MathsCategorical Data

Categorical Data

Explain in Detail :Types of Categorical Data

There are four types of categorical data: nominal, ordinal, interval, and ratio.

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    Nominal data is the simplest type of data, and it is just a list of names or labels. There is no order or rank associated with the data, and there is no meaningful way to compare the values.

    Ordinal data is a little more complex. It still has no order or rank, but at least there is some meaning to the comparisons. For example, you might have a list of survey responses that are coded as “1” for “strongly disagree,” “2” for “disagree,” “3” for “neutral,” “4” for “agree,” and “5” for “strongly agree.” You can’t say that “3” is twice as good as “1,” but you can say that “4” is better than “1.”

    Interval data is even more complex. In addition to having order and rank, it also has a meaningful zero point. This means that you can say that “3” is twice as good as “1,” or that “-2” is twice as bad as “0.”

    Ratio data is the most complex type of data. In addition to all of the features of interval data, it also has a meaningful unit of measurement. This means that you can say that “3” is three times as good as “1,” or that “3” is three

    Categorical Data

    Nominal Data

    Name:

    Gender:

    Age:

    Height:

    Weight:

    Location:

    Nationality:

    Ethnicity:

    Occupation:

    Ordinal Data

    Ordinal data is data that can be put in order. This could be data that is measured on a scale, such as 1-10, or data that is put in order by a researcher.

    Categorical Variables

    A categorical variable is a variable with a finite number of possible values. For example, the sex of a person is a categorical variable with two possible values, male and female.

    The possible values for a categorical variable are usually denoted by the letters A, B, C, etc. For example, the possible values for the sex of a person might be denoted by the letters M, F.

    The values of a categorical variable are usually ordered, with one value being the most common and the other value being the least common. For example, the most common sex of a person is male, while the least common sex of a person is female.

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