What is mean by a presentation of Data? There are various methods of collecting statistical raw data. Whatsoever method is used in the collection of data, the question arises; what is the procedure for presentation of data? Everyone is aware of the fact that raw data is in great bulk and it is very difficult to understand and handle data in this form. There are various statistical tools which are used to present data in a meaningful manner. These tools are helpful in classification, tabulation and graphical presentation of statistical data.

When statistical data are arranged according to some common characteristic or similarities, it is known as classified data. Data classification is the categorization of data for its most effective and efficient use. The statistical data may be classified according to geographical location, chronological order etc. The following are the various methods which are used for presentation of data.

**FREQUENCY DISTRIBUTION| PRESENTATION OF DATA**

A representation of statistical data in a tabular format is called a frequency distribution. A frequency distribution displays the number of observations a particular class. The intervals must be mutually exclusive and exhaustive.

**CUMULATIVE FREQUENCY DISTRIBUTION: **A table showing the cumulative frequencies is called a cumulative frequency distribution. A cumulative frequency distribution is a summary of a set of data showing the number of items less than or equal to the upper class boundary of each class. A cumulative frequency distribution is also called less than frequency distribution.

**DECUMULATIVE FREQUENCY DISTRIBUTION:**

A decumulative frequency distribution is a summary of a set of data showing the number of items more than or equal to the lower class boundary of each class. A decumulative frequency distribution is also called more than frequency distribution.

**RELATIVE FREQUENCY DISTRIBUTION **

A relative frequency distribution is a tabular summary of a set of data showing the relative frequency of items in each of several non-overlapping classes. The relative frequency of a class is obtained by dividing the frequency of the class by the total of frequencies of the whole data. The relative frequency is the fraction or proportion of the total number of items belonging to a class.

**PERCENTAGE RELATIVE FREQUENCY DISTRIBUTION **

The relative frequency distribution expressed in percentage form is called a percentage frequency distribution.

**GRAPHIC AND DIAGRAMMATIC REPRESENTATION OF DATA:**

BAR CHART:

A bar chart is a diagram showing a number of bars of equal width and each bar is followed by a reasonable space. The height of each bar is taken according to the size of that class. A bar chart is usually used to express the data of geographical nature.

**PIE CHART: **A pie chart or a circular diagram is represented by drawing a circle of 360 degrees and subdividing the circle into various sectors, where each sector is proportional to the quantity it represents.

**HISTOGRAM**

A histogram is a graph of frequency distribution. The graph is represented by a set of adjacent rectangles whose width is equal to the size of a class and whose area is proportional to the frequency of the corresponding class.

Frequency Curve:

Year HDI

2001 0.4454

2002 0.4542

2003 0.4630

2004 0.4718

2005 0.4807

2006 0.4860

2007 0.4910

2008 0.4940

A frequency curve is a freehand smoothed curve which is plotted by taking mid points of classes on the horizontal axis and the frequencies along vertical axis for drawing a freehand curve through these mid points. It can also be obtained by joining the mid points of the rectangles of a histogram by means of a smooth curve. The frequency polygon is different from a frequency curve which is obtained by joining the mid points of class intervals with the help of straight liars.

**HISTORIGRAM:**

The graph of time series data is called historigram. To construct a historigram, the horizontal axis is used to plot the date or time increments, and the vertical axis is used to plot the values of the variable that we are measuring.