Levels of Measurement
In survey research and data science, one of the most important concepts to understand is levels of measurement. Knowing the different levels of measurement, also known as measurement scales, is essential for any researcher, as it allows them to select and analyze data accurately.
Levels of measurement refer to the nature and quality of the data being collected and analyzed. The levels are nominal, ordinal, interval, and ratio. Each level gives different types of information and has unique characteristics that must be taken into consideration when creating and analyzing data sets.
Nominal Measurement
Nominal measurement is the lowest level of measurement and is used to classify categories which are not ordered and do not provide a clear numerical value. It is often used for data such as gender, race, or religion and is measured through categorical variables.
For instance, say you are conducting a survey to determine the age range of respondents. The nominal level of measurement would be used to classify the data into categories like 18-24, 25-34, 35-44, and so on.
Ordinal Measurement
Ordinal measurement is used to rank categories in terms of order or level. It is often used when measuring attitudes such as preferences, satisfaction, or agreement.
For instance, say you are conducting a survey to determine people’s opinion of a new product. The ordinal level of measurement would be used to classify the data into categories like strongly disagree, disagree, neutral, agree, and strongly agree.
Interval Measurement
Interval measurement is used to quantify values and quantify their spacing. It is often used when measuring respondent opinions on a specific scale.
For example, say you are conducting a survey to determine people’s opinion of a new website. The interval level of measurement would be used to measure the magnitude of their opinion using a scale from one to ten.
Ratio Measurement
Ratio measurement is the highest level of measurement and is used to quantify values and compare them numerically. It is often used when measuring physical characteristics such as length, temperature, and weight.
For instance, say you are conducting a survey to determine the height of respondents. The ratio level of measurement would be used to measure the height in inches or centimeters.
Conclusion
Understanding the different levels of measurement is an essential part of survey research and data science. By understanding the different measurement scales, researchers are able to select and analyze data more accurately and effectively. Nominal, ordinal, interval, and ratio measurement scales all have their own unique characteristics and must be taken into account when gathering and analyzing data sets.
