The chi-square goodness-of-fit statistical test allows us to test whether the observed data of a dice is different from the expected distribution of a fair dice. The null hypothesis is that the dice is a fair dice (or in other words, follows the expected distribution). If the p-value is less than 0.05, then you can reject the null hypothesis and conclude that the dice is not fair. You need to enter the expected counts for a fair dice and the observed counts of the real dice. Non-integer expected counts are allowed. However, make sure the total expected count is the same as the total observed count.
Note: Other recommendations: 1) there should be no expected frequencies less than 1; 2) no more than 20% of your expected frequencies are less than 5.
Preacher, K. J. (2001, April). Calculation for the chi-square test: An interactive calculation tool for chi-square tests of goodness of fit and independence [Computer software]. Available from http://quantpsy.org.