A common feature of research is the attempt to have respondents communicate their feelings, attitudes, opinions, and evaluations in some measurable form. What is important for the researchers is to understand measurement properties. Some scales have more extensive mathematical properties and some, hold out the possibility of establishing cause and effect relationships between variables.
Measure is important in research. Measure aims to ascertain the dimension, quantity, or capacity of the behaviors or events that researchers want to explore. Measurement is a process of mapping empirical phenomena with using system of numbers.
Basically, the events or phenomena that researchers interested can be existed as domain. Measurement links the events in domain to events in another space which called range. In another words, researchers can measure certain events in certain range. The range is consisting of scale. Thus, researchers can interpret the data with quantitative conclusion which leads to more accurate and standardized outcomes. Without measure, researchers can't interpret the data accurately and systematically.
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Data and measurement form the backbone of research. There are different scales of measurement including nominal, ordinal, interval, and ratio. There is a direct relationship between types of data, scales of measurement, and the types of statistical analyses wish a researcher chooses for the data analysis. For instance, quantitative data such as raw scores on a given test require a metric or interval scale of measurement, which in turn determines the application of a related parametric statistical technique.
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