Show/Hide Menu
Hide/Show Apps
Logout
Türkçe
Türkçe
Search
Search
Login
Login
OpenMETU
OpenMETU
About
About
Open Science Policy
Open Science Policy
Open Access Guideline
Open Access Guideline
Postgraduate Thesis Guideline
Postgraduate Thesis Guideline
Communities & Collections
Communities & Collections
Help
Help
Frequently Asked Questions
Frequently Asked Questions
Guides
Guides
Thesis submission
Thesis submission
MS without thesis term project submission
MS without thesis term project submission
Publication submission with DOI
Publication submission with DOI
Publication submission
Publication submission
Supporting Information
Supporting Information
General Information
General Information
Copyright, Embargo and License
Copyright, Embargo and License
Contact us
Contact us
Olasılık konusu öğrencilere neden zor gelmektedir?
Date
2009-01-01
Author
Kazak, Sibel
Metadata
Show full item record
This work is licensed under a
Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License
.
Item Usage Stats
223
views
0
downloads
Cite This
URI
https://hdl.handle.net/11511/100580
Relation
İlköğretimde karşılaşılan matematiksel zorluklar ve çözüm önerileri
Collections
Department of Mathematics and Science Education, Book / Book chapter
Suggestions
OpenMETU
Core
Olasılık öğretiminde farklı bir yaklaşım: İnanç ve frekans bakış açıları
Kazak, Sibel (2022-09-01)
Quantitative measures of observability for stochastic systems
Subaşı, Yüksel; Demirekler, Mübeccel; Department of Electrical and Electronics Engineering (2012)
The observability measure based on the mutual information between the last state and the measurement sequence originally proposed by Mohler and Hwang (1988) is analyzed in detail and improved further for linear time invariant discrete-time Gaussian stochastic systems by extending the definition to the observability measure of a state sequence. By using the new observability measure it is shown that the unobservable states of the deterministic system have no effect on this measure and any observable part wit...
Probabilistic matrix factorization based collaborative filtering with implicit trust derived from review ratings information
Ercan, Eda; Taşkaya Temizel, Tuğba; Department of Information Systems (2010)
Recommender systems aim to suggest relevant items that are likely to be of interest to the users using a variety of information resources such as user profiles, trust information and users past predictions. However, typical recommender systems suffer from poor scalability, generating incomprehensible and not useful recommendations and data sparsity problem. In this work, we have proposed a probabilistic matrix factorization based local trust boosted recommendation system which handles data sparsity, scalabil...
The Interaction of probability learning and prefrontal cortex
Gözenman, Filiz; Gökçay, Didem; Çakır, Murat Perit; Department of Cognitive Sciences (2012)
Probability learning is the ability to establish a relationship between stimulus and outcomes based on occurrence probabilities using repetitive feedbacks. Participants learn the task according to the cue-outcome relationship, and try to gain in depth understanding of this relationship throughout the experiment. While learning is at the highest level, people rely on their working memory. In this study 20 participants were presented a probability learning task, and their prefrontal cortex activity was measur...
Gene function inference from expression using probabilistic topic models
Tercan, Bahar; Acar, Aybar Can; Department of Medical Informatics (2016)
The main aim of this study is to develop a probabilistic biclustering approach which can help to elaborate on the question "Can we determine the biological context of a sample (tissue/condition etc.) using expression data and associate the contexts with annotation databases like Gene Ontology, KEGG and HUGE to discover annotations (like cell division, metabolic process, illness etc.) for these contexts?". We applied a nonparametric probabilistic topic model, Hierarchical Dirichlet Process (HDP), which was o...
Citation Formats
IEEE
ACM
APA
CHICAGO
MLA
BibTeX
S. Kazak,
Olasılık konusu öğrencilere neden zor gelmektedir?
2009.