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--- public:t-701-rem4:ultimate_note_on_statistical_tests [2007/11/17 19:38] – helgi
+++ public:t-701-rem4:ultimate_note_on_statistical_tests [2024/04/29 13:33] (current) – external edit 127.0.0.1
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 **We have a random sample from a (often infinite) population.** The population is either explicit or hypothetical.
-**We have a precise hypothesis called the null hypothesis (H0) to be tested**. Loosely speaking, "being tested" means that H0 is accused of being wrong. The hypothesis is on some property of the population from which the sample was drawn.
+**We have a precise hypothesis to be tested, called the null hypothesis (H0)**. Loosely speaking, "being tested" means that H0 is accused of being wrong. The hypothesis is on some property of the population from which the sample was drawn.
 Often, H0 states that the effect of some independent variable on another dependent variable is zero (thus null-hypothesis). The independent variable can by either a grouping (gender of a living being, type of machine, ..., called qualitative variables, classifications, logical variables if there are only 2 groups) or a numeric variable (height of a being, weight or power of a machine, ..., called quantitative variable or sometimes a measure). Often, H0 can then be the conventional wisdom or a harmless situation (all individuals are equal), nothing needs to be done.
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 The only rule of thumb we have for directly interpreting test statistics is for the t-value: If the absolute value of t is smaller than 1.5, we never reject H0 (p-value much higher than 0.05), if it is larger than 4 we always do (p-value very small), if it is in between we need to choose a threshold for rejection and look at the p-value.
+{{public:t-701-rem4:noteontests.pdf|}}