Qualitative Data - Why ? What? || Nominal Data || Ordinal Data || Statistics for Beginners

Overview of the importance of studying data types and the different types of data in Statistics such as Qualitative Data and Quantitative Data.

Understanding different data types is crucial for applying appropriate analysis techniques and selecting the best method for each type of data.

The understanding of data types is essential for comprehending algorithms, as certain algorithms are specific to numeric data types while others are suitable for categorical data.

Data in Statistics can be broadly classified into two categories based on the quality of the attributes being measured or observed.

Exploration of qualitative data focusing on qualities that cannot be measured numerically, classified into groups, and known as categorical data.

Detailed discussion on the subtypes of qualitative data, including Nominal Data that cannot be measured numerically and does not involve ranking or ordering.

Features and characteristics of Nominal Data, its categorization into groups, and the inability to assign numerical values to its attributes.

Introduction to Ordinal Data, which cannot be measured numerically but follows a specific order allowing for sorting and comparisons.

Exploration of the properties of Ordinal Data, including the ability to order but lack of meaningful zero and continuity in relative distances between categories.

Discussion on the mathematical operations that can be performed on Ordinal Data, emphasizing the order and hierarchy within this data type.

Summary of the key insights regarding qualitative data types and the hierarchy present in Ordinal Data.