I am working on a few algorithms where I have a list of $N$ samples. Currently I have plotted these into a histogram and have a view of how uniform the values are distributed within an interval, which is quite good as a visualization, although I need a comparable value of how uniform the dataset is, in order to measure how robust it is compared to my other algorithms.
I have been looking at chi-squared test, but could not figure out how it would become helpful in my usecase?
Sample from dataset:
8725 462 1492 972 9941 8235 8220 6949 1252
Code for importing data and applying chi-squared in
mydata = read.csv2("/opt/doc/stat/uniform_test_1.csv") x <- sapply(mydata, as.numeric) chisq.test(x)
X-squared = 1664769844, df = 999998, p-value < 2.2e-16