Tag: ordinal scale
Spearman Rank Correlation Analysis | Practical Test on the Relationship Between Education Level and Performance Level
In statistics, correlation tests are frequently used by researchers to examine associations. The purpose of conducting a correlation test is to determine the relationship between two observed variables. However, many people still ask me about one specific correlation test for variables measured on an ordinal scale.
How to Analyze Likert Scale Variables | Non-Parametric Ordinal Scale Variables
Non-parametric variables measured using the Likert scale (ordinal scale) have a slightly different analysis approach compared to parametric variables. This Likert scale approach is often used in social and management research. In such studies, we are often confronted with variables that cannot be directly quantified.
How to Create a Likert Scale Score Category (Ordinal Scale)
Creating Likert scale score categories is essential to answer one of the research objectives, particularly in descriptive statistical analysis. We can categorize non-parametric variables that use the Likert scale into high, medium, and low categories. This information will significantly enrich the research findings.
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.
How to Analyze Correlation between Ratio and Ordinal Scale Variables (Different Measurement Scales)
In correlation analysis, we often use Pearson correlation to test the relationship between variables measured on a ratio/interval scale. Variables measured on a ratio/interval scale have a greater potential to meet the normality assumption for data testing.
How to Analyze Correlation and Interpret for Variables Measured Using the Likert Scale
Researchers can choose correlation analysis to examine the relationship between variables. The selection of correlation analysis techniques depends on the scale of measurement used for the data. In statistics, the data measurement scale of a variable consists of nominal, ordinal, interval, and ratio scales.