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أ.1 |
Understand the philosophy of Bayesian statistic model |
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أ.2 |
Understand Bayesian model for numerous common data analysis situations , including prior elicitation . |
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أ.3 |
Use software such as R to implement Bayesian analyses . |
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أ.4 |
Understand assessing model quality and Bayesian analysis for two or more sample models . |
ب. (Mental skills)
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ب.1 |
Student should be able to compute Baye’s law . |
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ب.2 |
Student should be able to conduct Bayesian analysis for one sample . |
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ب.3 |
Student should be able to conduct Bayesian linear models . |
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ب.4 |
Student should be able to assess Bayesian model quality . |
جـ - (Practical & professional skills)
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ج.1 |
The ability to find the suitable Bayesian linear models. |
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ج.2 |
The ability to run Monte-carlo methods using R . |
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ج.3 |
The ability to identify the general classes of prior distributions . |
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ج.4 |
The ability to apply Bayesian analysis for two and k-sample models. |
د - (Generic and transferable skills)
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د.1 |
Student will be able to apply different Bayesian techniques. |
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د.2 |
Student will be to find different types of priors distributions. |
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د.3 |
Student will be able to assess Bayesian model quality . |
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د.4 |
Establish a competitive environment between students. |
Teaching and learning methods
.Lectures
· Exercises andpractical applications using statistical programs
Methods of assessments
(Assessment table)
Rating No. | Evaluation methods | Evaluation Duration | Evaluation weight | Percentage | Rating Date (Week) | Reviews |
First Assessment | First Midterm Exam | Two hours |
| 25% | Sixth week |
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Second Assessment | Second Midterm Exam | Two hours |
| 25% | Week Eleven |
|
Final Evaluation | Final Exam | Two hours |
| %50 | Final Exams Week |
|
Total | 100 degree | 100% | ||||
Course (contents)
Scientific topic | Number of Hours | Lecture | laboratory | Exercises |
Review of statistical concepts | 10 | 6 | 4 | 2 |
Beesel analysisSingle-sample models | 10 | 6 | 4 | 2 |
Linear models according to Bayes' philosophy | 10 | 6 | 4 | 2 |
First Exam |
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Prior and subsequent distributions in general | 10 | 6 | 4 | 2 |
Hypothesis test according to the Beese method | 10 | 6 | 4 | 2 |
Bayes's analysis of linear models | 15 | 10 | 5 | 3 |
Second Exam |
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Some simulation methods using a statistical program | 5 | 4 | 1 | 1 |
(References)
Bibliography | Publisher | Version | Author | Where it is located |
Rapporteur notes | Memoirs of the professor |
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Textbooks | Bayesian methods | 2008 | Jeff Gill Chapman and Hall |
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Help Books | Bayesian data analysis | 2009 | Gelman, Carlin, Stren, and Rubin, Chapman and hall |
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Scientific Journals | ||||
Internet Sites | ||||
Other |
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