve to get a cumulative frequency diagram or
“ogive”.

DATA
48
Example :
A Professor arranged the marks gained by all year 10
pupils in a Anatomy test in a table as shown below:
Marks Frequency of
pupils
11-20 2
21-30 11
31-40 19
41-50 36
51-60 42
61-70 31
71-80 13
81-90 6

CUMULATIVE FREQUENCY
DIAGRAM/OGIVE:
49
 This table shows the number of pupils (called the
frequency) who gained marks in the various mark
bands, eg 31-40.
 For example, the number of pupils who scored
between 21 and 30 marks was 11.
 No pupil scored fewer than 11 marks or more than
90 marks.

CUMULATIVE FREQUENCY DIAGRAM/OGIVE:
50
 To create a cumulative total for the frequency of
pupils in each group (called the cumulative frequency)
a third column is created as shown below:
Marks Frequency Cumulative
Total
Cumulative
frequency
11-20 2 2 2
21-30 11 2+11 13
31-40 19 13+19 32
41-50 36 32+36 68
51-60 42 68+42 110
61-70 31 110+31 141
71-80 13 141+13 154
81-90 6 154+6 160

CUMULATIVE FREQUENCY
DIAGRAM/OGIVE:
51
 The cumulative frequency column makes it easy to
see at a glance that 68 pupils scored 50 marks or
fewer, and that 32 pupils scored 40 marks or
fewer.
Cumulative Frequency Graph for year 10 anatomy results

52
6. SCATTER/DOT DIAGRAM:

53
6. SCATTER/DOT DIAGRAM:
 These show relationship between two variables
 Also called as correlation diagram
 Perpendicular drawn from each scatter point on x
& y axis gives value of two variables associated
with it.
 Depending on the clustering of scatter points this
diagram can provide evidence of positive, negative
or no correlation

SCATTER/DOT DIAGRAM:
54
Example
The Prosthodontics and Periodontics results of ten dental
students are shown in the table below:
Name Sal Kim Bill Tom Gita Alex Bev Ken Alen Jo
Prostho 20 71 60 52 80 32 47 90 49 80
Perio 30 80 65 50 81 38 40 87 55 70

55
 To see whether there is a correlation between the
Prostho and Perio marks, you could plot a scatter
diagram.
 The Prostho mark is on the horizontal scale and
the corresponding Perio mark on the vertical scale.
 Bill's Prostho mark was 60 and his Perio mark was
65, so his results are represented by the orange
point at coordinates (60, 65).

56 Prosthodontics Mark
Periodontics
Marks

SCATTER PLOT
57
Things to look for:
 If the points cluster in a band running from lower left
to upper right, there is a positive correlation (if x
increases, y increases).
 If the points cluster in a band from upper left to
lower right, there is a negative correlation (if x
increases, y decreases).

58
 Imagine drawing a straight line or curve through the
data so that it "fits" as well as possible. The more the
points cluster closely around the imaginary line of
best fit, the stronger the relationship that exists
between the two variables.
 If it is hard to see where you would draw a line, and if
the points show no significant clustering, there is
probably no correlation.

Table Of Content
59
1. Introduction
a) Tabulation
b) Drawings/Graphs
I. Presentation of Quantitative data
through graphs
II. Presentation of Qualitative data
through graphs
3. Summary
4. Evaluation Of Learning Objective
5. Conclusion

60
PRESENTATION OF QUALITATIVE DATA

61
 Presentation of qualitative data is through
diagrams.
 The common diagrams in use are :
1. Bar diagram
2. Pie or sector diagram
3. Pictogram or Picture diagram
4. Map diagram or spot map

62
1. BAR DIAGRAM :

PRESENTATION OF QUANLITATIVE
DATA
63
1. BAR DIAGRAM :
 Bar diagram is a popular & easy method adopted
for visual comparison of the magnitude of
different frequency such as
morbity,mortality,immunization status of
population in different ages, sexes or places
 There are three types of bar diagrams:
a) Simple bar diagram
b) Multiple bar diagram
c) Proportional bar diagram

