Statistical test

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\newcommand{\P}[2][]{\mathbb{P}#1{\left[{#2}\right]} } \newcommand{\Pcond}[3][]{\mathbb{P}#1{\left[{#2}\!\ \middle\vert\!\ {#3}\right]} } \newcommand{\Plcond}[3][]{\Pcond[#1]{#2}{#3} } \newcommand{\Prcond}[3][]{\Pcond[#1]{#2}{#3} }
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Include hypothesis testing of which are an instance of statistical tests. Link to true/false positive/negative and create pages for false positive and such that redirect to an anchor on that page. Don't forget the power function - Alec (talk) 13:32, 14 December 2017 (UTC)

Definition

A statistical test, T, is characterised by two (a pair) of probabilities:

  • T\eq(u,v), where:
    • u is the probability of the test yielding a true-positive result
    • v is the probability of the test yielding a true-negative result

If we write [T\eq 1] for the test coming back positive, [T\eq 0] for negative and let P denote the actual correct outcome (which may be unknowable), denoting [P\eq 1] if the thing being tested for is, in truth, present and [P\eq 0] if absent, then:

Outcomes: Truly present
[P\eq 1]
Truly absent
[P\eq 0]
Test positive
[T\eq 1]
\Pcond{T\eq 1}{P\eq 1}\eq u \Pcond{T\eq 1}{P\eq 0}\eq 1-v
Test negative
[T\eq 0]
\Pcond{T\eq 0}{P\eq 1}\eq 1-u

false negative

\Pcond{T\eq 0}{P\eq 0}\eq v

true negative

OLD PAGE

Definition

A statistical test, T, is characterised by two (a pair) of probabilities:

  • T\eq(u,v), where:
    • u is the probability of the test yielding a true-positive result
    • v is the probability of the test yielding a true-negative result

Tests are usually asymmetric, see: below and asymmetry of statistical tests for more info.

Notation and Terminology

For a test subject, s, we say the outcome of the test is:

  1. Positive: [T(s)\eq 1], [T(s)\eq\text{P}], or possibly either of these without the [\ ]
  2. Negative: [T(s)\eq 0], [T(s)\eq\text{N}], or possibly either of these without the [\ ]

Power and Significance

The power of the test is

Explanation

Let R denote the result of the test, here this will be 1 or 0, and let P be whether or not the subject actually has the property being tested for. As claimed above the test is characterised by two probabilities