Easy read on Data Types in Statistics in just 2 mins

Learn about Data Types in Statistics

In general, data types in statistics are a group of individual data points. Statistics consists of two main types of Data.

  1. Categorical Data Types
  2. Numerical Data Types

In this section, we will be discussing each of the Data Types with the example from Cricket since I watch cricket the most and its kinds of intriguing for me. We will explain in detail below about each of the data types

Categorical Data:

Categorical data is a data type stored as groups or categories with the help of names or labels. There are two types of Categorical Data Type

Nominal: Datatypes with no proper order

Ordinal: Datatypes with proper order

Numerical Data:

Numerical data is a data type that represents values that are measured and put into a logical order. There are two types of Numerical Data Type

Discrete: Discrete Data types are the ones that take only certain values. Discrete Data Types cannot be measured but it can be counted

Continuous: Continuous Data types are the ones that are measured and hence it cannot be counted.

Data Types in Statistics
Data Types in Statistics

Examples of each Data Type:

Categorical – Nominal Data Type:

Which team does “Virat Kohli” play?

{India, Pakistan, Bangladesh, Sri Lanka}

Data inside the parenthesis is called Sample Space

Categorical – Ordinal Data Type:

Which position does “Virat Kohli” bat?

{1 down, 2 down, 3 down, 4 down}

Numerical – Discrete Data Type:

How many runs did “Virat Kohli” score in World Cup?

{150, 250, 350, 450}

Numerical – Continuous Data Type:

What is the height of “Virat Kohli”?

{5.5, 5.6, 5.7, 5.8}

Now that you have learnt the data types of basics in statistics we will discuss Distribution, Sampling & Estimation, Hypothesis Testing and P values in statistics. If you’re looking to enrol for Data Analytics Course, check the R Programming course from our institute. Also, read about the Installation of SAS University Edition.

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