Assessing Theoretical Conclusions With Blinded Inference to Investigate a Potential Inference Crisis
نویسندگان
چکیده
منابع مشابه
Bayesian approach to inference of population structure
Methods of inferring the population structure, its applications in identifying disease models as well as foresighting the physical and mental situation of human beings have been finding ever-increasing importance. In this article, first, motivation and significance of studying the problem of population structure is explained. In the next section, the applications of inference of p...
متن کاملSymbolic Probabilistic Inference with Evidence Potential
Recent research on the Symbolic Probabilis tic Inference (SPI) algorithm[;:] has focused attention on the importance of resolving general queries in Bayesian networks. SPI applies the concept of dependency-directed backward search to probabilistic inference, and is incremental with respect to both queries and observations. In response to this research we have extended the evidence potential al...
متن کاملInference to the Best Explanation and Theoretical Entities
Scientific entity realism has been challenged on the grounds that it depends on the controversial principle of inference to the best explanation. I defend the view against this challenge, by showing that the particular inferences needed by the entity realist do not have the objectionable features antirealist's cite in questioning inference to the best explanation. Indeed, these inferences are e...
متن کاملAssessing Student Learning about Statistical Inference
Statistical significance and p-values can be a particularly challenging topic for introductory statistics students. In an effort to assess curricular changes aimed at deepening student understanding of significance, we have developed assessment strategies to diagnose students’ conceptualization of p-value and their ability to communicate their understanding. We will present our approaches and d...
متن کاملAn Introduction to Inference and Learning in Bayesian Networks
Bayesian networks (BNs) are modern tools for modeling phenomena in dynamic and static systems and are used in different subjects such as disease diagnosis, weather forecasting, decision making and clustering. A BN is a graphical-probabilistic model which represents causal relations among random variables and consists of a directed acyclic graph and a set of conditional probabilities. Structure...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Advances in Methods and Practices in Psychological Science
سال: 2019
ISSN: 2515-2459,2515-2467
DOI: 10.1177/2515245919869583