Estimation and Model Building M. H. Faber. Yovisto Academic Video Search. Testing for statistical significance, Hypothesis testing, Selection of probability distributions, Model selection using probability paper Testing Statistical Significance Model Estimation Building Summary Previous Lecture Short selectio Selection Small sample probability Eidgenössische Technische Hochschule Zürich (ETHZ) technology institut federal swiss ordered from established function distribution cumulativ sampl pap probability selection building model estimation technology institut federal swiss normal constructing graphical pap probability building model estimation estimation technology institut federal swiss non-linear scal y-axis function distribution cumulativ normal exampl pap probability selection building model technology institut federal swiss lin straight shap hav plotted distribution cumulativ giv when that constructed pap probability selection building model estimation technology institut federal swiss non-linear scal y-axis function distribution cumulativ normal exampl pap probability selection building model estimation technology institut federal swiss pap probability selection building model estimation technology institut federal swiss selected contradiction gross check thereaft selecting reason physical consid first senc common necessary therefor significanc reasonabl with distribution giv hypothesis reject support abl spars data availabl that cas oft application engineering function probability selection building model estimation technology institut federal swiss verify reject test statistical perform postulated paramet estimat family hypothesis postulat approach classical formalized understanding engineering argument physical data information basis chos must process variabl random giv distribution general function probability selection building model estimation technology institut federal swiss subjectiv model engineering developing when used information typ different building model estimation overview technology institut fad swiss experienc engineering sampl mor testing significanc reduced mean descriptor sampl with associated uncertainty exercis technology institut federal swiss lat treated probl decision should chois formulation consequenc economical significant related which error typ performing effect direct hav chois anything prov possibl principl consequently level using ways hypothesis becaus test valu estimat over careful very must problem typ different variety test regarding consideration som significanc statistical testing technology federal from determined wher accept rul operating that would null-hypothesis paramet with f-distributed thus variabl random distributed chi-squar betwe theratio seen which statistic following considering performed test varianc equal significanc statistical testing technology institut federal swiss calculated valu mean equal significanc statistical testing technology institut federal swiss varianc valu statistic varianc with distributed normal assumed both variabl random realization being set data hav that assum her valu mean equal significanc statistical testing institut federal swiss correlation zero varianc valu mean equal test term compar know lik would larg very each set hav wher situation typically data than mor significanc statistical testing technology institut federal swiss freedom degre distributed chi-squar used from determined wher hypothesis accept then rul operating befor small treatment surfac with lif fatigu that postulat null-hypothesis varianc significanc statistical testing technology institut federal swiss effect verify availabl data only expensiv very experiment treatment surfac weld mean reduced attempted joint welded fatigu wher cas exampl consid varianc significanc statistical testing averag sampl befor outcom experiment sam assuming varianc unknown with mean significanc statistical testing technology institut federal swiss rejected should null-hypothesis thus interval within which becom isun giv technology institut federal swiss degre t-distribution using determined which from then rul operating freedom degre t-distributed realized considered must statistic sampl following that assumed varianc unknown with mean significanc statistical testing institut federal swiss rejected should null-hypothesis thus interval within which becom t-statistic giv averag sampl befor outcom experiment sam assuming varianc unknown with mean significanc statistical testing institut federal swiss degre t-distribution using determined from then rul operating freedom degre t-distributed realized which considered must statistic sampl following that assumed varianc unknown with mean significanc statistical testing institut federal swiss rejected should null-hypothesis thus interval within which becom giv averag sampl befor outcom experiment sam assuming varianc unknown with mean significanc statistical testing swiss degre t-distribution using determined from then rul operating freedom degre t-distributed realized which considered must statistic sampl following that assumed varianc unknown with mean significanc statistical testing technology institut federal institut federal swiss rejected should null-hypothesis thus interval within which becom ii-i giv averag sampl befor outcom experiment sam assuming varianc unknown with mean significanc statistical testing institut federal swiss degre t-distribution using determined from then rul operating freedom degre t-distributed realized which brand considered must statistic sampl following that assumed varianc unknown with mean significanc statistical testing technology institut federal swiss level concluded obtained result following carried experiment that assum accepted should null-hypothesis interval lies averag sampl varianc known with mean significanc statistical testing with mean significanc statistical testing technology institut federal swiss distributed normal averag sampl that assuming experiment choosing giv determined criteria acceptanc varianc known institut federal swiss level concluded obtained result following carried experiment that assum accepted should null-hypothesis interval lies averag sampl varianc known with mean significanc statistical testing technology institut federal swiss distributed normal averag sampl that assuming experiment choosing 1-ax giv determined criteria acceptanc varianc known with mean significanc statistical testing institut federal swiss a-level null-hypothesis accept formulated rul operating equal know that assum concentration chlorid surfac assumption design varianc known with mean significanc statistical testing technology institut federal swiss structur concret corrosion induced chlorid exampl significanc statistical testing technology institut federal swiss structur concret corrosion induced chlorid exampl significanc statistical testing technology institut federal swiss aaaaa structur concret corrosion induced chlorid exampl significanc statistical testing technology institut federal concret corrosion induced chlorid exampl significanc statistical testing technology institut federal swiss set data mor test unknown varianc known with mean engineering test typical significanc statistical testing video gelernt vorlesungsstoff gehalt englisch well meist skript behandelt them nutzbar munn wono kenntniss sich inter vorles naca hill alga english ward technology institut federal swiss set data mor test unknown varianc known with mean engineering test typical significanc statistical testing tuib operating technology institut federal follows visualized procedur hypothesis significanc statistical testing institut federal swiss otherwis level data evidenc supported that giv accepted rejected should null-hypothesis check statistic sampl observed evaluat test planned perform typ performing probability relevant corresponding valu calculat significanc statistical testing operating result test evidenc rejected accepted eith which basis rul formulat gtep valu giv equal mdan statistic sampl that postulating significanc statistical testing technology institut federal swiss fals influenc this error typ true though even probability wher level select hypothesis alternat accepting correspond rejecting null-hypothesis stati observed interval defined oft technology institut federal swiss following detail som approach this into look hav shall test hypothesis formulat supporting useful utilized highly trigg evidenc regard formalism giv data theevidenc reflect should transparent consistent basis drawn conclusion that important significanc statistical testing federal swiss quality drinking that wat ground collect valid assumption volum design check bridg crossing traffic observation characteristics strength soil model calculation verify test sit mak variability degre high with data limited based conclusion simpl draw dilemma engineering significanc statistical testing technology institut federal swiss subjectiv model engineering developing when used information typ different building model estimation overview random exercis institut federal swiss t-distribution follows distributed normal standard wher defined variabl high technology institut federal swiss f-distribution distribution follows distributed normal standard wher defined variabl random exercis techn institut federal swiss depend interval confidenc importanc significant data availabl numb lectur previous summary short techn federal level significanc siz tlev known i-47 true averag confidenc called thes probability giv them find wher interval determin howev valu exact their know dont mean sampl descriptor with associated uncertainty lectur previous summary short technology institut federal swiss biased varianc sampl lectur previous summary short technology institut federal swiss descriptor unbiased valu mean sampl lectur previous summary short technology institut federal swiss epistemical statistical uncertainty with associated learn what varianc valu mean simply descriptor sampl lectur previous summary short short institut federal swiss statistics characteristics ummm sum function valu interval confidenc sampl estimator looked lectur previous summary technology institut federal swiss pap probability function distribution selection set data mor test unknown varianc known with mean procedur hypothesis significanc statistical testing building model estimation overview previous summary shod lectur todays content switzerland zurich technology institut federal swiss fab michael prof engineering environmental surveying civil theory probability statistics basic