Popularly known as the Sapir–Whorf hypothesis, or Whorfianism, the principle is often defined as having two versions:
The hypothesis of linguistic determinism is now generally agreed to be false, though many researchers are still studying weaker forms of correlation, often producing positive empirical evidence for a correlation .
The Sapir-Whorf Hypothesis suggests that language shapes the way we see the world.
We would like to test this hypothesis by comparing the average out-degree of governmental and non-governmental actors in one organizational field.
This would seem to support our hypothesis; but tests of statistical significance urge considerable caution.
Differences as large as 6.481 in favor of government organizations happen 33.4% of the time in random trials -- so we would be taking an unacceptable risk of being wrong if we concluded that the data were consistent with our research hypothesis.
In many cases, the same or closely related tools are used for questions of assessing generalizability and for hypothesis testing.
The basic logic of hypothesis testing is to compare an observed result in a sample to some null hypothesis value, relative to the sampling variability of the result under the assumption that the null hypothesis is true.
If the sample result differs greatly from what was likely to have been observed under the assumption that the null hypothesis is true -- then the null hypothesis is probably not true.
The key link in the inferential chain of hypothesis testing is the estimation of the standard errors of statistics.
These differences are quite consequential for both the questions of generalization of findings, and for the mechanics of hypothesis testing.