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What is ordinal data?

Ordinal data is a type of qualitative (non-numeric) data that groups variables into descriptive categories. A distinguishing feature of ordinal data is that the categories it uses are ordered on some kind of hierarchical scale, e.g. high to low. On the levels of measurement, ordinal data comes second in complexity, directly after nominal data.

Can ordinal data be analyzed with descriptive and inferential statistics?

Ordinal data can be analyzed with both descriptive and inferential statistics. You can use these descriptive statistics with ordinal data: the range to indicate the variability. Regular physical exercise is important for my mental health.

What is the difference between ordinal and continuous data?

Ordinal and continuous data (both interval and ratio scale) can rank observations on a scale. In other words, you can record that one observation has more of a characteristic than another observation. However, as discussed earlier, ordinal data can’t describe the degree of difference between values, while a continuous variable can.

What types of data can be recorded at more than one level?

Some types of data can be recorded at more than one level. For example, for the variable of age: You could collect ordinal data by asking participants to select from four age brackets, as in the question above. You could collect ratio data by asking participants for their exact age.

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