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A statistician has recorded the series of years in which a team has won the title in baseball.

The scale of measurement determines the appropriate categorization and usage of data values as per the need for good statistical analysis.

Nominal:When unordered data is present in the form of descriptive labels for a particular category, a nominal scale is used. For example, modes of payment can be categorized as (1) for cash, (2) for debit card, and (3) for credit card payment.

Ordinal: When ordered data is present in the form of descriptive labels, an ordinal scale is used. The exact variation between any two values is not measurable. For example, the rankings of dishes served at a restaurant.

Interval: An interval scale is used when data is quantitative (countable or measurable), and differences are valid. The existence of a zero value has no significance. For example, air quality is measured in the range of 0 to 500. A zero level does not indicate a zero pollutant level.

Ratio: Quantitative data has a well-defined zero value and can be partitioned. For example, a person's weight (in kilograms) can be halved, and zero kilogram stands for no weight.

A true zero value for a series of years has no significance, and cannot be halved/doubled. Thus, the most appropriate level of measurement will be the interval level of measurement.