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'Age' and 'income' are continuous numeric variables, 'age group' is an ordinal qualitative variable, and 'sex' is a nominal qualitative variable.
'Age' and 'income' are continuous numeric variables, 'age group' is an ordinal qualitative variable, and 'sex' is a nominal qualitative variable.
Age, if measured in years, is a good example; each increment is one year. Typically, with interval or continuous variables, there are a relatively large number of values. Categorical variables have a limited number of values. Gender is an example of a category variable.
A great example of this is a variable like age. Age is, technically, continuous and ratio. A person's age does, after all, have a meaningful zero point (birth) and is continuous if you measure it precisely enough. It is meaningful to say that someone (or something) is 7.28-year-old.
Ordinal scale of measurement section 3.2.2, pp. 64-65. Different values of variables that have an ordinal scale of measurement can be ranked or ordered with respect to each other. This is a higher or stronger level of measurement than measurement at no more than the nominal level.
Ordinal variables have two are more categories that can be ordered or ranked. ... For example, an age variable measured continuously could have a value of 23.487 years oldie you wanted to get that specific! A continuous variable is considered ratio if it has a meaningful zero point (i.e., as in age or distance).
Age, if measured in years, is a good example; each increment is one year. Typically, with interval or continuous variables, there are a relatively large number of values. Categorical variables have a limited number of values. Gender is an example of a category variable.
An Example: Age is, technically, continuous and ratio. A person's age does, after all, have a meaningful zero point (birth) and is continuous if you measure it precisely enough. It is meaningful to say that someone (or something) is 7.28-year-old.
Ordinal scale is the 2nd level of measurement that reports the ranking and ordering of the data without actually establishing the degree of variation between them. Ordinal level of measurement is the second of the four measurement scales. Ordinal indicates order.
Discretely measured responses can be: Nominal (unordered) variables, e.g., gender, ethnic background, religious or political affiliation. Ordinal (ordered) variables, e.g., grade levels, income levels, school grades. Discrete interval variables with only a few values, e.g., number of times married.
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