The document discusses various forms of diagrams used for representing statistical data, such as bar diagrams, pie diagrams, and pictograms, emphasizing their simplicity and effectiveness for comparison. It outlines best practices for creating diagrams, including maintaining scale, clear titles, and the proper selection of diagram types based on data characteristics. Additionally, it distinguishes between diagrams and graphs, noting that while diagrams are suitable for discrete data visualization, graphs allow for further statistical analysis.

2.  A diagram is a visual form for presentation of
statistical data. The diagram refers various types
of devices such as bars, circles, maps, pictorials
and cartograms etc.

3.  They are simple, attractive and easy understandable
 They give quick information
 It helps to compare the variables
 Diagrams are more suitable to illustrate discrete data
 It will have more stable effect in the reader’s mind.

4. ◦ Diagrams shows approximate value
◦ Diagrams are not suitable for further analysis
◦ Some diagrams are limited to experts
(multidimensional)
◦ Details cannot be provided fully
◦ It is useful only for comparison

5.  Each diagram should have suitable title indicating
the theme with which diagram is intended at the
top or bottom.
 The size of diagram should emphasize the
important characteristics of data.
 Approximate proposition should be maintained for
length and breadth of diagram.

6.  A proper / suitable scale to be applied for diagram
 Selection of approximate diagram is important
and wrong selection may mislead the reader.
 Source of data should be mentioned at bottom.
 Diagram should be simple and attractive
 Diagram should be effective than complex.

7.  This is simplest type of one dimensional
diagram. On the basis of size of the figures,
heights of the bar / lines are drawn.
 The distance between bars are kept uniform.
The limitation of this diagram are it is not
attractive cannot provide more than one
information.

9.  A simple bar diagram can be drawn using
horizontal or vertical bar.
 In business and economics, it is very common
diagram.

11.  Multiple bar diagrams are used to provide more
information than simple bar diagram.
 Multiple bar diagram provides more than one
phenomenon and highly useful for direct
comparison.
 The bars are drawn side by side and different
columns, shades hatches can be used for
indicating each variables used.

13. Subdivided bar diagram - definition
Sub-divided Bar Diagram is a way of representation
of data in which the total length of the bar is divided
into different parts/components in particular ratios
depending upon the contributions of various
components.

14. Percentage Bar diagram:
• This is derived further from the subdivided bar
diagrams. In this, each bar has the same height that
represents 100 percent of the Y-axis in totality.
Further, each bar is divided into sections based on
percentages calculated according to the contribution
of these sections.
• Percentage bar diagrams are used when the values
are really high. This is because using subdivided bar
diagrams in such cases would not be easy and
appropriate.

16.  In two-dimensional diagram both breadth and
length of the diagram (i.e. area of the diagram)
are considered as area of diagram represents
the data. The important two dimensional
diagrams are
◦ Rectangular diagram
◦ Square diagram

17. Rectangular diagram
 Rectangular diagrams are used to depict two or
more variables. This diagram helps for direct
comparison.
 The area of rectangular are kept in proportion to
the values. It may be of two types.
 Percentage sub-divided rectangular diagram
 Sub-divided rectangular diagram

18.  In former case width of the rectangular are
proportional to the values, the various
components of the values are converted into
percentages and rectangles are divided
according to them.
 While later case is used to show some related
phenomenon like cost per unit, quality of
production etc.

20.  To draw square diagrams, the
square root is taken of the values
of the various items to be shown.
 A suitable scale may be used to
depict the diagram. Ratios are to
be maintained to draw squares.

21.  Pie diagram helps us to show the portioning of a
total into its component parts. It is used to show
classes or groups of data in proportion to whole
data set.
 The entire pie represents all the data, while
each slice represents a different class or group
within the whole.

24.  A pictogram is one of the simplest (and most
popular) forms of data visualization out there.
Also known as “pictographs”, “icon charts”,
“picture charts”, and “pictorial unit charts”,
pictograms use a series of repeated icons to
visualize simple data.

26. The following points are to be kept in mind for the
choice of diagram.
 To common man, who has less knowledge in
statistics cartogram and pictograms are suited.
 To present the components apart from magnitude of
values, sub-divided bar diagram can be used.
 When a large number of components are to be
shown, pie diagram is suitable

27.  A graphic presentation a visual form of
presentation graphs are drawn on a special type
of paper known are graph paper.
 Common graphic representations are
◦ Histogram
◦ Frequency polygon
◦ Cumulative frequency curve (ogive)

28.  It provides attractive and impressive view
 Simplifies complexity of data
 Helps for direct comparison
 It helps for further statistical analysis
 It is simplest method of presentation of data
 It shows trend and pattern of data

29. Diagram Graph
1. Ordinary paper can be used 1. Graph paper is required
2. It is attractive and easily understandable 2. Needs some effect to understand
3. It is appropriate and effective to measure
more variable
3. It creates problem
4. It can’t be used for further analysis 4. Can be used for further analysis
5. It gives comparison 5. It shows relationship between variables
6. Data are represented by bars, rectangles 6. Points and lines are used to represent data

30.  In this type of representation the given data are
plotted in the form of series of rectangles.
 Class intervals are marked along the x-axis and the
frequencies are along the y-axis according to suitable
scale.
 Unlike the bar chart, which is one-dimensional, a
histogram is two-dimensional in which the length and
width are both important.

31.  A histogram is constructed from a frequency
distribution of grouped data, where the height of
rectangle is proportional to respective frequency and
width represents the class interval.
 Each rectangle is joined with other and the blank
space between the rectangles would mean that the
category is empty and there is no values in that class
interval.

33.  A frequency polygon is a line chart of frequency
distribution in which either the values of discrete
variables or the mid-point of class intervals are
plotted against the frequency and those plotted
points are joined together by straight lines.

35.  ogives are the graphic representations of a
cumulative frequency distribution.
 These ogives are classified as ‘less than’ and ‘more
than ogives’.
 In case of ‘less than’, cumulative frequencies are
plotted against upper boundaries of their respective
class intervals.
 In case of ‘grater than’ cumulative frequencies are
plotted against lower boundaries of their respective
class intervals.

38.  False Base Line is a device relating to graphical
presentation.
 This line is used to break the continuity of Y-axis with
the origin.
 A false base line is used when figures start with high
values.
 If we maintain continuity of the value from the origin
then sufficient portion of the graph would go waste.

39.  In the diagram given here, since all the values are
confined between 800 and 1100.
 Therefore, in such a case, a false base line is used.
After the false base line, we can start from the actual
high figures as shown in the graph.

40. Objects of using False Base:
 To magnify the major fluctuations on the graph so as
to make them clearly visible.
 To economise in space On X-axis also, we can
represent false base by drawing a kinked line.