PRESENTATION OF QUANLITATIVE DATA
64
a) Simple bar diagram:
 It represents only one variable.
Example :
Age-wise prevalence of dental caries (in percentage)

Simple bar diagram:
65
5-9 years 10-14 years 15-19 years
0
10
20
30
40
50
60
70
80
90
100
Caries
Caries
Age-wise prevalence of dental caries (in percentage)

66
b) Multiple bar diagram:
 This diagram is similar to the bar diagram except that
for each category of the variable there are set of
bars of the same width corresponding to the different
sections without any gap in between
Example:
Prevalence of dental caries based on age & gender

Multiple bar diagram:
67
5-9 years 10-14 years 15-19 years
0
10
20
30
40
50
60
70
80
90
100
Males
Females
Prevalence Of Dental Caries Based On Age & Gender

68
c) Proportional bar diagram:
 The individual bars are divided into two or more parts.
 This diagram is used to compare the sub-groups
between different major groups of observations.
Example:
Prevalence of dental caries based on age and gender

Proportional bar diagram:
69
5-9 years
10-14Years
15-19 years
0 20 40 60 80 100 120 140 160 180 200
Females
Males
Prevalence of dental caries based on age and gender

70
2. PIE/SECTOR DIAGRAM:

71
2. PIE/SECTOR DIAGRAM:
 They are so called because the entire graph looks
like a pie & its component represent slices cut
from a pie.
 The total angle at the Centre of a circle is equal to
360 & it represents the total frequency.
 It is divided into different sectors corresponding
to the frequencies of the variables in the
distribution.
 Eg.: Distribution of dental disease in 30-40 year
olds.

DATA
72
2. PIE/SECTOR DIAGRAM Contd.:
 The segments are then shaded with different
shades or color and an index is provided for these
shade colors
 This diagram cannot be used to represent two or
more data sets.
Peter S. Essentials of community and preventive dentistry;4th ed.Arya publishing house
2009.chapter-14.Research methodology and biostatistics 365-384.

PIE/SECTOR DIAGRAM:
73
Dental Diseases
Caries
Gingivitis
Periodontitis
30
35
45
Distribution of dental diseases in 30-40 year olds

74
3. PICTOGRAM OR PICTURE DIAGRAM:

DATA
75
3. PICTOGRAM OR PICTURE DIAGRAM:
 These diagrams are used for a layman man those
who cannot understand technical charts like bar
charts.
 Here pictures or symbols are used to present the
data.
Example:
 For physically disabled person the symbol of
person sitting on wheelchair is used in public
places.

77
4. MAP DIAGRAM OR SPOT MAP:

DATA
78
4. MAP DIAGRAM OR SPOT MAP:
 These maps are used to show geographical
distribution of frequencies of a characteristic.
 It is a map of an area with the location of each
case of an illness,death,abnormality or condition
identified by a spot ,dot or other symbol on the
map

CONCLUSION
80
 "A picture is worth a thousand words" refers to
the notion that a complex idea can be conveyed
with just a single still image.
 Representation of data through charts & diagrams
also aptly characterizes one of the main goals of
visualization, namely making it possible to absorb
large amounts of data quickly.

REFERENCES
81
1. Dixit JV.Principles and practice of
biostatistics.4th
ed.In:M/s Banarsidas bhanot
publishers 2009.chapter-2.Collection and
presentation of data.p.5-24
2. Mahajan B.K.Methods in Biostatistics.6th ed.
Jaypee Brothers,Medical publishers(p)
Ltd.chapter-6.p.88-102
3. Hiremath SS.Textbook of preventive and
community dentistry.1st ed.Elsevier
2007:chapter-48. Biostatistics,p.483-488

REFERENCES
82
4. Peter S. Essentials of community and preventive
dentistry;4th ed.Arya publishing house
2009.chapter-14.Research methodology and
biostatistics 365-384
5. Indrayan A, Sarmukaddam SB. Medical
Biostatistic.1st ed. (Marcel Dekker,Inc. New
York) chapter-3.p.66-78

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