Intervals of confidence

The author s method which gives an interval of confidence shows that we have < 95% chance to be right when asserting the NfPA code. 1 can not be attributed to this substance (this will be explained p.81) ... 

If the (2observed > (2theoreticab the outlier may be discarded. The Q test gives a good evaluation of the outlier when the number of observations >5. Different intervals of confidence can be chosen to evaluate theoretical even if a 95% confidence limit is suggested. 

The cycles are stopped when the intervals of confidence for all y, remain unchanged. 

The interval of confidence of the variation of the reaction efficiency can be calculated using Table 5.56. Then, considering the AB interaction, we can compute the... 

In Chapter 1 sensitivity has been defined as the responsiveness of the assay to changes in concentration of the substance tested, i.e., d/ /dC. Therefore, on a sigmoid dose-response curve, sensitivity decreases at either end of the curve. As evident from Fig. 15.1, the interval of confidence for the concentration obtained can be defined by the ratio ... 

The methods and statistical criteria we have just studied allow the model coefficients to be estimated, the fitness of the model to be assessed, and its acceptance or rejection. They also allow estimation of the experimental variance and from this the variances and intervals of confidence of the coefficient estimates can be calculated. It is important, however, to test the quality of the design before the experiment, to allow, where necessary, the comparison of different strategies and to justify the choice of one plan or design rather than another (10). There are many objective criteria for doing this. We will list a few of the most important without theoretical justification, but describing their practical significance. Their use will be illustrated in later examples. 

The best results seem reasonable predictions, but somewhat unsafe, and therefore, an interval of confidence is necessary. 

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