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Hypothesis testing (view source)

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This type of error refers to the situation where it is concluded that no difference between two groups exists, when in fact it does. The probability of a type II error is often denoted with the symbol β. The 'power' of a study is defined as the probability of detecting a difference when it does exist, and so can be calculated as (1-β).

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===One-tailed and two-tailed tests===

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~~===Approach to hypothesis testing===~~

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The approach to hypothesis testing first requires making the assumption that there is ''no difference'' between the two groups (which is known as the '''null hypothesis'''). Statistical methods are then employed in order to evaluate the probability that the observed data would be seen if the null hypothesis was correct (known as the '''p-value'''). Based on the resultant p-value, a decision can be made as to whether the support for the null hypothesis is sufficiently low so as to give evidence against it being correct. It is important to note, however, that the null hypothesis can never be completely disproved based on a sample - only evidence can be gained in support or against it. However, based on this evidence, investigators will often come to a conclusion that the null hypothesis is either 'accepted' or 'rejected'.<br>

[[Category:Veterinary Epidemiology - Statistical Methods|E]]

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