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Scientific market research studies require careful measurements, using well-chosen instruments. This is where scales come in.
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A scale is a measurement tool used to grade a variable in terms of its magnitude or quality.
A variable is any characteristic (which is being observed or measured) whose value can change.
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How do we study phenomena using variables? Researchers studying any phenomena attempt to explain the causes & relations driving them by using variables. Variables are used to capture any repeatable patterns that show up when observing such phenomena. Researchers segregate variables into dependent & independent variables. This can be for market research as well as social/customer research. Then they attempt to run controlled experiments by varying only the independent variable to test their hypothesis about how those variables are related to the dependent variables.
There are four different scales of measurement. This means that the data gathered or observed can fall under one of the four scales. The four types of scales are:
Nominal, Ordinal, Interval & Ratio refer to the four scales of measurement used to define variables or numbers in statistics
A nominal scale uses numbers to classify & assign objects or items to categories (numbers such as 1 or 2 are used as labels). Numbers do not mean that one item is better or worse than the other; they are simply being used for classification.
For example in the case of gender, an individual may either be male or female. If we assign the number 1 to male & 2 to female, the numbers only function as tags to mark individuals as falling in either category 1 or 2. The categories cannot be ordered or ranked as better or worse than the other. They serve only a descriptive function.
In others words, the nominal scale is only qualitative in nature & not quantitative. The scale only indicates the presence or absence of a particular quality.
Examples – Nationality, literacy, gender, marital status etc
Ordinal Scale – refers to the second level of measurement as items falling on the scale are not just described but also ranked in an ‘order’. The scale captures the magnitude of a variable relative to others.
For example Ranks of athletes in a race – 1st, 2nd & 3rd capture that the first was faster than the second who was in turn faster than the third.
However, the scale does not indicate the interval properties. For example In the above case, The ranking of athletes does not capture their lap timings or the difference in their timings.
Therefore, it fails to indicate how much quicker the winner of the race is than the person assigned the rank 2. Numbers in the ordinal scale represent the rank order but do not convey any info regarding the amount of quantity or degree of quality.
An interval Scale refers to the third of measurement where numbers form a continuum and the difference between them is meaningful, but the scale lacks a true zero. The difference between any two numbers that are side by side is the same & known. If a zero is used, it is chosen arbitrarily for reference’s sake. Lack of a true zero means that the zero here does not denote the complete absence of the property being measured.
For eg. Temperature scales such as those in degree Fahrenheit & Celsius represent interval scales. They lack a true zero as 0 °F and 0 °C do not indicate an absence of temperature.
Ratio Scale refers to the fourth level of measurement where numbers have all the properties of interval Scale as well as a true zero. True zero means refers to a complete absence of the characteristic being measured. This makes it an effective tool in market research software.
For eg. Height & weight. A score of 0 in either means a complete absence of height or weight. A beam 6 feet tall is two-thirds as tall as a 9 feet tall one. Similarly, a rod weighing 20kg is half as heavy as one weighing 40 kg.