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Measuring is assigning values to the characteristics of people, animals, objects, organizations, situations, or whatever the object of your study is.

Suppose you want to describe a table. Now you can provide information about the height, the size of the surface, the colour and so on. All these aspects are characteristics, and all these aspects get a value. And that is what scientists do all the time (no, not only for tables, but for all objects, subjects, organisations, situations, or whatever is the object of the study).

The purpose of measuring characteristics is to make distinctions between objects. The height of the table can be measured in cm, mm, inches, or words like high, normal, low. Some values are occasionally better in other circumstances. The height of a desk could be measured in cm or inches. But for a side table values like low, rather low, high and rather high are more suitable. It therefore depends on the situation and for which it is to be used, with which values a characteristic must be measured.

The value that each characteristic receives is what we call operationalization. The way the measurement is operationalized yields a different type of data. For example, whether a company makes a profit can be answered with yes or no. In this case it is a dichotomy and the variable of the type is nominal. You can also ask how much profit the company makes. Now you have a variable that is measured at the interval level.

In science, five forms of measurement can be distinguished: observing, interviewing, measuring with instruments, copying from other files and generating data. There is quite a lot to tell about these methods, so for more information about these topics, I suggest to read further on these pages.

Related topics tot Measuring

• Observing
• Interviewing
• Instrumentation (measuring with instruments)
• Transferring data
• Generating data
  
  
• Variable 
  • Nominal data
  • Ordinal data
  • Interval data
  • Ratio data

Use our SPSS tutorials to analyse your data. It will go much faster.

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