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https://math.answers.com/math-and-arithmetic/Can_data_be_non_discrete_and_non_continuous

Can data be non discrete and non continuous? - Answers

Yes, data can be non-discrete and non-continuous, often referred to as categorical or qualitative data. This type of data includes attributes or qualities that cannot be measured on a numerical scale, such as colors, names, or types of animals. Such data can be further divided into nominal (unordered categories) and ordinal (ordered categories) types. These categories do not fit into the traditional discrete or continuous classifications.



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Can data be non discrete and non continuous? - Answers

https://math.answers.com/math-and-arithmetic/Can_data_be_non_discrete_and_non_continuous

Yes, data can be non-discrete and non-continuous, often referred to as categorical or qualitative data. This type of data includes attributes or qualities that cannot be measured on a numerical scale, such as colors, names, or types of animals. Such data can be further divided into nominal (unordered categories) and ordinal (ordered categories) types. These categories do not fit into the traditional discrete or continuous classifications.



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https://math.answers.com/math-and-arithmetic/Can_data_be_non_discrete_and_non_continuous

Can data be non discrete and non continuous? - Answers

Yes, data can be non-discrete and non-continuous, often referred to as categorical or qualitative data. This type of data includes attributes or qualities that cannot be measured on a numerical scale, such as colors, names, or types of animals. Such data can be further divided into nominal (unordered categories) and ordinal (ordered categories) types. These categories do not fit into the traditional discrete or continuous classifications.

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      Yes, data can be non-discrete and non-continuous, often referred to as categorical or qualitative data. This type of data includes attributes or qualities that cannot be measured on a numerical scale, such as colors, names, or types of animals. Such data can be further divided into nominal (unordered categories) and ordinal (ordered categories) types. These categories do not fit into the traditional discrete or continuous classifications.

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