I have a dataset containing the selling price of mineral stones that were sold in five different countries (namely Germany, France, Italy, Belgium and Spain). I am running multiple t-tests check if average selling prices in the selected countries significantly different from each other (i.e. Null hypotheses are: average price Germany= average price of France; average price Italy = average price Belgium; average price France= average price Spain etc.).
I know that running multiple t-tests increases the chances of committing a Type I error and I have found that the Bonferroni correction can be used to protect from Type I error. The question is, should I use it in this case?