How To Identify A Data Set Level Of Measurement

What is Level of Measurement?

In statistics, level of measurement is a classification that relates the values that are assigned to variables with each other. In other words, level of measurement is used to describe data within the values. Psychologist Stanley Smith is known for developing four levels of measurement: nominal, ordinal, interval, and ratio.

Level of Measurement

Four Measurement Levels

The four measurement levels, in order, from the lowest level of information to the highest level of information are every bit follows:

1. Nominal scales

Nominal scales comprise the least amount of data. In nominal scales, the numbers assigned to each variable or observation are only used to classify the variable or observation. For example, a fund manager may cull to assign the number 1 to small-scale-cap stocks Pocket-sized Cap Stock A small cap stock is a stock of a publicly traded company whose market capitalization ranges from $300 1000000 to approximately $2 billion. , the number 2 to corporate bonds, the number 3 to derivatives Derivatives Derivatives are fiscal contracts whose value is linked to the value of an underlying nugget. They are circuitous financial instruments that are , so on.

ii. Ordinal scales

Ordinal scales present more information than nominal scales and are, therefore, a higher level of measurement. In ordinal scales, there is an ordered relationship between the variable'southward observations. For example, a list of 500 managers of mutual funds Mutual Funds A mutual fund is a pool of money collected from many investors for the purpose of investing in stocks, bonds, or other securities. Mutual funds are owned by a grouping of investors and managed by professionals. Acquire about the various types of fund, how they work, and benefits and tradeoffs of investing in them may exist ranked by assigning the number 1 to the all-time-performing manager, the number 2 to the 2d best-performing manager, and then on.

With this type of measurement, one tin can conclude that the number 1-ranked mutual fund manager performed improve than the number 2-ranked mutual fund manager.

3. Interval scales

Interval scales present more than data than ordinal scales in that they provide assurance that the differences between values are equal. In other words, interval scales are ordinal scales but with equivalent scale values from low to high intervals.

For instance, temperature measurement is an example of an interval calibration: sixty°C is colder than 65°C, and the temperature difference is the same as the difference between 50°C and 55°C. In other words, the deviation of five°C in both intervals shares the same interpretation and pregnant.

Consider why the ordinal calibration example is not an interval scale: A fund manager ranked i probably did not outperform the fund manager ranked 2 by the exact aforementioned corporeality that a fund managing director ranked half-dozen outperformed a fund managing director ranked seven. Ordinal scales provide a relative ranking, but there is no assurance that the differences between the scale values are the aforementioned.

A drawback in interval scales is that they do not take a true zero signal. Zilch does not stand for an absence of something in an interval scale. Consider that the temperature -0°C does not represent the absenteeism of temperature. For this reason, interval-scale-based ratios neglect to provide some insights – for case, fifty°C is non twice as hot equally 25°C.

four. Ratio scales

Ratio scales are the most informative scales. Ratio scales provide rankings, clinch equal differences betwixt calibration values, and have a true zero bespeak. In essence, a ratio scale can exist thought of every bit nominal, ordinal, and interval scales combined as one.

For instance, the measurement of money is an example of a ratio scale. An individual with $0 has an absence of money. With a true zippo point, information technology would exist correct to say that someone with $100 has twice as much money as someone with $50.

More than Resources

Thank you for reading CFI's guide on Level of Measurement. To keep learning and developing your noesis of business organization intelligence, we highly recommend the additional CFI resources below:

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