I see a lot phrases like "studies show that" these days. Somehow in our science-based, sophisticated society everybody likes to throw studies at each other to prove their own narrative. But I don't understand them. I am not that statistical illiterate, I know the difference of mean, mode and median and stdev (and when to use what). When I dig deeper into one study I'll find hypothesis testing methods like p-values, r^2 and whatever ("our hypothesis was proven because p > 0.9"). But here my knowledge ends. If p>0.9 is that good? or did they just tune the data to get that high p-values? or is the whole method garbage and the study could not get replicated with the same p value? And I want to know how to cheat with statistics, because since these studies are made by people, whom might get paid to prove a certain point (e.g. "My institute gets paid by Mars, hence I'll downplay the effects on health of sugar in daily nutrition and amplify the positives effects of <some chemical found in chocolate>"). or they just want to show significance for their research, because they worked the last 10 years on it and it's "their baby".