A new study indicates that researchers' political ideologies tend to shape their scientific findings. An experiment involving 158 scientists revealed that personal views on immigration predicted the results obtained from identical data.
Very little that can be inferred indeed. They use linear regression to quantify correlations, that is they assume that relations are linear – and don’t even seem to justify why or how such an assumption should be valid. Good luck with that. Final blow is the use of p-values and “statistical significance”. To quote from the official statement by the American Statistical Association:
P-values do not measure the probability that the studied hypothesis is true, or the probability that the data were produced by random chance alone.
Scientific conclusions and business or policy decisions should not be based only on whether a p-value passes a specific threshold.
A p-value, or statistical significance, does not measure the size of an effect or the importance of a result.
By itself, a p-value does not provide a good measure of evidence regarding a model or hypothesis.
Very little that can be inferred indeed. They use linear regression to quantify correlations, that is they assume that relations are linear – and don’t even seem to justify why or how such an assumption should be valid. Good luck with that. Final blow is the use of p-values and “statistical significance”. To quote from the official statement by the American Statistical Association: