1.  The diagrams should be simple.
 Each diagram must be given a clear,
concise and suitable title without
damaging clarity.
 A proper proportion between height and
width must be maintained in order to
avoid an unpleasant look.
 Select a proper scale; it should be in
even numbers or in multiples of five or
ten.e.g. 25,50, 75 or 10, 20, 30, 40, ....
etc. But no fixed rule.
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2.  In order to clear certain points, always put
footnotes.
 An index, explaining different lines, shades
and colors should be given.
 Diagrams should be absolutely neat and
clean.
 "The important point that must be borne in
mind at all times that the pictorial
representation chosen for any situation must
depict the true relationship and point out the
proper conclusion. Above all the chart must
be honest." .... C. W. LOWE.
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3.  Graphics, such as maps, graphs and diagrams, are used to
represent large volume of data.
They are necessary:
 · If the information is presented in tabular form or in a descriptive
record, it becomes
difficult to draw results.
 · Graphical form makes it possible to easily draw visual impressions
of data.
 · The graphic method of the representation of data enhances our
understanding.
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4.  · It makes the comparisons easy.
 · Besides, such methods create an imprint on mind for a longer time.
 · It is a time consuming task to draw inferences about whatever is
being presented in
non–graphical form.
 · It presents characteristics in a simplified way.
 · These makes it easy to understand the patterns of population
growth, distribution and
the density, sex ratio, age–sex composition, occupational structure,
etc.
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5.  Selection of a Suitable Graphical Method
Each characteristic of the data can only be
suitably represented by an appropriate
graphical method.
 Selection of Suitable Scale
Each diagram or map is drawn to a scale
which is used to measure the data. The scale
mustcover the entire data that is to be
represented. The scale should neither be too
large nor toosmall.
 Design
T itle,Legend or Index,Direction
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6.  Diagrams and Graphs are meant for a lay
man.
 Tables are meant for statisticians for the
purpose of further analysis.
 Diagrams give only an approximate idea.
 Tables contain precise figures. Exact
values can be read from tables.
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7.  Diagrams can be more easily compared, and can
be interpreted by a layman.
 Comparison and interpretations of tables can only
be done by statisticians and it is a difficult task.
Diagrams and graphs cannot present much
information.
 Tables can present more information.
 Diagrams are more attractive and have a visual
appeal.
 Tables are dry for a layman ( may be attractive to a
statistician.)
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8. Presentation of Quantitative Data by graphs
 Histograph
 Frequency polygon
 Line chart or graph
 Cumulative frequency diagram
 Scatter or dot diagram
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9. Presentation of Qualitative Data
 Bar diagram
 Pie or sector diagram
 Pictogram
 Map diagram or spot map
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10.  Purpose
To graphically summarize the distribution
of a univariate data set.
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11.  Special form of Bar diagram which
represent categories of continuous and
ordered data.
 It consists of a series of bars and blocks.
 The class interval are given along the
horizontal axis and the frequency along the
vertical axis.
 The width of bar represents the interval of
each category.
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12. The histogram graphically shows the
following:
 Center (i.e., the location) of the data;
 Spread (i.e., the scale) of the data;
 Skewness of the data;
 Presence of outliers; and
 Presence of multiple modes in the data.
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13.  It is an area diagram.
 X axis depicts the category of data and y
axis depicts the frequency of data in each
category.
 Frequency polygon can be obtained from
histogram by joining midpoints of blocks
or rectangles of the histogram.
 It can be more useful than the histogram
because several frequency distributions
can be plotted on one graph.
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15.  It is used when sets of data are to be
illustrated on the same diagram such
as death and birth rates.
 Frequency polygons are a graphical
device for understanding the shapes of
distributions. They serve the same
purpose as histograms, but are
especially helpful in comparing sets of
data. Frequency polygons are also a
good choice for displaying cumulative
frequency distributions.
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16. Frequency distribution curves are like frequency polygons. In
frequency distribution, instead of using straight line segments, a
smooth curve is used to connect the points.
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17. A smooth curve which corresponds to the
limiting case of a histogram computed for a
frequency distribution of a continuous
distribution as the number of data points
becomes very large.
