What Is A Tabular Representation of Statistical Data?
Statistical data usually pertains to an aggregate of numerical data that would eventually contribute to its collection, analysis, and interpretation. The quantification of data helps in research and as well as statistical operations.
In a tabular presentation, data is arranged in columns and rows, and the positioning of data makes comprehension and understanding of data more accessible. Statistical and logical conclusions are derived from its presentation.
Objectives Of Tabular Presentation of Data
The objectives of the tabular presentation of data have been mentioned below.
A tabular presentation helps in the simplification of complex data
It helps in the comparison of different data sets and brings out their essential aspects
Statistical analysis can be undertaken from a tabular presentation
A tabular presentation of data further aids in formations of graphs and diagrams for data analysis
Here Is A Fun Fact!
The concept of numbers mainly originated in the middle east. The counting houses during that point of time used cloth with check prints to count money. Those were spread across a table for purposes of counting. Coins used to be stacked over these checkerboard tables. It is understood to be the point of origin of the modern-day tabular representation of data.
Parts of A Table in The Tabulation
Different parts of a statistical table in its complete form are as under –
Tabular presentation of data example is shown below.
Test Your Knowledge –
1. Where Is A “Headnote” Placed In A Table?
A headnote comprises the main title
It follows the primary title within a small bracket
A headnote can be placed anywhere in the table
2. Which Of The Following is Used for Explanation of Column Figures?
[Refer the solutions to the questions at the end of the article]
Forms of Tabular Analysis
The quantitative tabular analysis provides a description and interpretation of items based on statistics. Such analysis is undertaken through numeric variables as well as statistical methods.
Qualitative analysis is done, taking into account various attributes that are non-numerical. For instance, it may include social status, nationality, and physical specifications, among others. In such classification, the attributes that are taken into consideration cannot be subjected to quantitative measurement.
Categorisation, when done based on location such as a state, country, block, and district, etc., is called spatial analysis.
In this analysis method, time becomes a variable for data analysis. Such consideration of time may be in the form of hours, days, weeks, and months among others.
Limitations of A Tabular Presentation
There are certain drawbacks to a table presentation of data that have been mentioned below.
Lack of Focus on Individual Items
Individual items are not presented distinctly. A tabular presentation shows data in an aggregated manner.
No Scope for Description
It is only the figures that are indicated in a tabular presentation. The attributes of those figures cannot be mentioned in tables. Moreover, the qualitative aspects of figures cannot be mentioned.
Requires Expert Knowledge
A layperson will not be able to decipher the intricacies that are mentioned in the figures within a tabular presentation. Its interpretation and analysis can only be undertaken by a person with the requisite expertise.
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1. What is The Tabular Presentation of Data?
The particular methods of presenting statistical data in a tabular format are called the tabular presentation of data. Data is logically and systematically arranged within columns and rows concerning specific data characteristics. A tabular presentation of data makes for straightforward interpretation and comprehensible data set.
What Are The Objectives of The Tabulation of Data?
There are several objectives behind the tabulation of data. A large amount of data can be easily converted into comprehensible form by way of tabulation. Apart from the convenience in the data arrangement, tabular representation also creates the basis for statistical analysis. Such statistical analysis may include correlation, dispersion, and averages, among others.