41 resultados para Algorithmic Probability
Resumo:
Performance at the Joinery, Dublin, at at Spatial Music Collective concert
Resumo:
In three studies we looked at two typical misconceptions of probability: the representativeness heuristic, and the equiprobability bias. The literature on statistics education predicts that some typical errors and biases (e.g., the equiprobability bias) increase with education, whereas others decrease. This is in contrast with reasoning theorists’ prediction who propose that education reduces misconceptions in general. They also predict that students with higher cognitive ability and higher need for cognition are less susceptible to biases. In Experiments 1 and 2 we found that the equiprobability bias increased with statistics education, and it was negatively correlated with students’ cognitive abilities. The representativeness heuristic was mostly unaffected by education, and it was also unrelated to cognitive abilities. In Experiment 3 we demonstrated through an instruction manipulation (by asking participants to think logically vs. rely on their intuitions) that the reason for these differences was that these biases originated in different cognitive processes.
Dual-processes in learning and judgment:Evidence from the multiple cue probability learning paradigm
Resumo:
Multiple cue probability learning (MCPL) involves learning to predict a criterion based on a set of novel cues when feedback is provided in response to each judgment made. But to what extent does MCPL require controlled attention and explicit hypothesis testing? The results of two experiments show that this depends on cue polarity. Learning about cues that predict positively is aided by automatic cognitive processes, whereas learning about cues that predict negatively is especially demanding on controlled attention and hypothesis testing processes. In the studies reported here, negative, but not positive cue learning related to individual differences in working memory capacity both on measures of overall judgment performance and modelling of the implicit learning process. However, the introduction of a novel method to monitor participants' explicit beliefs about a set of cues on a trial-by-trial basis revealed that participants were engaged in explicit hypothesis testing about positive and negative cues, and explicit beliefs about both types of cues were linked to working memory capacity. Taken together, our results indicate that while people are engaged in explicit hypothesis testing during cue learning, explicit beliefs are applied to judgment only when cues are negative. © 2012 Elsevier Inc.
Resumo:
Multiple-cue probability learning (MCPL) involves learning to predict a criterion when outcome feedback is provided for multiple cues. A great deal of research suggests that working memory capacity (WMC) is involved in a wide range of tasks that draw on higher level cognitive processes. In three experiments, we examined the role of WMC in MCPL by introducing measures of working memory capacity, as well as other task manipulations. While individual differences in WMC positively predicted performance in some kinds of multiple-cue tasks, performance on other tasks was entirely unrelated to these differences. Performance on tasks that contained negative cues was correlated with working memory capacity, as well as measures of explicit knowledge obtained in the learning process. When the relevant cues predicted positively, however, WMC became irrelevant. The results are discussed in terms of controlled and automatic processes in learning and judgement. © 2011 The Experimental Psychology Society.
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Soil fauna in the extreme conditions of Antarctica consists of a few microinvertebrate species patchily distributed at different spatial scales. Populations of the prostigmatic mite Stereotydeus belli and the collembolan Gressittacantha terranova from northern Victoria Land (Antarctica) were used as models to study the effect of soil properties on microarthropod distributions. In agreement with the general assumption that the development and distribution of life in these ecosystems is mainly controlled by abiotic factors, we found that the probability of occurrence of S. belli depends on soil moisture and texture and on the sampling period (which affects the general availability of water); surprisingly, none of the analysed variables were significantly related to the G. terranova distribution. Based on our results and literature data, we propose a theoretical model that introduces biotic interactions among the major factors driving the local distribution of collembolans in Antarctic terrestrial ecosystems. (c) 2007 Elsevier Ltd. All rights reserved.
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Ninety-one patients were studied serially for chimeric status following allogeneic stem cell transplantation (SCT) for severe aplastic anaemia (SAA) or Fanconi Anaemia (FA). Short tandem repeat polymerase chain reaction (STR-PCR) was used to stratify patients into five groups: (A) complete donor chimeras (n = 39), (B) transient mixed chimeras (n = 15) (C) stable mixed chimeras (n = 18), (D) progressive mixed chimeras (n = 14) (E) recipient chimeras with early graft rejection (n = 5). As serial sampling was not possible in Group E, serial chimerism results for 86 patients were available for analysis. The following factors were analysed for association with chimeric status: age, sex match, donor type, aetiology of aplasia, source of stem cells, number of cells engrafted, conditioning regimen, graft-versus-host disease (GvHD) prophylaxis, occurrence of acute and chronic GvHD and survival. Progressive mixed chimeras (PMCs) were at high risk of late graft rejection (n = 10, P <0.0001). Seven of these patients lost their graft during withdrawal of immunosuppressive therapy. STR-PCR indicated an inverse correlation between detection of recipient cells post-SCT and occurrence of acute GvHD (P = 0.008). PMC was a bad prognostic indicator of survival (P = 0.003). Monitoring of chimeric status during cyclosporin withdrawal may facilitate therapeutic intervention to prevent late graft rejection in patients transplanted for SAA.
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Scrapers have established an important position in the earthmoving field as they are independently capable of accomplishing an earthmoving operation. Given that loading a scraper to its capacity does not entail its maximum production, optimizing the scraper’s loading time is an essential prerequisite for successful operations management. The relevant literature addresses the loading time optimization through a graphical method that is founded on the invalid assumption that the hauling time is independent of the load time. To correct this, a new algorithmic optimization method that incorporates the golden section search and the bisection algorithm is proposed. Comparison of the results derived from the proposed and the existing method demonstrates that the latter entails the systematic needless prolongation of the loading stage thus resulting in reduced hourly production and increased cost. Therefore, the proposed method achieves an improved modeling of scraper earthmoving operations and contributes toward a more efficient cost management.
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Large data sets of radiocarbon dates are becoming a more common feature of archaeological research. The sheer numbers of radiocarbon dates produced, however, raise issues of representation and interpretation. This paper presents a methodology which both reduces the visible impact of dating fluctuations, but also takes into consideration the influence of the underlying radiocarbon calibration curve. By doing so, it may be possible to distinguish between periods of human activity in early medieval Ireland and the statistical tails produced by radiocarbon calibration.
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The equiprobability bias is a tendency for individuals to think of probabilistic events as 'equiprobable' by nature, and to judge outcomes that occur with different probabilities as equally likely. The equiprobability bias has been repeatedly found to be related to formal education in statistics, and it is claimed to be based on a misunderstanding of the concept of randomness.