When data have errors, standard testing methods can give wrong results. A new test was created to compare two sets of data with errors. This test considers the errors and uses a special statistic based on hidden variables. It works for many situations without strict rules on the data's distribution. The test's accuracy was confirmed through simulations and real data analysis, showing it is better than traditional tests.