Ratio in research refers to a type of variable measurement scale that is quantitative in nature. It is the highest level of measurement in the four levels of measurement, based on the precision involved. Ratio scales allow researchers to categorize and rank data along equal intervals, and they apply to measurements in which there is a true zero value, making it easier to draw comparisons between variables like age, time, weight, and more. Examples of ratio scales include length, money, age, duration, and mass.

Ratio data is characterized by its unique qualities, including an absolute point zero, which is measured on a ratio scale. This means that there can be no negative numerical value in ratio data, and it is possible to say that one object is twice as long as the other or that 4 has twice the value as 2. Ratio data is often used in market research to evaluate concepts like sales numbers, market share, customer data, and pricing.

After collecting ratio data, researchers can use it to gather descriptive and inferential statistics, and almost all statistical tests can be performed on ratio data because all mathematical operations are permissible. Some of the statistical tests that can be used on ratio data include T-tests, ANOVA, SWOT analysis, TURF analysis, and cross-tabs.

In summary, ratio in research refers to a type of variable measurement scale that is quantitative in nature and applies to measurements in which there is a true zero value. Ratio data is characterized by its unique qualities, including an absolute point zero, and is often used in market research to evaluate concepts like sales numbers, market share, customer data, and pricing. Researchers can use ratio data to gather descriptive and inferential statistics and perform various statistical tests.