Data of unknown quality are useless! All laboratory measurements contain experimental error.
It is necessary to determine the magnitude of the accuracy and reliability in your measurements. Then you can make a judgment about their usefulness.
Replicates - two or more determinations on the same sample Example 3-1: One student measures Fe (III) concentrations six times. The results are listed below: 19.4, 19.5, 19. 6, 19.8, 20.1, 20.3 ppm (parts per million) 6 replicates = 6 measurements The "middle" or "central" value for a group of results: Mean: average or arithmetic mean
This paper proposes a method of correcting annotation errors in a treebank. By using a synchronous grammar, the method transforms parse trees containing annotation errors into the ones whose errors are corrected. The synchronous grammar is automatically induced from the treebank. We report an experimental result of applying our method to the Penn Treebank.
A collection of 3208 reported errors of Chinese words were analyzed. Among which, 7.2% involved rarely used character, and 98.4% were assigned common classifications of their causes by human subjects. In particular, 80% of the errors observed in writings of middle school students were related to the pronunciations and 30% were related to the compositions of words. Experimental results show that using intuitive Web-based statistics helped us capture only about 75% of these errors.
Modeling of individual users is a promising way of improving the performance of spoken dialogue systems deployed for the general public and utilized repeatedly. We deﬁne “implicitly-supervised” ASR accuracy per user on the basis of responses following the system’s explicit conﬁrmations. We combine the estimated ASR accuracy with the user’s barge-in rate, which represents how well the user is accustomed to using the system, to predict interpretation errors in barge-in utterances. Experimental results showed that the estimated ASR accuracy improved prediction performance.
Ideally, the first activity provides the necessary know-how for the pursuit of the second, but in practice,
the help it can give is only partial, and the second activity has to fall back on trial and error techniques in
order to achieve its ends. This means that a good chemist is one who not only has a mastery of chemical
theory, but also a good knowledge of chemical facts.
An ideal way to run this experiment would be to run all the 4x3=12
wafers in the same furnace run. That would eliminate the nuisance
furnace factor completely. However, regular production wafers have
furnace priority, and only a few experimental wafers are allowed into
any furnace run at the same time.
A non-blocked way to run this experiment would be to run each of the
twelve experimental wafers, in random order, one per furnace run.
A new edition of any book presents an opportunity which an author welcomes for several
reasons. It is a chance to respond to constructive criticisms of the previous edition which he
thinks are valid. New material can be introduced which may be useful to teachers and
students in the light of the way the subject, and the teaching of the subject, has developed in
the intervening years. Last, and certainly not least, there is an opportunity to correct any
errors which had escaped the author’s notice....
These results show that the existing literature considerably underestimates the reality of the wood
industry of Jepara. Using the data on the time of creation of all the enterprises that we surveyed,
we were able to deduce the number of enterprises of the furniture cluster back to 1955. Thus, we
can assess the magnitude of the error of former studies.
These and all subsequent regressions include our full array of demographic and time
controls, but we only report the distance coefficients for the sake of brevity.12 All
regressions report robust standard errors, which are adjusted for possible correlation
between the error terms of observations drawn from the same household.
The first column of Table 2 summarizes the relationship between distance and
diary week spending. Diary week spending declines significantly over the pay period at a
rate of 0.8 percent per day. Over the entire pay period this implies a substantial decline.
Based on common interests in the potential appli-
cation of these technological goals, the Museum of
Modern Art (MoMA), New York, and the MIT Me-
dia Laboratory agreed to a collaboration driven by
the desire to increasingly use technology in their ex-
hibits without making aesthetic concessions. Their
mainmotivation was to use smart spaces
exhibits, without the obvious elements of the asso-
ciated computing. They offered a very useful error
metric that is lacking in a laboratory: a very high aes-
Nuclear isotopes making experimental gamma energy spectrum are denoted
via their energies. One energy level of an isotope is supposed presence in the spectrum, if there is an energy level that is diﬀerent from it with a value less than its error. With suitable database, the program can be used to identify isotopes even stable isotopes by using α, β , X spectra.
Schmidt and Stolpe Health Economics Review 2011, 1:12 http://www.healtheconomicsreview.com/content/1/1/12
Transitivity in health utility measurement: An experimental analysis
Ulrich Schmidt1,2 and Michael Stolpe1*
Abstract Several experimental studies have observed substantial violations of transitivity for decisions between risky lotteries over monetary outcomes. The goal of our experiment is to test whether these violations also affect the evaluation of health states.
State-of-the-art statistical machine translation (MT) systems have made signiﬁcant progress towards producing user-acceptable translation output. However, there is still no efﬁcient way for MT systems to inform users which words are likely translated correctly and how conﬁdent it is about the whole sentence. We propose a novel framework to predict wordlevel and sentence-level MT errors with a large number of novel features. Experimental results show that the MT error prediction accuracy is increased from 69.1 to 72.2 in F-score. ...
Almost always, the cause of too good a chi-square ﬁt is that the experimenter, in a “ﬁt” of conservativism, has overestimated his or her measurement errors. Very rarely, too good a chi-square signals actual fraud, data that has been “fudged” to ﬁt the model.
This article summarizes expertise gleaned from the first years of Internet-based experimental research and
presents recommendations on: (1) ideal circumstances for conducting a study on the Internet; (2) what precautions have to
be undertaken in Web experimental design; (3) which techniques have proven useful in Web experimenting; (4) which
frequent errors and misconceptions need to be avoided; and (5) what should be reported. Procedures and solutions for
typical challenges in Web experimenting are discussed.
In this interactive presentation, a Chinese named entity and relation identification system is demonstrated. The domainspecific system has a three-stage pipeline architecture which includes word segmentation and part-of-speech (POS) tagging, named entity recognition, and named entity relation identitfication. The experimental results have shown that the average F-measure for word segmentation and POS tagging after correcting errors achieves 92.86 and 90.01 separately.
This paper describes a spoken dialog QA system as a substitution for call centers. The system is capable of making dialogs for both ﬁxing speech recognition errors and for clarifying vague questions, based on only large text knowledge base. We introduce two measures to make dialogs for ﬁxing recognition errors. An experimental evaluation shows the advantages of these measures.
This paper addresses the issue of POS tagger evaluation. Such evaluation is usually performed by comparing the tagger output with a reference test corpus, which is assumed to be error-free. Currently used corpora contain noise which causes the obtained performance to be a distortion of the real value. We analyze to what extent this distortion may invalidate the comparison between taggers or the measure of the improvement given by a new system. The main conclusion is that a more rigorous testing experimentation setting/designing is needed to reliably evaluate and compare tagger accuracies.
This paper proposes an alignment adaptation approach to improve domain-specific (in-domain) word alignment. The basic idea of alignment adaptation is to use out-of-domain corpus to improve in-domain word alignment results. In this paper, we first train two statistical word alignment models with the large-scale out-of-domain corpus and the small-scale in-domain corpus respectively, and then interpolate these two models to improve the domain-specific word alignment.