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18. Shape of Distribution Curves:-
 (i) Symmetrical or bell-shaped
 (ii) Moderately symmetrical or skew
 (ii) J-shaped and
 (iv) U-shaped.
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19.  Histogram is a bar graph while frequency
polygon is a line graph.
 Frequency polygon is more useful and
practical. In frequency polygon it is easy
to know the trends of the distribution;
unable to do so in histogram.
 Histogram gives a very clear and accurate
picture of the relative proportion of the
frequency from interval to interval.
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20.  It is used to show the trends of events with
the passage of time.
 It is a frequency polygon presenting
variations by a line .the class interval can
be a week, a year or 100year.
 A line graph is useful for displaying data
or information that changes continuously
over time.
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21. The line graphs are usually drawn to
represent the time series data related
to the temperature, rainfall, population
growth, birth rates and the death
rates.
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22. The various parts of a line graph.
 TitleThe title of the line graph tells us what the graph is about.
 LabelsThe horizontal label across the bottom and the vertical
label along the side tells us what kinds of facts are listed.
 ScalesThe horizontal scale across the bottom and the vertical
scale along the side tell us how much or how many.
 PointsThe points or dots on the graph show us the facts.
 LinesThe lines connecting the points give estimates of the
values between the points.
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23.  Polygraph is a line graph in which two or
more than two variables are shown on a
same diagram by different lines. It helps in
comparing the data. Examples which can be
shown as polygraph are:
 · The growth rate of different crops like
rice, wheat, pulses in one diagram.
 · The birth rates, death rates and life
expectancy in one diagram.
 · Sex ratio in different states or countries in
one diagram.
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26. The line and bar graphs as drawn
separately may also be combined
to depict the data related to some
of the closely associated
characteristics such as the
climatic data of mean monthly
temperatures and rainfall.
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27.  Multiple bar diagrams are constructed to
represent two or more than two variables
for the purpose of comparison. For
example, a multiple bar diagram may be
constructed to show
proportion of males and females in the
total, rural and urban population or the
share of canal, tube well and well irrigation
in the total irrigated area in different states.
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29. The curve obtained by plotting cumulating frequencies is called a
cumulative frequency curve or an ogive.
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30.  1)Add up the progressive totals of
frequencies, class by class, to get the
cumulative frequencies.
 2) Plot classes on the horizontal ( x-axis )
and cumulative frequencies on the vertical
( y-axis).
 3) Join the points by a smooth curve.
 Ogives start at (i) zero on the vertical axis,
 (ii) outside class limit of the last class.
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31. A Scatter Diagram examines the
relationships between data collected for
two different characteristics. Although the
Scatter Diagram cannot determine the
cause of such a relationship, it can show
whether or not such a relationship
exists, and if so, just how strong it is. The
analysis produced by the Scatter Diagram
is called Regression Analysis.
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32.  Use a Scatter Diagram to determine if
there is correlation between two
characteristics. Correlation implies that as
one variable changes, the other also
changes. Although this may indicate a
cause and effect relationship, this is not
always the case, since there may be a
third characteristic (or many more) that are
actually the cause, and both the
characteristics of interest are the effect.
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34. A scatter diagram is a tool for analyzing
relationships between two variables. One
variable is plotted on the horizontal axis and
the other is plotted on the vertical axis.
 Scatter diagram is used to prove or disprove
cause-and-effect relationships.
 Examination of theories about cause-and-
effect relationships and to search for root
causes of an identified problem.
 Scatter diagram used to design a control
system to ensure that gains from quality
improvement efforts are maintained.
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35.  Scatter diagrams will generally show one of
six possible correlations between the
variables:
1.Strong Positive Correlation The value of Y
clearly increases as the value of X increases.
2.Strong Negative Correlation The value of Y
clearly decreases as the value of X increases.
3.Weak Positive Correlation The value of Y
increases slightly as the value of X increases
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36. 4.Weak Negative Correlation The value of Y
decreases slightly as the value of X
increases.
5.Complex Correlation The value of Y
seems to be related to the value of X, but
the relationship is not easily determined.
6.No Correlation There is no demonstrated
connection between the two variables.
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