2. GRAPHICAL REPRESENTATION OF DATA
Data : Collection of facts or information
It can be represented by a variety of graphs
This gives a visual picture of the distribution
Different types of Graphs
Bar graph
Pie graph
Histogram
Frequency polygon
Frequency curve
Ogives
3. FREQUENCY POLYGON
It is a type of graphical representation of data
It is a line graph in which points are joined by straight lines to make a
polygon
It can be constructed by joining the midpoints of the tops of all the
rectangles in a histogram
The height of the point represent the frequencies
It can also be drawn without constructing a Histogram
4. Terms associated with frequency polygon
Class interval : Specific range in which data is going to
fall eg : 20-30
Frequency : The number of times the observation
occurred
Mid point : The center point of bar
Upper limit (U.L) : Ending value of class interval
Lower limit (L.L) : Starting value of class interval
Class mark : Mid value of class
Class mark =
U.L+L.L
2
5. STEPS IN DRAWING A FREQUENCY POLYGON
1. Construct histogram
2. Mark midpoint
3. Join the points by straight line
4. Take rectangle of 0 heights and mark mid points
5. Join the the straight line to these newly marked points
6. Question :
Construct a frequency polygon using data given below:
MARKS 0 - 10 10 -20 20 - 30 30 - 40 40 - 50 50 - 60
No : of
students 5 10 15 20 15 5
7. 0 10 20 30 40 50 60
5
10
15
20
Marks
No
:
of
students
70
-10
Marks obtained by students
8. FREQUENCY POLYGON WITHOUT HISTOGRAM
Construct frequency polygon of following data:
MARKS 30 - 40 40 - 50 50 - 60 60 - 70 70 - 80 80 - 90
No : of
students 5 10 15 20 15 5
Answer:
MARKS No : of Students Class mark
30 – 40 5 35 (
40+30
2
=
70
2
=35)
40 – 50 10 45
50 – 60 15 55
60 – 70 20 65
70 - 80 5 75
9. 30 40 50 60 70 80
5
10
15
20
MARK
No
of
students
Marks obtained by students
0
10. Advantages
It help to sort out and represent data
Give a clear picture distribution of data
Simple and easier to understand
We can draw two or more frequency polygons on the same axes/graph
Thus we can make comparisons between the sets of data easily
11. Disadvantages
Can be used only with continuous data
Less accurate representation of data because it represent
frequency of each class by single point
In short : It can mainly used to show the change and for comparison