From Ordinal To Ratio Scales And Their Different Applications

Introduction

Quantitative research is a form of research that allows researchers you to get an insight into a certain phenomenon in a quantitative method, rather than a qualitative way. Using quantitative research you can find out what actually happens in a certain situation. For example, if you would want to know whether one product is better than another, among many other factors, quantitative research would be a great way to start.

What Defines The Measurement Scale — The Four Characteristics

Identity – that is a number that is assigned with each entry on the data set, and has no meaning to its actual numerical value. For example, 1 is white, 2 is black, 3 is green, 4 is yellow, etc.

Magnitude – that is a number that represents the order of a certain subset, for example standings in a football league: First, second, third, etc

Equal Intervals – this is for example when a team gets 20 points if they come in first, 15 if they come in second, 10 if they come in third, etc

Absolute zero – that can measure a factor that is outside the scale. For example, in a track race, a car that hasn’t finished the race will be marked as such.

How Likely Is It For You To Use Ordinal Scales?

Ordinal Scale involves the ranking or ordering of the attributes depending on the variable being scaled. For example, if you want to know how satisfied your customers are with your products, a quantitative research would work well, as you can ask them to rate their level of satisfaction between 1 and 5 for instance. That is one of the unique capabilities that a quantitative research holds.

Ordinal scale can hence be used when advertising a product. One can address their viewers and as for an answer that would show the level of attractiveness of a campaign that they are launching. A good question would be: Did you think the advertisement was: Very good, good, neither good nor bad, bad, or very bad.

Ordinal scale can be used in market research, advertising, and customer satisfaction surveys.For that reason, ordinal scales are the right fit for customer service quantitative research.

From 1 to 10 — Understanding Interval Scales

Point 1: This is a scale in which the levels are ordered and each numerically equal distances on the scale have equal interval difference. For example, that would be when the level of satisfaction from a service can be ranked: How good is this service on a scale of 1 to 10. 10 being the best service and 1 being the worst service.

It is used in various sectors like in education, medicine, engineering, etc. Some of these uses include calculating a student’s CGPA, measuring a patient’s temperature, etc.

It is a way of using quantitative research as an extension of the interval scale, therefore satisfying the four characteristics of the measurement scale; identity, magnitude, equal interval, and the absolute zero property. – Give example

Data measurement At Its Peak

Data measurement is a great tool for using quantitative research. It is an extension of the interval scale, therefore satisfying the four characteristics of the measurement scale; identity, magnitude, equal interval, and the absolute zero property.

When it comes to market research, the common ratio scale examples are price, number of customers, competitors, etc. It is extensively used in marketing, advertising, and business sales.

This level of data measurement allows the researcher to compare both the differences and the relative magnitude of numbers. There is no better way to add measurable tools to market research than using qualitative research. That includes questionnaires that include questions like: On a 1 to 10 scale, how likely are you to tell a friend about your recent purchase?