Lec-30 2010 - CEE 3040 UNCERTAINTY ANALYSIS IN ENGINEERING...

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CEE 3040 - UNCERTAINTY ANALYSIS IN ENGINEERING Notes for Lecture #30 Monday, Nov.8, 2010 Review Let’s play the “one-tail test or two-tail test?” game: 1. Does the new roofing material last sufficiently long? 2. Does the new medication reduce the incidence of short-term illness compared to a placebo? 3. You travel to a distant solar system and encounter an alien life form. Is their average height different from that of humans? 4. Does the new medical treatment lead to more patients being cured than the current best practice? 5. Is the condition of the field different from that of surrounding fields due to contamination? Paired Tests (Devore §9.3)(Last  new  topic related to Hypothesis testing) Statisticians and engineers can  control variability  if experiments employ paired data.  This is a simple  example of “Experimental Design” discussed in  ActivStats  Chapter 11.  For example, suppose you want  to evaluate two methods by which engineers can estimate the 50-year flood at ungauged sites.   Experiment with independent samples. Select 16 engineers to do analysis with method A:    {X i } Select 16  different  engineers to do analysis with method B:     {Y i } Sources of variability in  talent and skill of 32 randomly selected engineers random errors in calculations Signal is E[] =  µ x  –  µ y   =  difference in efficiency and accuracy of methods Experiment with paired data.  Page  1  of 6
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CEE 3040 - UNCERTAINTY ANALYSIS IN ENGINEERING Notes for Lecture #30 Select 16 engineers to use both methods; record differences: W i  = (X – Y i )
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