 # Quick Answer: Can Ordinal Data Be Continuous?

## Is Likert scale ordinal or interval data?

The Likert scale is widely used in social work research, and is commonly constructed with four to seven points.

It is usually treated as an interval scale, but strictly speaking it is an ordinal scale, where arithmetic operations cannot be conducted..

## Is age nominal or ordinal?

Age can be both nominal and ordinal data depending on the question types. I.e “How old are you” is a used to collect nominal data while “Are you the first born or What position are you in your family” is used to collect ordinal data. Age becomes ordinal data when there’s some sort of order to it.

## Is eye color nominal or ordinal?

Certainly, eye color is a nominal variable, since it is multi-valued (blue, green, brown, grey, pink, black), and there is no clear scale on which to fit the different values.

## Is gender nominal ordinal interval or ratio?

There are four basic levels: nominal, ordinal, interval, and ratio. A variable measured on a “nominal” scale is a variable that does not really have any evaluative distinction. One value is really not any greater than another. A good example of a nominal variable is sex (or gender).

## Can ordinal data be treated as interval data?

All ordinal data is not the same. There is a continuum of “ordinality” if you like. … Then there are other instances of ordinal data for which it is reasonable to treat it as interval data and calculate the mean and median. It might even be supportable to use it in a correlation or regression.

## Can you average ordinal data?

Using the mean of ordinal data is fine; just be careful not to make interval or ratio statements about your data — even researchers who take a more relaxed view of averaging ordinal data would disagree with that practice.

## Is ordinal data continuous or discrete?

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. Continuous variables grouped into small number of categories, e.g., income grouped into subsets, blood pressure levels (normal, high-normal etc)

## Is Likert scale ordinal or scale in SPSS?

Various statistical models have been developed and are currently headed under the Item Response Theory framework. The simple answer is that Likert scales are always ordinal. The intervals between positions on the scale are monotonic but never so well-defined as to be numerically uniform increments.

## Is gender ordinal or nominal?

There are two types of categorical variable, nominal and ordinal. A nominal variable has no intrinsic ordering to its categories. For example, gender is a categorical variable having two categories (male and female) with no intrinsic ordering to the categories. An ordinal variable has a clear ordering.

## Is gender an ordinal scale?

For example, a person’s gender, ethnicity, hair color etc. are considered to be data for a nominal scale. … Here, the data collected will be on an ordinal scale as there is a rank associated with each of the answer options, i.e. 2 is lower than 4 and 4 is lower than 5.

## Is categorical data ordinal?

An ordinal variable is similar to a categorical variable. The difference between the two is that there is a clear ordering of the categories. … Even though we can order these from lowest to highest, the spacing between the values may not be the same across the levels of the variables.

## How do you test ordinal data?

In lieu of testing differences in means with t-tests, differences in distributions of ordinal data from two independent samples can be tested with Mann-Whitney, runs, Smirnov, and signed-ranks tests. Test for two related or matched samples include the sign test and the Wilcoxon signed ranks test.

## Is ordinal data qualitative or quantitative?

Data at the ordinal level of measurement are quantitative or qualitative. They can be arranged in order (ranked), but differences between entries are not meaningful. Data at the interval level of measurement are quantitative. They can be ordered, and meaningful differences between data entries can be calculated.

## Is weight nominal or ordinal?

When working with ratio variables, but not interval variables, the ratio of two measurements has a meaningful interpretation. For example, because weight is a ratio variable, a weight of 4 grams is twice as heavy as a weight of 2 grams.

## Are years ordinal?

Time is (usually) a continuous interval variable, so quantitative. … So year is a discretized measure of a continuous interval variable, so quantitative. Year can also be an ordinal variable. For example, you might have data on the top marginal income tax rate per year.