An introductory handbook of Bayesian thinking /
As Bayesian techniques become more common across a variety of fields, it becomes important for experts in those fields to understand those methods. An Introductory Handbook of Bayesian Thinking brings Bayesian thinking and methods to a wide audience beyond the mathematical sciences. Appropriate for...
-д хадгалсан:
| Үндсэн зохиолч: | |
|---|---|
| Формат: | Цахим Цахим ном |
| Хэл сонгох: | англи |
| Хэвлэсэн: |
[London] :
Academic Press,
[2025]
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| Нөхцлүүд: | |
| Онлайн хандалт: | ScienceDirect |
| Шошгууд: |
Шошго нэмэх
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MARC
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| 100 | 1 | |a Loftus, Stephen C., |e author. | |
| 245 | 1 | 3 | |a An introductory handbook of Bayesian thinking / |c Stephen C. Loftus. |
| 264 | 1 | |a [London] : |b Academic Press, |c [2025] | |
| 300 | |a 1 online resource. | ||
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| 588 | 0 | |a Online resource; title from PDF title page (ScienceDirect, viewed July 1, 2024). | |
| 520 | |a As Bayesian techniques become more common across a variety of fields, it becomes important for experts in those fields to understand those methods. An Introductory Handbook of Bayesian Thinking brings Bayesian thinking and methods to a wide audience beyond the mathematical sciences. Appropriate for students with some background in calculus and introductory statistics, particularly for nonstatisticians with a sufficient mathematical background, the text provides a gentle introduction to Bayesian ideas with a wide array of supporting examples from a variety of fields. Utilizes real datasets to illustrate Bayesian models and their results Guides readers on coding Bayesian models using the statistical software R, including a helpful introduction and supporting online resource Appropriate for an undergraduate statistics course, as well as for non-statisticians with sufficient mathematical background (integral and differential Calculus and an introductory Statistics course) Covers any more advanced topics which readers may not be familiar with--such as the basic idea of vectors and matrices--as much as needed in order to foster understanding of core concepts. | ||
| 650 | 0 | |a Bayesian statistical decision theory |v Handbooks, manuals, etc. | |
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