Hello folks,

In the previous article we read about different types of statistics coming to more basics let’s discuss about different types of data.

So there are two types of statistics Descriptive and Inferential.

Similarly, Data is divided into two types shown in the visual below.

Types of Data

In the above visual Data is divided as Numerical and Categorical and Numerical is further divides as Discrete and Continuous

Numerical Data:

Numerical data has meaning which has certain measurement. For example person’s height, weight, student’s marks, blood group or they are count as the numbers for example number of properties a person owns.

Discrete data represents items that can be counted, they have certain possible values that can be listed. The values can either be finite or infinite. For example: Number of children in school, number of books in library, etc.

Continuous data represents measurements and they cannot be counted they are measured using range or intervals on the number line. For example under 18 people staying in Mumbai.

Categorical Data:

Categorical Data contains information about a category. Categorical data represents certain characteristics. Lets take an example, gender of person either male or female, marital status either single or married, Yes or No, types of movies, etc.

Also note that categorical values can take on numerical values (such as male is denoted by “1” and female is denoted by “0”) but these numbers does not have any mathematical meaning.

Level of Measurements

Level of measurement also known as scale of measure is types that give information and describes the nature of data with the particular values that are assigned to a variable.

By observing the above visual we have 4 different types of Level of measurement.

1. Nominal
2. Ordinal
3. Interval
4. Ratio

Nominal Data

Nominal Data also knows as Qualitative / Categorical data. It us used for labelling different types of classification and does not have a particular quantitative value of order.

For example: Where do you leave? Options are 1- Village     2- City     3- Town

Similarly, What is your gender? Options are 1- Male    2- Female

Nominal scale of measurement are mostly used in research surveys and Questionnaires where only variable label has certain significance. It  is the most fundamental level of measurement.

There can be two ways through which this type of data can be collected either by open ended question to which answers are coded by a label decided by researcher.

The alternative method is to include MCQ’s in which answers will be labelled.

Ordinal Data

Ordinal Scale is defined as a variable measurement scale used for rank of variables but difference between or distance between each variable does not matter.

They are mostly used to convey non-mathematical ideas satisfaction, degree of main, happiness, etc.

Here rank is important but degree does not matter.

Let’s take an example of race, in a race a person can come 1st, 2nd, 3rd, 4th … and so on here irrespective of distance person who comes first is first.

Another example grading system where we get ranks i.e. rank 1, rank 2, rank 3. If you get highest marks you are going to be the topper. If a person who is second is 5 Marks below then so he/she is going to be 2nd only.

Interval Data

Interval Scale is defined as a variable measurement scale use for rank of variables on basis of difference or distance. Here both rank and distance has importance.

For example, rank based on percentage, week days i.e. there are fixed set of intervals after every 24 hours. Another similar example is class periods here there are fixed set of time for all classes for 30 min each period.

Ratio Data

It is a variable measurement scale that not only produces the order of variable but also makes the difference between the known variable along with information about the value of true zero.

For example: What is your weight in Kg?

Options can be Less than 50 kg, 51 – 70 kg, 71 – 90 kg, 91 – 110 kg or more than 110 kg.