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This is the second of a two-part article, in which we discuss problems associated with null hypothesis significance testing (NHST) and the use of the I p i -value. To start with misuse, many researchers just use CIs to conduct NHST: when the CI does not include the value of no effect, the null hypothesis is rejected, and the effect is significant. The area under the curve represents possible I p i -values; more specifically, the I p i -value is the probability where a datapoint or more extreme data can be observed under this curve. When the probability of an observed, or more extreme observation under the assumption that H SB 0 sb is true (i.e. the I p i -value), is very small, we state that this value does not support our null hypothesis and consequently reject it. [Extracted from the article]

In hand surgery research, most studies, whether observational studies or randomized controlled trials (RCT), are aimed at finding out whether there is an effect (association or difference) of a certain determinant on a specific outcome. The whiskers represent the 95% confidence intervals (CI), which provide an indication of the precision with which this difference was estimated (this will be further elaborated in Part 2). In the last scenario (yellow), the 95% CI reflects a very imprecise result that is clearly not statistically significant, and for which clinical relevance remains inconclusive since the 95% CI overlaps the MCIC. [Extracted from the article]