Ordinal Data
Ordinal data is a type of categorical data that has a natural order or ranking between the categories. In other words, the categories can be ordered or ranked based on some criteria, but the differences between the categories are not necessarily equal. Ordinal data is commonly used in surveys and questionnaires to measure attitudes, opinions, and preferences. In data science, ordinal data is often transformed into numerical values to be used in statistical analysis. One common method is to assign a numerical value to each category based on its position in the ranking. For example, if the categories are 'strongly disagree', 'disagree', 'neutral', 'agree', and 'strongly agree', they can be assigned values of 1, 2, 3, 4, and 5, respectively. Another method is to use dummy variables to represent each category as a binary variable. Ordinal data analysis techniques include non-parametric tests such as the Wilcoxon rank-sum test and the Kruskal-Wallis test.
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