{"id":259118,"date":"2024-02-06T10:47:19","date_gmt":"2024-02-06T10:47:19","guid":{"rendered":"https:\/\/imarticus.org\/blog\/?p=259118"},"modified":"2024-07-18T07:25:24","modified_gmt":"2024-07-18T07:25:24","slug":"categorical-data-for-data-analytics","status":"publish","type":"post","link":"https:\/\/imarticus.org\/blog\/categorical-data-for-data-analytics\/","title":{"rendered":"Categorical Data for Data Analytics"},"content":{"rendered":"\n

When conducting research, categorical data is of the utmost importance. Research involves the application of two types of data \u2014 categorical data and numerical data. Categorical data refers to a kind of qualitative data that may be classified into several categories. The data comprises categorical variables that can only be expressed in natural language. While numerals may be used to represent categorical data, there is no mathematical aspect of categorical data. <\/span><\/p>\n\n\n\n

Categorical data generally includes data on birth, hair colour, body weight, height, and other factors relevant to any specific research. A deep understanding of categorical data is crucial to conducting data analysis<\/strong><\/a> in research. <\/span><\/p>\n\n\n\n

If you seek to delve deeper into categorical data, then you may consider pursuing a <\/span>career in data science<\/span>. Enrol in a <\/span>data science certification<\/span> course to gain a deep insight into the nuanced aspects of categorical data for data analytics. Read on to learn more about categorical data to <\/span>become a data analyst<\/span> and conduct in-depth <\/span>data analysis<\/span><\/a> in your research.<\/span><\/p>\n\n\n\n

Categorical Data: Types<\/span><\/h2>\n\n\n\n

Categorical data primarily includes points of observation and values that can be grouped into definite classes based on characteristics. Specifically, categorical data is of two types: nominal and ordinal.<\/span><\/p>\n\n\n\n

Nominal data is a type of categorical data that cannot be ranked hierarchically. While nominal data can be both quantitative and qualitative at times, yet, it cannot be measured or arranged in a ranked order. Symbols, letters, and words are some instances of nominal data. Ordinal data is the type of categorical data that possesses a natural order. Ordinal data is generally used in surveys and questionnaires.<\/span><\/p>\n\n\n\n

A deeper understanding of nominal and ordinal data can be acquired by pursuing a <\/span>Data analytics certification course<\/a><\/strong>.<\/span><\/p>\n\n\n\n

Primary Characteristics of Categorical Data<\/span><\/h2>\n\n\n\n

The key features of categorical data are listed below:<\/span><\/p>\n\n\n\n