This is a type of numerical data which represents measurements-their values are described as intervals on a real number line, rather than take counting numbers. Whether finite or infinite, discrete data take on counting numbers like 1 to 10 or 1 to infinity, with these groups of numbers being countably finite and countably infinite respectively.Ī more practical example of discrete data will be counting the cups of water required to empty a bucket and counting the cups of water required to empty an ocean-the former is finite countable while the latter is infinite countable. It takes on values that can be grouped into a list, where the list may either be finite or infinite. Numerical data can take 2 different forms, namely discrete data, which represents countable items and continuous data, which represents data measurement. The continuous type of numerical data is further sub-divided into interval and ratio data, which is known to be used for measuring items.ĭiscrete Data represents countable items and can take both numerical and categorical forms, depending on usage. Sometimes called quantitative data, numerical data is always collected in number form. Numerical data differentiates itself from other number form data types with its ability to carry out arithmetic operations with these numbers.įor example, numerical data of the number of male students and female students in a class may be taken, then added together to get the total number of students in the class. This characteristic is one of the major ways of identifying numerical data.
Numerical data is a data type expressed in numbers, rather than natural language description. These data types are significantly used for statistical analysis or research purposes. Numerical data as a case study is categorized into discrete and continuous data where continuous data are further grouped into interval and ratio data.
This knowledge is what is used during the research process.
Therefore, researchers need to understand the different data types and their analysis. The different data types are used in separate cases and require different statistical and visualization techniques. When working with statistical data, researchers need to get acquainted with the data types used- categorical and numerical data.
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