The t statistic is used in the context of a t-test when doing hypothesis testing. Hypothesis tests start with a null hypothesis (Ho) which states there is no statistically significant difference.

Statistical significance alone didn’t lead to the replication crisis. The institutions of science incentivized the behaviors that allowed it to fester. You’ve read 1 article in the last month.

A t-test is an inferential statistic used in hypothesis testing to determine if there is a statistically significant difference between the means of two samples.

But business relevance (i.e., practical significance) isn’t always the same thing as confidence that a result isn’t due purely to chance (i.e., statistical significance).

Where did the idea for statistical significance come from? Many scientists now interpret P equal to 0.05 as a cutoff between an experiment that “worked” and one that didn’t.

One advocate called it a “surgical strike against thoughtless testing of statistical significance” and “an opportunity to register your voice in favour of better scientific practices”.

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