Statistics does not tell us whether we are right. It tells us the chances of being wrong.
Krzywinski, M., Altman, N. Importance of being uncertain. Nat Methods 10, 809–810 (2013). https://doi.org/10.1038/nmeth.2613
Understanding Replication & Uncertainty
When an experiment is reproduced, we almost never obtain exactly the same results.
Instead, repeated measurements span a range of values because of biological variability and precision limits of measuring equipment.
But if results are different each time, how do we determine whether a measurement is compatible with our hypothesis?
Statistical Methods are Key
💡 Statistics helps us answer this question.
It gives us a way to quantitatively model the role of chance in our experiments and to represent data not as precise measurements but as estimates with error. It also tells us how error in input values propagates through calculations.
The practical application of this theoretical framework is to associate uncertainty to the outcome of experiments and to assign confidence levels to statements that generalize beyond observations.”
An easy to read paper to understand the notion of uncertainty and how it affects the decision-making process in science.