Robust and sound?

When we carry out experiments and perform statistical tests we have two distinct aims.

  1. To form statistically robust conclusions about empirical data.
  2. To make logically sound arguments about experimental conclusions.

Robustness is essentially an inductive mathematical or statistical issue.

Soundness is a deductive question of experimental design and reporting.

Robust conclusions are those that are likely to be repeated if another researcher were to come along and perform the same experiment with different data sampled in much the same way. Sound arguments distinguish between what we can legitimately infer from our data, and the hypothesis we may wish to test.

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