A classification that relates the values that are assigned to variables with each other Show 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 information within the values. Psychologist Stanley Smith is known for developing four levels of measurement: nominal, ordinal, interval, and ratio. Four Measurement LevelsThe four measurement levels, in order, from the lowest level of information to the highest level of information are as follows: 1. Nominal scalesNominal scales contain the least amount of information. 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 choose to assign the number 1 to small-cap stocks, the number 2 to corporate bonds, the number 3 to derivatives, and so on. 2. Ordinal scalesOrdinal 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’s observations. For example, a list of 500 managers of mutual funds may be ranked by assigning the number 1 to the best-performing manager, the number 2 to the second best-performing manager, and so on. With this type of measurement, one can conclude that the number 1-ranked mutual fund manager performed better than the number 2-ranked mutual fund manager. 3. Interval scalesInterval scales present more information 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 example, temperature measurement is an example of an interval scale: 60°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 difference of 5°C in both intervals shares the same interpretation and meaning. Consider why the ordinal scale example is not an interval scale: A fund manager ranked 1 probably did not outperform the fund manager ranked 2 by the exact same amount that a fund manager ranked 6 outperformed a fund manager ranked 7. Ordinal scales provide a relative ranking, but there is no assurance that the differences between the scale values are the same. A drawback in interval scales is that they do not have a true zero point. Zero does not represent an absence of something in an interval scale. Consider that the temperature -0°C does not represent the absence of temperature. For this reason, interval-scale-based ratios fail to provide some insights – for example, 50°C is not twice as hot as 25°C. 4. Ratio scalesRatio scales are the most informative scales. Ratio scales provide rankings, assure equal differences between scale values, and have a true zero point. In essence, a ratio scale can be thought of as nominal, ordinal, and interval scales combined as one. For example, the measurement of money is an example of a ratio scale. An individual with $0 has an absence of money. With a true zero point, it would be correct to say that someone with $100 has twice as much money as someone with $50. More ResourcesThank you for reading CFI’s guide on Level of Measurement. To keep learning and developing your knowledge of business intelligence, we highly recommend the additional CFI resources below:
Lecture 1 Discrete and continuous variables Levels of measurement Nominal Ordinal Interval Ratio One can think of nominal, ordinal, interval, and ratio as being ranked in their relation to one another. Ratio is more sophisticated than interval, interval is more sophisticated than ordinal, and ordinal is more sophisticated than nominal. I don't know if the ranks are equidistant or not, probably not. So what kind of measurement level is this ranking of measurement levels?? I'd say ordinal. In statistics, it's best to be a little conservative when in doubt. Two General Classes of Variables (Who Cares?) Ordinal scales with few categories (2,3, or possibly 4) and nominal measures are often classified as categorical and are analyzed using binomial class of statistical tests, whereas ordinal scales with many categories (5 or more), interval, and ratio, are usually analyzed with the normal theory class of statistical tests.� Although the distinction is a somewhat fuzzy one, it is often a very useful distinction for choosing the correct statistical test.� There are a number of special statistics that have been developed to deal with ordinal variables with just a few possible values, but we are not going to cover them in this class (see Agresti, 1984, 1990; O�Connell, 2006; Wickens, 1989 for more information on analysis of ordinal variables). General Classes of Statistics (Oh, I Guess I Do Care)
Survey Questions and Measures: Some Common Examples Yes/No Questions Likert Scales Physical Measures Counts What scale of measurement has the most information?Ratio scales are the most informative scales. Ratio scales provide rankings, assure equal differences between scale values, and have a true zero point. In essence, a ratio scale can be thought of as nominal, ordinal, and interval scales combined as one.
What is nominal and ordinal scale?Nominal scale is a naming scale, where variables are simply “named” or labeled, with no specific order. Ordinal scale has all its variables in a specific order, beyond just naming them. Interval scale offers labels, order, as well as, a specific interval between each of its variable options.
What are the 4 types of measurement scales?Each of the four scales (i.e., nominal, ordinal, interval, and ratio) provides a different type of information. Measurement refers to the assignment of numbers in a meaningful way, and understanding measurement scales is important to interpreting the numbers assigned to people, objects, and events.
Why is the ratio scale most powerful?A ratio scale of measurement is considered to be the most powerful of the four measurement scales because it has an absolute zero rather than an arbitrary origin. Hence, it encompasses all the properties of the other three measurement scales.
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