# What is Data: 2 types of data and their general understanding

#### What is Data

Data are basically units of information that are usually numeric. Technically it is a set of values of qualitative or quantitative variables of a person(s)/subject(s) usually collected by observation.

Data is raw, unorganized which needs to be processed, organized, structured and to be presented in a given context to make it useful to be called as information.

Data could be primary or secondary depending on source of origination.

In a high level categorization we can bifurcate data as Qualitative and Quantitative

What is Qualitative data type

Qualitative data type are mostly in categorical form is non numerical and is available in textual and non descriptive form like rating “very satisfied”, “Yes/No”, “Male/Female”, “Observation/review of a program” etc.

Qualitative data can be further bifurcated as Nominal scale data and Ordinal scale data. Both data type is non parametric but what differentiates them is the fact that ordinal data is placed into some kind of order by their position.

Let us understand it by an example of reviewing movie by scaling it Very Good, Good, Average, Bad and very Bad. All these observations are nominal data when considering individually. But when placed on a scale and arranged in a given order, they are regarded as ordinal data.

What is Quantitative data type

Quantitative data type are numerical data that can be measured. Like height, weight, distance etc.

We can divide Quantitative data into two parts: Discrete and continuous.

Discrete data represents data which is an integers number, can be counted and can’t be divide further. Like # of fruits,# of wins, #number of eggs. Here each value is different and separate.

Continuous data represents data that can be broken into infinite units usually within a range. Like weight, height or temperature. It is a scale of measurement that can consist of numbers other than whole numbers like decimals and fractions.

Continuous data can be further bifurcated as ratio and interval.

Interval scale are numeric scales in which we know order and exact difference between the values. Like age interval 0-10 years,10-20 year,20-30 years and so on. Here we know there is difference of 10 between every interval 10-20 years is greater than 0-10 year. It is very used in normal data analysis to summarize the data and make it visualize in a compact way.

Ratio scale are numeric scale and has all property of Interval scale with just one difference that 0(zero) has meaningful here. Like Height can be zero or temperature can be zero.