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Avis et commentaires pour d'étudiants pour Statistiques déductives par Université Duke

2,422 évaluations

À propos du cours

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...

Meilleurs avis


28 févr. 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!


23 août 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!!!

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51 - 75 sur 434 Avis pour Statistiques déductives

par Emilio M

4 juin 2020

Very concise and interesting. I was able to brush up many concepts. It is important to indicate to the students, that the materials provided are not enough to create a final project in a meaningful way.

This is because the code to use R is limited to the basics throughout the course. Extra or outside research is necessary to increase R skills.

Many students have technical difficulties, sometimes unusual. Is it possible to address them by expanding an FQA section?

par Dario B

6 nov. 2018

Very interesting material. Statistical inference was one of the great mysteries for me, and it is indeed a technical topic. But the professor does a great job in presenting the material in an intuitive way, giving an awesome introduction. Very interesting real examples too.

Looking forward to have a proof-based equivalent course, though maybe I should focus on a forma probability course first.

par Ondina F P

17 mai 2019

Very good explained course, with lot of useful exercise, so you can be sure to understand the theory. Th practical examples in R are well designed and explained. This is definitely a must for someone interested in statistics, with beginning concepts that you need to keep in mind for further coursers. The teaches is also excellent, explanation and examples are very good. Recommended!

par John F W S

5 nov. 2016

I really enjoyed this course, it is pitched at just the right level for someone who is sometimes busy with part time work. It does ask that when you study, you study well. I've not learned any programming before these courses, so sometimes my knowledge of R is lacking. But it is rewarding to learn R to really see these statistical ideas come alive.

par jose m

25 mai 2017

If you are new to this, get ready to sweat. This course teaches many many concepts and if you think that it tiptoes around it you will be surprised. You might walk away and forget some of the methods and tests since there are too many, but you won't get away without learning to interpret and reasoning absolutely everything that you compute or do.

par Igor S

5 mai 2021

The course is well-paced, covers the relevant topics from the basics and gives you a bit of freedom on the project. The comments made for the first course in this series still stand: there is a lot of statistics and a little R. However, it is not as painful to code as it was during the first course (although still need to google a lot).

par Jesus

16 mai 2016

Great course, the professor is able to explain and articulate complex ideas into a digestible manner. If you ever taken a statistics class you know would know how incredibly rare it is to have such a great professor able to explain the material as well as she does. Thanks you very much Dr. Mine Cetinkaya-Rundel for teaching this course.

par Bruno A

24 mars 2020

Nice refresher course on inference testing, with a broad coverage of the types of variables / analyses.

Not heavy at all on the math side.

Students have to find their tips for R-coding on the Internet for the most part. It is a good way to learn! But we could use more standard tips from the course itself, especially on EDA.

par Jacob T

7 mai 2019

The best online course I have taken so far. It teaches you all the statistical methods you need to do for inference. The lessons are well taught and organized in a way where each lesson builds off the previous. The final project is also a great way to put everything you learned throughout together.

par Amarendra S

26 févr. 2019

Had a great learning experience with in depth knowledge of statistics, inference and hypothesis. Structure of the course helped me grasp things in an organized way. The use of real time data to explain concepts had a great impact in making things easier to understand and relate to things around us.

par José J P A

4 juil. 2016

Excelente curso. Vale totalmente la pena tomarlo. Es muy importante atender la lectura sugerida y tomar notas. Complementando la platica junto con la lectura sugerida estoy seguro que tendrás las herramientas necesarias para iniciar un desarrollo en el ámbito de análisis de datos.

par Praneeth K

17 avr. 2017

The course is structured very well and has some great content, suitable for anyone who is just beginning with statistics in R or if you want a refresher on statistics. Dr. Milne is a great instructor, i have taken some other courses of her's and was never disappointed.

par Lucía C

9 juin 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

par Thomas B

31 oct. 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.

par Bryan L

11 mai 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.

par Mariia D

10 janv. 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.

par A A

18 mai 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

par Muhammad F

8 avr. 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.

par Cynthia J J

28 déc. 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.

par Satoshi

17 mars 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.

par Pat B

4 août 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.

par Mrigank S

18 mai 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.

par Subodh C A

16 sept. 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.

par Luo Y

2 mai 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

par Andreas Z

7 janv. 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.