Chevron Left
Zurück zu Bayessche Statistik

Kursteilnehmer-Bewertung und -Feedback für Bayessche Statistik von Duke University

3.8
Sterne
760 Bewertungen
246 Bewertungen

Über den Kurs

This course describes Bayesian statistics, in which one's inferences about parameters or hypotheses are updated as evidence accumulates. You will learn to use Bayes’ rule to transform prior probabilities into posterior probabilities, and be introduced to the underlying theory and perspective of the Bayesian paradigm. The course will apply Bayesian methods to several practical problems, to show end-to-end Bayesian analyses that move from framing the question to building models to eliciting prior probabilities to implementing in R (free statistical software) the final posterior distribution. Additionally, the course will introduce credible regions, Bayesian comparisons of means and proportions, Bayesian regression and inference using multiple models, and discussion of Bayesian prediction. We assume learners in this course have background knowledge equivalent to what is covered in the earlier three courses in this specialization: "Introduction to Probability and Data," "Inferential Statistics," and "Linear Regression and Modeling."...

Top-Bewertungen

RR
20. Sep. 2017

Great course. Difficult to apprehend sometimes as the Frequentist paradigm is learned first but once you get it, it is really amazing to see the believe update in action with data.

GH
9. Apr. 2018

I like this course a lot. Explanations are clear and much of the (unnecessarily heavyweight) maths is glossed over. I particularly liked the sections on Bayesian model selection.

Filtern nach:

51 - 75 von 239 Bewertungen für Bayessche Statistik

von Mark P

24. Okt. 2017

Slightly math heavy at times but the practical labs were awesome. I thoroughly enjoyed the final modeling assignment as well

von Michael B

26. Okt. 2016

Great course with clear instruction and a final peer-review project with clear expectations and explanations.

von Melesio C S

22. Aug. 2019

It was a very interesting course, i really recommend it if you want to get into bayesian statistics.

von Jinwoo L

10. Juli 2019

Literally best concise and brief explanation. Dr. Rundel wakes my intellectual vitality up again!

von Yan Q

22. Dez. 2016

very helpful, however there is no recourse or recommend information for reference textbook.

von fanjieqi

3. Jan. 2018

Pretty good, but some parts is a little difficult. I need to watch these videos more.

von Julio C L J

18. Dez. 2017

The course was hard, because the topic is quite difficult. I missed the readings.

von Perry C

25. Sep. 2017

I didn't understand everything but I learned more than I ever thought I would.

von Parab N S

2. Okt. 2019

An excellent course by Professor Rundel and her team on Bayesian Statistics.

von Zhen X

26. Nov. 2018

Provide bunches of intuition of bayesian statistics. Worthwhile to enroll!

von Himanshu D

19. Feb. 2017

Excellent content. Gives a very different outlook of Bayesian Stats.

von Øyvind M E

24. Mai 2020

Harder than the previous courses but well worth the learning

von Alfonso G D

29. Apr. 2020

Very interesting aproach to statistics in a very clear way

von Aditya G

6. Juni 2020

Course was really good and I enjoyed it a lot. Thank You.

von Buckley O

26. Juli 2020

Great class. Well worth the time investment and effort.

von Hohyun J

20. Juni 2020

Excellent lecture, well structured, easy to understand.

von JULIETH I M S

27. Nov. 2017

Excellent course. Both instructors are really great.

von Ricardo B

24. Nov. 2017

Very comprehensive course on Bayesian Statistics.

von Nandini G

5. Feb. 2021

Best Course under Statistics domain on coursera

von Junyu W

7. Juli 2020

Very organized and detailed offered course

von Ale D

17. Dez. 2017

Hard, but very good first course on Bayesian

von Lou B V

11. Sep. 2020

It was difficult for me yet it is so great.

von Luis A

11. Okt. 2018

Excellent course very clear explenations.

von Matthew L

31. Jan. 2018

Really hard, but absolutely worth it.

von Ananda R

19. Apr. 2017

very difficult but it is interesting