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

4.8
étoiles
1,937 évaluations
361 avis

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

ZC

Aug 24, 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

Mar 01, 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 sur 355 Avis pour Statistiques déductives

par Mrigank S A

May 18, 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

Sep 17, 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

May 02, 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

Jan 07, 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.

par Chen N

Mar 15, 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 :)

par zhenyue z

May 25, 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.

par Peter H

Sep 29, 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.

par Ylenia V

Jun 24, 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.

par Kirti K

May 30, 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.

par Krishnamurthy P

Feb 25, 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.

par Akshay K

Jul 03, 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

par Bruno R S

Dec 18, 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.

par Ann N

Jun 29, 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.

par Long D H

Apr 29, 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.

par Hrithik S

Jul 06, 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.

par Prakhar P

Jan 22, 2019

The concepts are explained in a very simple and effective manner with the help of a case study. Background knowledge of R will be very handy if one wants to cover the topics at a faster rate.

par PAUL M

Dec 13, 2017

Very well taught. Student given an opportunity to explore and search for ways to solve problems by themselves. Professor (mentor) and other students always ready to help should you get stuck!

par Arnold T

Aug 31, 2016

The professor is one of the best instructers I've seen. I've struggled to understand these concepts before but this course just set everything straight. Lots of content to practice with too.

par Chin J L

Mar 22, 2018

The subjects are presented very clearly and the lectures very enjoyable to watch. Although I have a basic knowledge on the subject this course improved my understanding on the subject.

par Wang Y

Oct 18, 2016

I learnt a lot about inferential statistics from this course. It help me to understand better why I used one inferential method instead of another, and the assumptions and conditions.

par María J O

Sep 01, 2016

This course is really well prepared. The material is very clear and good resources are provided for further learning. The quizzes and labs are always relevant to the course content.

par anthony w

Nov 02, 2017

I really enjoyed this course and found the professors lectures better structured and clearer. I also like (and needed) the variety of datasets she used for instruction. Thank you!!

par Gary H

Sep 25, 2017

This was hard; The Statistics part became harder and harder and the R part seemed to not keep up with it. You need to learn more R on your own, which is a challenge - there are man

par David H

Jun 27, 2017

What I learned best is not the formula, but the approach to test the conditions, the discussion of source of potential bias, the selection of inferential statistics methods.

par Peeyush J

Jan 27, 2018

Very good course for understanding the basic concept of statistical inference. Effective teaching by providing suitable examples, test and assignment. Thanks faculty !!!