A Study on Two Sample Test for Interval-Valued Symbolic Data

Symbolic data appear from various field of applications, such as social sciences, medical, industry and government experiment etc.. Symbolic data analysis treats new concepts that are underlying on the given raw data. It is important of the complex nature of big data. It can be multi-valued data, interval-valued data, histogram-valued data. Classical variables can be transformed into symbolic variables. So, we can reduce the size of the data. In this study, we consider statistical tests of two sample symbolic data, especially on interval-valued variables. It can be easily extended to other symbolic data such as histogram- valued variables. We are interested in two sample statistical tests for interval-valued variables. The first approach could be Kolmogorov-Smirnov (K-S) test for intervals. To construct K-S tests, we define empirical distributions of intervals and then compare proposed tests to classical ones. The p-value of the tests is calculated using permutation techniques with R. Blood pressure data is used as an applications to investigate their properties. We can find that the proposed method is competitive.