How is interval data characterized in biostatistics?

Interval data in biostatistics is characterized by having a meaningful numeric value but no true zero. This means that while the differences between values are meaningful and can be measured, the zero point does not denote the absence of the quantity measured. For example, in temperature measured in Celsius, 0 degrees does not mean there is no temperature; rather, it is an arbitrary point in the temperature scale.

This property distinguishes interval data from other data types, such as ratio data, which does have a true zero (for example, a weight of zero means there is no weight). Interval data also has more precision than ordinal data, which only ranks categories without defining the exact quantitative differences between them.

Understanding this distinction is essential for correctly interpreting statistical analyses in research, as it influences the kinds of calculations and inferences that can be made from the data.