L22 - Testing a Single Parameter Significance tests are different type of statisti cal inference Want to choose between com peting hypotheses about

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Unformatted text preview: Testing a Single Parameter Significance tests are different type of statisti- cal inference. Want to choose between com- peting hypotheses about a parameter. θ Definition: An hypothesis is an assertion about a population or about a parameter. We distinguish two kinds of hypotheses: H : null hypothesis (status quo, previously accepted) H 1 : alternative hypothesis (what you hope to establish) A significance test is a procedure for judging which hypothesis is true. 1 Criminal trial analogy (in Canada, U.S.A.): H : not guilty H 1 : guilty Not treated symmetrically. Assume H true unless compelling evidence against H in favour of H 1 . Likewise, in statistics H is assumed true and is only rejected in favor of H 1 if the evidence (data) is compelling ( significant ) beyond rea- sonable doubt (could not happen by chance). 2 Example. p 248 . Standard production setup, average μ = 30 minutes to com- plete task. Variation: work conditions, parts, ability leads to random error . X i is time taken by randomly selected worker...
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This note was uploaded on 01/03/2012 for the course EE 1244 taught by Professor Drera during the Fall '10 term at Conestoga.

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L22 - Testing a Single Parameter Significance tests are different type of statisti cal inference Want to choose between com peting hypotheses about

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