{"id":20478,"date":"2018-12-15T20:00:58","date_gmt":"2018-12-15T14:00:58","guid":{"rendered":"https:\/\/www.enago.com\/academy\/?p=20478"},"modified":"2022-04-29T22:47:44","modified_gmt":"2022-04-29T16:47:44","slug":"should-researchers-include-a-confidence-index-of-their-results","status":"publish","type":"post","link":"https:\/\/www.enago.com\/academy\/should-researchers-include-a-confidence-index-of-their-results\/","title":{"rendered":"Should Researchers Include a Confidence Index of Their Results?"},"content":{"rendered":"

The ongoing reproducibility crisis has drawn attention to the way experiments are reported. Alarmingly, a Nature survey revealed that 70 % of scientists were unable to reproduce another scientists\u2019 experiments and 50 % were unable to reproduce their own experiments. It is common scientific practice to back your results statistically with a p-value. However, the reproducibility crisis suggests that this is not enough. One way to add clarity to data interpretation<\/a> may be to use a confidence index, that tells you the chances of your results being true.<\/p>\n

What is a Confidence Index?<\/h2>\n

In scientific experiments, you test a treatment on a sample of a population. You ensure that you select a random sample (e.g. clinical trial participants) representative of a population. The confidence index will tell you how certain you can be that your treatment will have the same effect (as occurred in your experiments) on the entire population.<\/p>\n

It is a convention within scientists to report their data<\/a> with a p-value, and although it is similar to a confidence index, it is not the same. The difference is that the p-value implies that your result is 95 % accurate, whereas a confidence index tells you the probability of your result being accurate.<\/p>\n

P-value calculations are dependent on:<\/p>\n