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Data Measurement Scales for Likert Scale Variables in Non-Parametric Statistics

The use of variables measured with the Likert scale is certainly familiar to us. This scale is often applied in research involving non-parametric variables.

In statistics, we recognize four types of data measurement scales namely nominal, ordinal, interval, and ratio. However, a common question arises: into which category does a variable measured using the Likert scale fall?

In this article, I will discuss and answer this question in depth. Read this article to the end to gain a comprehensive understanding.

Measurement of Research Variables with the Likert Scale

In research, whether conducted by students or professional researchers, understanding the variables used is very important. To achieve research objectives, we must go through several stages, such as data collection, data tabulation, data analysis, interpretation, and conclusion drawing.

During the data collection stage, we identify and measure the observed variables. Sometimes we need to measure variables that cannot be directly assessed numerically. This is where the Likert scale plays a crucial role.

The Likert scale is used to measure variables whose values cannot be obtained directly. For example, to measure employee motivation, we cannot directly get a numerical value. Therefore, we create an instrument with several statements representing that variable.

Respondents are then asked to respond to these statements by choosing the most appropriate answer. These answer choices are usually in the form of a scale from 1 to 5 or 1 to 4, with examples of options being strongly disagree, disagree, neutral, agree, and strongly agree on a scale of 1 to 5.

After compiling the statement items, we conduct validity and reliability tests to ensure that these items can be relied upon. The results of these tests determine which items are valid and reliable.

In the analysis of validity and reliability, respondents’ answers are converted into scores. Items that are not valid and not reliable are removed from the instrument. Finally, we obtain an instrument ready for field data collection.

What Data Scale Does the Likert Scale Fall Into?

After understanding how to measure variables with the Likert scale, we need to answer what data scale is used. Non-parametric data measurement scales include nominal and ordinal scales.

There is often confusion about whether the converted scores, which are numerical values, are already included in the interval scale. To answer this, it is important to consider how the variable was initially measured.

If variables like employee motivation cannot be directly measured numerically, then clearly, those variables are non-parametric. Non-parametric variables are divided into nominal and ordinal scales. The Likert scale, based on the differences in answer choices that can be distinguished by levels or rankings, falls under the ordinal scale.

In the nominal scale, variables are categorized without levels or rankings, such as gender or job type. Conversely, the ordinal scale categorizes variables with clear distinctions between higher and lower levels, such as educational levels.

Conclusion

Thus, the measurement of variables using the Likert scale falls under the ordinal scale. This means that the data analysis of variables with the Likert scale should use non-parametric statistics. This article is expected to be beneficial and add to our knowledge. For further educational content, visit the Kanda Data YouTube channel. Thank you.

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