NOMINAL, ORNIDAL, INTERVAL AND RATIO Calender year is an example of

The scale of measurement are NOMINAL, ORNIDAL, INTERVAL AND RATIO.
Solution :
Nominal :
A nominal level of measurement deals strictly with qualitative data assigned to predetermined categories.
One example is the gender of a survey respondent, with the categories being male and female.
This type of data is referred to as nominal data, or categorical data.
Nominal data are considered the lowest level of data, and, as a result, the statistical techniques used to analyze them are the most restrictive.
Ordinal :
Ordinal data have all the properties of nominal data, with the added feature that we can rank-order the values from highest to lowest.
A property of ordinal data is that the differences between categories are not meaningful and, therefore, cannot be measured. Ordinal data can also be numerical.
One example of numerical ordinal data is when we rate movies with one, two, three, or four stars.
Qualitative : interval and Ratio
interval :
Interval data, which are strictly quantitative, allow us to measure the differences between the categories with actual numbers in a meaningful way.
The interval measurement level is a higher level of measurement. It measures interval data, which are strictly quantitative.
Temperature measurements in degrees Fahrenheit are an example of interval data.
Ratio :
Ratio data have all the features of interval data, with the added benefit of having a true zero point.
The most versatile of data types is the ratio level of measurement. Ratio data are as good as it gets as far as data are concerned.
Examples of this type of data are ages, weights, prices, and salaries.
Therefore
Calender year is an example of Interval scale of measurement.