Sense confidence

As Tribus, 1969, says, all probabilities are conditional. In the example of the dree, the probabilities are conditioned on the assumption that the dice are perfect and the method of throwing has no effect on the outcome. Some writers (e.g., deMorgan, 1847) say, probability refers to the belief by a mind having uncertain knowledge. This is the interpretation of probability in the Zion-Indian Point (ZIP) and some other PSAs. IVobabiiity in this sense attempts to include all information e.g., QA that could affect the performance of a piece of equipment. Such information may be conveyed as a distribution whose height is proportional to confidence in the belief and who.se width reflects uncertainty (refer to Section 2.6). 

A Without an improvement in performance, we would be throwing our money away. The direct cost savings alone would not justify this project. Only when we factor in improved safety and environmental performance does the cost of this project make any sense. We would not be going ahead unless we were confident that real savings are possible. 

Educationists usually place the emphasis on the cognitive objectives of practical work. Of equal importance are however factors of the affective domain. Gott Mashiter (1991, p. 61) proposed that practical tasks should have within them the elements of motivation that stem from confidence in and a sense of ownership of the activity by the stndent . Motivation, however, requires not only a measnre of self-directedness by the learner but also interesting and exciting experiments (Hodson, 1996). 

Models must be both realistic and also robust. A model which predicts effects which are quite contrary to common sense or to normal experience is unlikely to be met with confidence. To accord with this, some use of empirical adjustment factors in the model may be needed, in order to represent combinations of relatively unknown unknown factors. 

Regardless of the relative importance of polar and nonpolar interactions in stabilizing the cyclohexaamylose-DFP inclusion complex, the results derived for this system cannot, with any confidence, be extrapolated to the chiral analogs. DFP is peculiar in the sense that the dissociation constant of the cyclohexaamylose-DFP complex exceeds the dissociation constants of related cyclohexaamylose-substrate inclusion complexes by an order of magnitude. This is probably a direct result of the unfavorable entropy change associated with the formation of the DFP complex. Thus, worthwhile speculation about the attractive forces that lead to enantiomeric specificity must await the measurement of thermodynamic parameters for the chiral substrates. 

The largest drawback to the use of amphetamines is the often severe side effects that can occur. All amphetamines can cause nervousness, dry mouth, insomnia, anxiety, elevated heart rate, high blood pressure, and heart palpitations. Another side effect of amphetamines is artificially elevated feelings of self-confidence. Abusers of amphetamines have a false sense of well-being they feel like they are invincible and could conquer the world. ... 

But where to begin Every day the prisoners are holding board-of-directors meetings, confident that they will soon be released because of insufficient evidence. You pick up a document it will have to wait until Charmatz translator returns, for all the other translators are busy. Besides, it doesn t make sense to take in one fact after another without a theory or a direction. 

For whatever reason, the client may not successfully negotiate the high-risk situation in a way that averts the risk. Unsuccessful coping may cause two unfortunate events to occur. The first is a reduction in her or his self-efficacy to successfully cope with the situation without drug use. As you may remember, self-efficacy involves the sense of mastery of a situation that results from competence and confidence. Client competence and confidence can take a beating when a high-risk situation is not handled effectively. 

Models must be both realistic and robust A model predicting effects, which are quite contrary to common sense or to normal experience, is unlikely to be met with confidence. 

Our experience has shown that computerized searching for information results in a false sense of credibility for what is retrieved. Additional confidence, particularly on the part of... 

Sensing the discontent of the staff members, who at first had seemed so glad to see me arrive, I decided to do the psychiatric thing - visit the boss and confide my growing discomfort and sense of rejection. 

In a sense, each element seems to have its own personality. The noble gases— helium, neon, argon, and the rest—seem aloof, independent, uninterested. Precious metals, including silver, gold, and platinum, impress me as serene, quiet, confident. Chromium, a shiny metal that forms many highly colored compounds appears to be a rock star among the elements, as does neodymium, the key element in early lasers. 

In some textbooks, a confidence interval is described as the interval within which there is a certain probability of finding the true value of the estimated quantity. Does the term true used in this sense indicate the statistical population value (e.g., p if one is estimating a mean) or the bias-free value (e.g., 6.21% iron in a mineral) Could these two interpretations of true value be a source of misunderstanding in conversations between a statistician and a geologist ... 

In Section 6.1, the concept of confidence intervals of parameter estimates was presented. In this section, we consider a general approach to the estimation of confidence intervals for parameter estimates and response surfaces based on models that have been shown to be adequate (i.e., the lack of fit is not highly significant, either in a statistical or in a practical sense). 

One question that is often asked of statisticians is in what sense can we be 95% confident that the population mean lies within the limits 3.84 and 4.13 To answer the question we can again conduct a sampling experiment as follows. Suppose that the 40 blood glucose measurements in Figure 8.3 comprised the total population of values. For random sample of size 10 from the populations of blood glucose values determine the sample mean, standard error and the corresponding 95% confidence interval. Repeat the process 100 times. The results of such an experiment are shown in Figure 8.6. 

In Figure 8.9, we illustrate various cases that can arise from studies intended to show equivalence and the relationship between significance in the traditional sense and clinical significance as determined by the confidence interval and the boundaries of equivalence. In case (A), the 95% confidence interval includes both the null hypothesis of no difference and is within the boundaries of equivalence and from both a statistical and clinical perspective there is no evidence of a difference between the treatments. In case (B), in contrast, the confidence interval is still within the boundaries, but does include the null hypothesis, so from a statistical perspective there is a difference between the treatments but it is not clinically relevant. Case (C) shows both statistical and clinical significance, as the confidence interval lies outside the equivalence boundaries and therefore cannot include the null hypothesis. In the final case, (D), the confidence interval includes... 

In a conventional sense, rejection of hypothesis H is significant at the 5%, and highly significant at the 1% level, i.e. at a 95% and 99% level of confidence, respectively. The required tests are applied to ranks, or differences in ranks, instead of numerical observations this is a fundamental characteristic of nonparametric versus classical statistics. 

An approach that is sometimes helpful, particularly for recent pesticide risk assessments, is to use the parameter values that result in best fit (in the sense of LS), comparing the fitted cdf to the cdf of the empirical distribution. In some cases, such as when fitting a log-normal distribution, formulae from linear regression can be used after transformations are applied to linearize the cdf. In other cases, the residual SS is minimized using numerical optimization, i.e., one uses nonlinear regression. This approach seems reasonable for point estimation. However, the statistical assumptions that would often be invoked to justify LS regression will not be met in this application. Therefore the use of any additional regression results (beyond the point estimates) is questionable. If there is a need to provide standard errors or confidence intervals for the estimates, bootstrap procedures are recommended. 

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