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Statistical assumptions are general assumptions about statistical populations.

Statistics, like all mathematical disciplines, does not generate valid conclusions from nothing. In order to generate interesting conclusions about real statistical populations, it is usually required to make some background assumptions. These must be made with care, because inappropriate assumptions can generate wildly inaccurate conclusions.

The most commonly applied statistical assumptions are:

1. independence of observations from each other (see statistical independence)
2. independence of observational error from potential confounding effects
3. exact or approximate normality of observations (see normal distribution)
4. linearity of graded responses to quantitative stimuli (see linear regression)

This page uses content from the English-language version of Wikipedia. The original article was at Statistical_assumptions. The list of authors can be seen in the page history. As with Psychology Wiki, the text of Wikipedia is available under the GNU Free Documentation License.