Say I am performing a hypothetical measurement study of the time taken by different computers to finish a specific task eg. download a list of web pages $w \in W$ and store the results of each page load in an array $T$. Using the results obtained so far, I make a prediction that by changing some parameter like the file chunk size the download times can be reduced to $P$ which is a list of floating point values corresponding to the expected download time. At a later time, by actually performing an experiment to validate the hypothesis of file chunk size improving download time I obtain the actual times $A$.
Is a t-Test (
scipy.stats.ttest_ind(P, A, equal_var=True)) the correct way to check and conclude that the predictions made in $P$ were accurate and reliable? Are there other statistical tests which I could use here to indicate the accuracy of the predictions compared to the experimental results?