Statistics – Data and Type of Data Sources

We have gone through the introduction of statistics in our previous blogs.In this blog, we will learn about the types of data and data sources that are used to generate this statistics.

Data is broadly classified into two main parts :-

• Quantitative Data
• Qualitative Data

Quantitative data are the data that can quantified in definite units of measurements .The Quantitative data are further divided into two more categories :

• Continuous Data
• Discrete Data

Continuous data can take any values on the line segment It can include data like height , weight , Temperature etc. The continuous data can have the highest degree of precision. They can be represented on a number line .

Discrete  are the one whose outcome is measured in fixed numbers . For example :- No of Student in the class, How many matches played by Virat Kohli .

As per wiki , Qualitative data is a categorical measurement expressed not in terms of numbers, but rather by means of a natural language description. In statistics, it is often used interchangeably with "categorical" data.

Example :- Favorite Color = ‘Blue’

Height = ‘Tall’

Qualitative data are further divided into two parts :-

• Nominal Data
• Ordinal Data

Nominal data can be simply be called “labels.”.Nominal data simply names something without assigning it to an order in relation to other numbered objects or pieces of data. An example of nominal data might be a "pass" or "fail" , Male or Female etc.

Ordinal data, unlike nominal data, involves some order; ordinal numbers stand in relation to each other in a ranked fashion. Example :- How do you feel today ? Very happy , happy ,ok , Unhappy , Very Unhappy . Here , we know that happy is better than Inhappy but we can not quantify it , like how much is the difference .

Data Sources are of two types :-

Primary Data :- Those data which do not already exist in any form,and thus

have to be collected for the first time from the primary source(s). Example :- Collecting the data for the census.

Secondary Data :- 

Such data are already exist in some form .Example :- Using the Census data to find how many women are employed in India .