# Interval Level of Measurement

JoVE Core
Statistik
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JoVE Core Statistik
Interval Level of Measurement

### Nächstes Video1.7: Ratio Level of Measurement

Data can be divided into four levels of measurement.

The interval level of measurement includes data that can be ordered, and the difference between the values is meaningful.

For example, the temperature in a desert is measured in degrees Celsius and can be ordered from low to high.

The difference between the highest and the lowest values indicates how much the temperature changes in a day.

But, a nighttime temperature of zero degrees Celsius does not mean there is no temperature; on the contrary, it is quite cold. So, the interval level of measurement does not have a natural zero point.

On the contrary, consider a catalog of computer prices. Zero dollars means no cost. So this data set has a natural zero point and cannot be considered for interval level of measurement.

## Interval Level of Measurement

For effective statistical analysis, data are classified into four levels of measurement—nominal, ordinal, interval, and ratio.

Data measured using the interval scale are similar to ordinal level data because they have a definite arrangement. However, in the interval level of measurement, the differences between data values are meaningful even though the data does not have a starting point.

Temperature is measured using the interval scale. It is measurable data, and the difference between the two temperature points is meaningful. Forty degrees equals 100 degrees minus 60 degrees. However, zero degrees does not mean that there is no temperature; it is just cold. Temperatures like −10 °F and −15 °C exist and are colder than zero.

Interval level data can be used in calculations, but the data cannot be compared. For example, 80 °C is not four times as hot as 20 °C (nor is 80 °F four times as hot as 20 °F). There is no meaning to the ratio of values in the interval level of measurement.