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Volver a estadísticas por inferencias

Opiniones y comentarios de aprendices correspondientes a estadísticas por inferencias por parte de Universidad Duke

4.8
estrellas
2,295 calificaciones
420 reseña

Acerca del Curso

This course covers commonly used statistical inference methods for numerical and categorical data. You will learn how to set up and perform hypothesis tests, interpret p-values, and report the results of your analysis in a way that is interpretable for clients or the public. Using numerous data examples, you will learn to report estimates of quantities in a way that expresses the uncertainty of the quantity of interest. You will be guided through installing and using R and RStudio (free statistical software), and will use this software for lab exercises and a final project. The course introduces practical tools for performing data analysis and explores the fundamental concepts necessary to interpret and report results for both categorical and numerical data...

Principales reseñas

ZC
23 de ago. de 2017

This course by Professor Çetinkaya-Rundel is awesome because it is taught in a very clear and vivid way. Lab section and forum are so dope that I love them so much! Definitely strong recommendation!!!

MN
28 de feb. de 2017

Great course. If you put in a little effort, you will come out with a lot of new knowledge. I recommend using the book after you have seen the movies. It gives a deeper picture of how it works. Great!

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51 - 75 de 415 revisiones para estadísticas por inferencias

por Lucía C

9 de jun. de 2020

Great course, really useful and amazing explanations by Dr. Mine Çetinkaya-Rundel. I learnt a lot and the data we are given to analyse in the final project is really interesting. Totally recommend this course to anyone interested in working with stats in R

por Thomas B

31 de oct. de 2016

Really good course on inference. The statistical tools and the reasons why those tools are used, are explained well. I am looking forward to the last week's exercise and the next courses of the series. This one is a bit more difficult than the first course.

por Bryan L

11 de may. de 2020

The content of the course of was informative and clear. The lab sessions were really useful in evaluating one's understanding of the topic while introducing useful functions in R though more emphasis could have been placed on ANOVA during the lab sessions.

por Mariia D

10 de ene. de 2021

Great course, good for begginners or those who (like me) wants to gather separate pieces of knowledge into a solid picture.

Good examples, well explained, not too much calculus, appropriate quizzes. Reading a book accompanying course is also very helpful.

por Ako A A

18 de may. de 2017

I found this course very exciting. The knowledge it imparts is so invaluable that I am keen to complete course after course. The lecturer also has a charm with which she holds your attention and makes learning quite a breeze. I give 5 stars unreservedly

por Muhammad F

8 de abr. de 2020

The course gives me an understanding of inference for numerical and categorical data. The example as well as the project assignment use real-world data which prepares the students to use the technique taught in the course to tackle real-world problems.

por Cynthia J J

28 de dic. de 2019

This is a wonderful course with a very good instructor. Her explanations and observations are clear, concise and on point. I am so glad I am taking this course because now the mystery of statistics is over for me. I finally understand this logic.

por Satoshi

17 de mar. de 2020

This course is brilliant. It's straight forward and a lot but moderate practices. A quiz, working on R, and discussion forums assist your understanding of the contents. I am not a native English speaker, but I could enjoy this learning. Thank you.

por Patricia B

4 de ago. de 2017

This course is very complete. It helps, even who have already studied Statistics on university level before, to really understand the concepts on inference. The labs are cleverly built to help the student to use R and apply the concepts learned.

por Mrigank S

18 de may. de 2016

The course content is very comprehensive and all the concepts have been explained clearly. This course has helped me a lot in building my statistics skill. I would recommend this course to anybody who is looking to learn inferntial Statistics.

por Subodh C A

16 de sep. de 2017

An excellent course that was just right for me. I have started on course 3 and hope to complete the Capstone project eventually. My thanks to Prof. Cetinkay-Rundel and other members of the Coursera team for giving me this opportunity.

por Luo Y

2 de may. de 2018

Very good course! With the course and the book you can get equipped with all the basic skilled needed for inference. Strongly recommended!

It took longer hours to study for me than the estimated time provided by coursera though

por Andreas Z

7 de ene. de 2018

This is a hands-on to the point introduction to hypothesis testing. The perfect course for showing "how it works" without bombarding the reader with maths. Also very well suited for relearning the material after 15+ years.

por James H

25 de jul. de 2021

Really good overview of inferential stats such as central limit theorem and T-Tests

The best part of the course is they relate the theory to real world examples and worked through examples that makes the course relatable.

por Chen N

15 de mar. de 2019

Much better than the course offered by John Hopkins University on the same subject. Concepts are clearly explained with detailed examples. Nice course to solidify your statistics skills. And BTW, really cute professor :)

por zhenyue z

25 de may. de 2016

very awesome class for statistics, very clear explanation. recommend for any one who want to know statistics. This inferential class is much better than the one I took from JHU data science course. 5 star recommended.

por Peter H

29 de sep. de 2020

The course is not easy to follow, but you can learn a lot with the practice and R Lab. The Reference book is more clearly explained. Suggest starting to learn from the first unit, then familiar with R. That's helpful.

por Ylenia V M

24 de jun. de 2020

The course was very well organized and with detailed explanations and exercises offered by the Professor. Lots of practice with R was included, which makes it extremely useful for coding and future jobs in this field.

por Kirti K

30 de may. de 2020

This course was an eye-opener for drawing inferences from huge data sets using R. The concepts were so clearly explained with many examples, that it is now quite easy to implement the tools for real observations.

por Krishnamurthy P

25 de feb. de 2017

It is my first course. Two weeks have passed and I am learning and relearning. The professor is really good and I am motivated every day to be on track. I registered for the course. I wish to pass the course.

por Akshay K

3 de jul. de 2020

The course structure was up to the point, not more not less. and it was more of a practical approach rather than high-level theoretical proofs. I really enjoyed this course it was a perfectly balanced course

por Bruno R S

18 de dic. de 2017

Excellent course for one seeking to understand the basics of Inferential. It as difficult as it sounds, but manageable and the additional course materials are enough for the intermediate level self study.

por Ann N

29 de jun. de 2017

Quite challenging, but I truly enjoy the Final project.

Video was fast, and a lot of Video to learn and ponder from :( not a bad thing, but I feel constantly under pressure. I learned A LOT!!.

Thank you.

por Long D H

29 de abr. de 2020

This has been the second course in this specialization and things are going smoothly.

The greatest thing is the final projects which give us freedom on what we want to figure out with given data set.

por Hrithik S

6 de jul. de 2020

Very nicely designed course and it also progresses very well. If higher mathematics would be involved in it, the course has the ability to replace many college's statistical inference's classes.