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Avis et commentaires pour d'étudiants pour Introduction to Probability and Data with R par Université Duke

4.7
étoiles
4,946 évaluations
1,191 avis

À propos du cours

This course introduces you to sampling and exploring data, as well as basic probability theory and Bayes' rule. You will examine various types of sampling methods, and discuss how such methods can impact the scope of inference. A variety of exploratory data analysis techniques will be covered, including numeric summary statistics and basic data visualization. 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 concepts and techniques in this course will serve as building blocks for the inference and modeling courses in the Specialization....

Meilleurs avis

AM
7 févr. 2021

After trying several courses to get me started with R programming, this one came to the rescue and had all the info I wanted. It also provides a great way to practice through labs and a final project!

AA
24 févr. 2021

I always wanted to learn statistics from scratch, but I never had a good university teacher. Here I found a good teacher and also the opportunity to learn whenever I want ( and skipping parts I knew!)

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51 - 75 sur 1,173 Avis pour Introduction to Probability and Data with R

par Katherine T

15 juin 2017

I really enjoyed this course - the instruction and materials were high quality and very helpful in clarifying statistical concepts that had seemed unnecessarily confusing to me prior to taking this course. The assignments were very helpful in teaching R, with the final assignment requiring slightly more familiarity in R than the first 4 weeks prepare students for. My advice for students who take this course is that if you have the time in the first 4 weeks, try to learn a bit more than is minimally required in R to be best prepared for the final project. Overall a great course!

par Bharat K

18 juil. 2016

One of the well made MOOCs. There are many courses in Coursera taught by good professors from good universities but are badly designed for an MOOC environment making it a bad experience. This course is really well designed. The contents is modular and lectures are split into easy to grasp chunks. The weekly lab exercises using R using real datasets is a plus. Though not much of R syntax is taught and it is up to us to explore(understandable since the goal of this course is not to teach R). The final project was a bit challenging but fun. The course 'mentors' are helpful.

par William S H

18 mai 2020

Very clear and simple to follow along with. This allowed me to brush up on and formalize my stats knowledge a bit more, but I have no doubt that it would be good for a complete newbie. The lectures are succinct and comprehensive and there is a free online textbook for reinforcement as needed. Moreover, the R labs and project really add a LOT to the course, jumpstarting my knowledge of R, R studio, and how to perform some exploratory data analysis. For prospective data science folks, I recommend taking this in conjunction with The Data Scientist's Toolbox.

par Mark F C

30 juin 2017

Great intro course into both stats and R. I especially like how the videos succinctly explain all the concepts in such short lessons, supplemented by the thorough readings that provide more details and the lessons in R.

The data analysis project, while challenging at first, did a good job of providing an interesting data set and forcing us to come up with the rest. If I had my hand held all the way through, I wouldn't have learned as much as I did, as I was forced to look throughout the internet for code to perform functions I was anxious to use.

par Veerawut A

10 avr. 2019

This is an excellent course to lay down the ground works for further courses within the specialization. You'll get the necessary introduction to statistics along with beginner level knowledge of the statistical tool R package. While certain area of the course, especially week 5 data analysis project, can be challenging. Know that the discussion forum is always there to help you if you are stuck. The quiz and project is never outside the scope of the course materials. Totally would recommend this course for anyone who interested in statistics.

par Erin A

18 oct. 2019

This course made principles of probability interesting, going beyond the usual examples of coin flips, dice rolls, and card draws. The discussion about the limits of which observed trends can be applied to a greater population of interest was clear and the project gave us an opportunity to put it into practice ourselves. I especially liked the opportunity to ask questions of a large dataset and generate tables of data and graphs to illustrate these tables a bit more clearly. I feel I now have a good foundation upon which to build!

par Monique O V

19 févr. 2020

I highly recommend this instructor and this course! Excellent teaching, good practical examples that show you why statistics are such a useful technique, very clear lectures, good step-by-step explanations of solving example problems. The free textbook (written by the instructor) that accompanies the course is likewise excellent. If you watch the lectures, read the book, do the problem exercises at the end of each section of the book, you will pick up an excellent grounding in statistics.

par Lenka B

24 avr. 2020

I enjoyed the course very much. I appreciated that the course was teaching practical skills that we could immediately apply to solve problems using real data. I was pleasantly surprised that I was able to explore a big dataset from a US survey, formulate my own questions and actually get some answers! Although I found some of the assignments challenging, and I spent on them more time than expected, it was worth it. I guess it helps to know some basics of R programming beforehand.

par Richard N B A

13 avr. 2016

Interesting, information-dense and well presented lectures by someone who obviously has a deep understanding of the topics and who is passionate about teaching the subject. Added to that: a great course textbook and useful R tutorials with a focus on commonly used libraries such as dplyr and ggplot. Beginner and intermediate statistics students, as well as teachers interested in the presentation of statistics theory and practice, can't go wrong with this course.

par Nur H J

24 sept. 2020

The lecture were great and it was easy to digest and remember. At first, it was hard trying to familiarise with R and understanding the technical aspects of R programming but I survived the course and was able to complete the assignment. I would say that the most learning came from my own peers through the discussion forums and peer-review assignment. This course has definitely increased my interest in learning R and performing data analysis with R.

