# Graphical Representation of Data (Frequency Polygon, Frequency Curve, Ogive and Pie Diagram)

Graphical Representation of Data: Part 2
(Data Representation Methods: Frequency Polygon, Frequency Curve, Ogive and Pie Chart)

This post is the continuation of the Previous Post (Graphical Representation of Data Part 1).

(3). Frequency Polygon

Ø  The Frequency Polygon is a curve representing a frequency distribution.

Ø  In frequency polygon, the mid values of each class are first obtained.

Ø  In a graph paper, the frequency of each class is plotted against the mid-value of class (on the X axis).

Ø  Then these points are then joined by a straight line.

Ø  This straight line is extended in both directions to meet on the X axis.

Ø  The first point is joined to the lower limit of the first class and the last point is joined to the upper limit of last class. Thus, the frequency polygon is a closed graph.

Ø  The graph now obtained is called Frequency polygon.

Example: Construct a Frequency Polygon using the following data

# Graphical Representation of Data: Part 1 (Diagrammatic Data Representation: Line Chart, Bar Diagrams and Histogram)

Graphical Representation of Data / Variables

Ø  The data presentation in statistics may be Numerical or Graphical.

Ø  If the data is presented in the numerical form, it will not attract the attention of the audience.

Ø  In order to attract the attention of the audience, Graphical Representation method is usually adopted.

Ø  Graphical Representation: It is the representation or presentation of data as Diagrams and Graphs.

Ø  The statistical graphs were first invented by William Playfair in 1786.

Ø  In graphical data representation, the Frequency Distribution Table is represented in a Graph.

Advantages of Graphical Representation of Data

Ø  Data are presented pictorially.

Ø  Give better insight and understanding of the data.

# Graphical Representation of Data- Part-1 – Tables & Tabulation (Tabulation of Data and Things to Remember when Creating a Data Table)

“Science is organized knowledge…
Wisdom is organized life…
Immanuel Kant

What is Data or Variable?

Ø  Data or variables in biostatistics (statistics) are individual observations of a natural phenomenon or an experiment.

Ø  All scientific investigations involve observations on the variables.

Ø  Observations made on these variables are obtained in the form of DATA.

Ø  The reason for calling data as variables is because it has the tendency of variation.

Ø  For example, if you take the size of leaves of a rose plant with many leaves the value of the size of each leaf (individual data) shows variation.

Ø  The individual observations form the data and the data thus collected are called Raw Data.

Ø  The raw data is an ungrouped or unorganized data and it should be classified based on some criterions.

Ø  Only the classified or grouped data can be used for logical interpretations and further statistical analysis.

Data Representation Methods

Ø  Data presentation (representation): ‘For the maximum utilization of data and its correct interpretation, it should be presented in an appropriate way’.

Ø  Different types of data representations methods are:

(1).    Tables

(2).    Graphs / Charts