I'm a statistician, and when I wrote my own book about bad statistics in science (see https://www.statisticsdonewrong.com/), I made sure to reference studies which quantify how often errors occur in real published research. The rate is stunningly high. The average biomedical experiment is conducted with (a) a sample size which is far too small to detect an effect of the expected size, (b) a vague analysis plan which leads to exploratory analyses with high false positive rates, (c) frequent copy-and-paste errors and math mistakes in presenting important results, and (d) an overreliance on statistical methods to make up for poor experimental design.
This means the average published paper is likely a false positive, likely an overestimate of the true effect if not, and is barely reproducible.
Is this the fault of individual scientists? Partly, yes -- these problems have been pointed out for years in leading journals, but nobody takes action to do better research. It's also the fault of the grant funding systems which incentivize salami-slicing of results instead of doing one big, rigorous, well-designed study, and of journals which prefer dramatic but unreliable results over mundane but well-executed results. (Of course, the journal editors and reviewers are usually active scientists themselves.) I think the average researcher would like to "get it right", but has to focus on getting a career instead.
Just a few papers on the problem of poor sample sizes in biomedicine: http://journals.plos.org/plosbiology/article?id=10.1371/jour... http://rsos.royalsocietypublishing.org/content/4/2/160254 http://www.nature.com/nrn/journal/v14/n5/full/nrn3475.html