par Sujoy S

18 oct. 2017

Instructor is excellent. While I bought the recommended book I hardly referred to it. The response from the mentors (especially David Hood) in the discussion forum to every question has been very prompt and precise. Overall the combination of the Instructor, the illustrations in the videos, the practice tests and the online support of the mentors makes it an ideal online course. I was able to finish this despite being in a fairly demanding full time

par LIZBETH P B C

22 juil. 2020

Al enfrentarme al proyecto final me di cuenta que quería hacer muchas cosas y no contaba con las herramientas, tal vez porque lo que quería realizar se encontraba en un nivel más avanzado así que accedí a buscar más info en internet. Descubrí que podemos buscar más ayuda por fuera del curso y que no debe ser una limitación, aunque me tomó días completar mi proyecto traté de hacerlo lo mejor posible. Muchas gracias por lo aprendido en este curso!

par Awani B

20 juil. 2020

The course was very good! The instructor explained the concepts very clearly. She also took effort to differentiate between commonly confused concepts. The final project in R was tough, but through it I really used my own knowledge to approach a question like an actual research project. I also learned to search for R commands that were not taught in the course with the help of the RStudio cheatsheets and online platforms like Stack Exchange.

par roxana t

10 févr. 2020

Excellent introduction to R and probability. The lectures were very clear and well structured.

I particularly enjoyed the final project, and the fact that we were given free reign over the research topics: what questions to ask, and also how to structure the answers. It is an great opportunity to further the knowledge acquired during the lectures and become familiar with R capabilities. The feedback from the other students was very valuable.

par Aditya

25 mai 2021

It is the best course I have taken till now on Coursera. Having a python background, my only concern was that I would have to learn R for this course and I am sure there are others in the same boat. My advice to them - Take this course anyway. You will build a strong grasp on probability, and also end up learning R (Understanding its basics barely takes time since the syntax is just as easy as Python) and open up a myriad of opportunities!

par Cecilia L

25 juin 2019

Mine Cetinkeya-Rundel' explains the concepts in a very very clear manner.

I actually started with other statistics course on Coursera. But found it going too fast. A lot of ideas were poorly presented. I was quite frustrated with one topic, so I searched online for detail elaboration and found Mine Cetinkeya-Rundel's youtube videos. Her deliberate explanation built my confidence. Hence now I'm at her class and I really enjoy it overall.

par HEMANT S G

6 avr. 2018

This course is really helpful to have a better understanding of fundamentals of probability and data statistics. The course mainly focuses on basic concepts of probability and how to apply them. The assignment provided was very helpful and challenging. The peer graded project allows me to evaluate my fellow course mates which really boost my confidence as make me feel like an invigilator and provide the basis for my academic career.

par Noah

1 oct. 2017

This is a very good course to learn (or review) the foundations of statistics and how R can be a great companion tool to augment a solid understanding of the topic.

The instructor speaks clearly and at a fast enough pace that there is no time to pay attention to anything else. I appreciated the lectures, slides and there is a free PDF book which is also well written! I am looking forward to the other courses in this series!

par Kimberly G

5 sept. 2017

The course was really beneficial to someone with no R experience. Having taking statistics courses before I was mainly interested in the use of R for computational uses of statistics and analysis. The course provided those means and more. I'd recommend using RStudio on your own computer versus the Data Camp tutorials however as when it comes to the project at the end, you'll be extra comfortable with the use of RStudio.

par Jeremy M

18 sept. 2021

V​ery well-designed course with interesting topics. The supplementary reading proved essential for me. The recommended times are not very reliable. The only down side is the extent to which R is used (not enough in my opinion) and I did not feel well prepared for the final assignment but this may be due to the type of research questions I set myself. Overall, very interesting and I am glad to have done this course.

par Bruno P

29 mai 2019

It's a great course for who want to learn applied statistics using R. The main topics are deeply explained. Exercises and other materials, like the OpenIntro book, are challenging. And final project gives you and idea of your new skills levels. The only attention point, for me, was the unbalance between the expected time to do the final project and the real demand. But it was a very, very rich experience for me.

par Lawrence K

10 juin 2021

The course provides a solid introduction to probability and statistics and the instructor clearly explains all the topics. The quizzes and labs were very useful in reinforcing the concepts that were covered in the course. I was a little disappointed that R is used instead of Python but after using R Studio, which is a very nice tool, I can appreciate that R may make the course more accessible.

par Muhammad N

26 mars 2021

Wonderful course. Provides direction but after that is pretty much self-driven with little spoon feeding, which is how courses should be. If you're looking to learn R this may not be the best place to start since this course doesn't talk much about base R and goes straight to tidyverse packages.

I think links to more mathematical proofs for some concepts would be useful for advanced learners.

par Mabeesha P W

14 juin 2020

Everything is clear and well organized. But, the final assignment might be little bit difficult for a beginner. The estimated time for that is 2 hours but I think it would take more than 2 hours for a beginner (A day or a two). It would be great if there are more explanations and guidance for the last assignment. But, anyone would be able to complete if he/she has enough time to spare.

par Sandra J G M

30 juin 2020

I really liked this course, it is very well organised and the explanations are good and sufficient. However, this is not a course for someone who haven't work with R before. You need to have at least some basics of R to complete the labs and the final assignment. It was not easy to complete the final assignment but absolutely worth the effort. I learned a lot during this course.