Jun 2, 20224 min read

Data Classification and Presentation

Updated: Jun 18, 2022

Drawing conclusion from raw data is very difficult technically, which is also called ungrouped data. Through statistics the data can be grouped in many meaningful ways. Data presentation in frequency distribution is known as grouped data.

Once the data is grouped, it becomes easier to pick out the patterns and to draw the logical conclusion out of it.

In simple words frequency distribution is a tabular summary, grouping the frequencies of observations in each of the several non – overlapping classes.

Classification is a process of arranging the data according to some common characteristic possessed by the facts constituting the data. The facts having a common characteristic are termed as one class or group. Thus classification is the grouping of the related facts into different classes.

Purpose of Classification

To condense the mass of data in such a manner that similarities and dissimilarities are readily apprehended and relationship studied.
To facilitate comparison.
To have a bird’s eye view of the significant features of the data.
To enlighten the important information while giving less prominence to insignificant items.
To utilize the data for tabulation and further statistical analysis.
To eliminate unnecessary details contained in raw data.
To present the complex, scattered data in a concise, logical and understandable form.

Essentials of Good Classification

Classification is done in such a way so that entire data is covered and not even a single item is left unclassified.
Item of the data should belong only to one class by avoiding overlapping.
It should facilitate comparison
Class interval should be of equal length.
Should confirm to the objects of investigation.
It should be flexible.
Items constituting in a group should be homogeneous

Kinds of Classification

Quantitative Classification

If the data is classified on the basis of some quantitative information the classification is known as quantitative

Example

Chronological Classification

When the data is classified on the basis of time it is known as chronological classification. The data is also known as time series data.

Example

Geographical Classification

When data is classified on the basis of geographical information, it is known as geographical classification.

Example

Qualitative Classification

If the data are classified on the basis of some attributes or quality (descriptive characteristics) such as sex, literacy, beauty, honesty, intelligence, religion, education, colour of hair etc. The classification is called qualitative classification. “In this type of classification, the attribute under study cannot be measured but its presence or absence can be found or felt”. This type of classification is called Simple or Dichotomous or Two-fold classification.

Two Fold Classification

Tabulation

Frequency Distribution

A frequency distribution is any device such as a graph or table that displays the values that the variable can assume along with the frequency of occurrence of these values either individually or as they are grouped into a set of mutually exclusive and exhaustive intervals

“Frequency distribution is a method of organizing the raw and unorganized data”

Following are the three steps by which the data can be organized:

Step 1: To find the range of given data

Step 2: To get the number of class – intervals

Step 3: To determine the width of the class

Class Intervals

Class intervals are contiguous non-overlapping intervals selected in such a way that they are mutually exclusive and exhaustive

Formation of Frequency Table

The number of times a value occurs in a series is called the frequency of that value and the arrangement obtained by mentioning the frequency against each value in the series is called frequency distribution.

The frequency distributions can be divided into two categories:

a. Discrete Frequency Distribution

b. Continuous Frequency Distribution

Discrete Frequency Distribution

In this distribution the variable under study is listed as discrete number and the frequencies are marked against the particular value depending on times of occurrence.

Table 1.0 - Discrete Frequency Distribution

(Number of cars sold)

Grouped or Continuous Frequency Distribution

In this, the various items of a series are classified into groups or classes. The lowest and highest values that can be included in a class or group are called class limits. The lowest value is known as lower limit and the highest value is known as the upper limit.
The width of the class is known as class interval, the number of items falling within the range of the class interval is called the frequency of that class.

Open and Closed Ended Classes

An open end or undetermined class is a class in which either the lower limit or the upper limit is missing. In general it is applied to more than or less than type classification.
However in practice they are generally avoided because open end classes make it difficult to calculate certain statistical measure like arithmetic mean.

For Example:

Exclusive and Inclusive Classes

In exclusive classes the upper limit of the class is excluded from the particular class and in Inclusive class distribution the upper limit of the classes is included in the particular class.

Example: Exclusive Class Interval

Example: Inclusive Class Interval

As far as possible the inclusive class intervals shall be avoided as it becomes very difficult for respondents to understand at times. Every Inclusive type can be converted in to exclusive type as;

Find the difference between the upper limit of any class and the lower limit of the next class.
Divide the difference found in step 1 by 2.
Subtract the fraction obtained in step 2 from the lower limit of all the classes and add the same fraction to the upper limit of all the classes.

Converting Inclusive Interval in Exclusive

In the previous example the difference between the upper limit of the first class and the lower limit of the second class is 10 – 9 =1. Half of this difference is ½ = 0.5. Hence the previous data can be modified as;

Determination of Number of Classes

Sturge’s has given a formula to determine the number of classes:

Where; K represents the number of classes and N as number of observations.

Determination of Magnitude of Class Intervals

The magnitude of the class interval is given by;

Where; Range=Maximum Value -Minimum Value

Charts and Graphs

Pie Chart

Pie chart is used to show the proportion. A Pie chart shall contain data in percentage only. A complete pie chart represents 100% of the data. More effective for 2 to 4 category proportions