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Introduction to Probability and Data with R に戻る

デューク大学(Duke University) による Introduction to Probability and Data with R の受講者のレビューおよびフィードバック



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....



This course literally taught me a lot, the concepts were beautifully explained but the way it was delivered and overall exercises and the difficulty of problems made it more challenging and enjoying.


Very clearly explained and the pace is awesome! I really enjoy each deadline and l can already see how it is impacting my day to day work and life. I ook forward to completing the course! Thank you.


Introduction to Probability and Data with R: 1051 - 1075 / 1,084 レビュー

by Leif B


I honestly can't recommend this course. The coverage of statistics was fine, and the labs were sufficiently clear, but the final project suffers exactly the same critical flaw as so many other online courses: after a limited exposure to a tool, the student is expected to use that tool in a context that is so different that the original classes are all but useless. In this case, where RStudio worked flawlessly and effortlessly on clean data, the final project doesn't use clean data.

If your goal is to learn statistics without a particular software package, look elsewhere.

If your goal is to learn R & RStudio, I'd have to suggest a more rigorous, step-by-step approach.

by Ghasem B S


I reviewed many concept which I am grateful for, but several thing need to get better. First, all over the course I was waiting to hear about p-values more, as was promised first time but got nothing more on the videos. Second, many question were asked on exam about the material in the book that were supposed to be optional. Third, final projects includes a huge data file which my laptop suffered loading in RStudio every time. If the it is meant to evaluate the students knowledge, a much smaller data would be enough as well. by the way, I appreciate your endeavor.

by Jamison T


Content is not bad. However, peer review system for final project is not great. I had to wait for other students to review mine and wait for other students to submit theirs. How long this is takes is largely dependent on how many students are currently taking the course (which was not enough and so I had to wait). This kind of system for marking should not be done for online courses where you cannot guarantee there are enough users always taking it at the same time. Especially when there are paying users that may have to pay an extra month whilst waiting.



It is a basic level course and I was expecting I will be taught how to use R studio or basic R functions. But instead , difficult R exercises were assigned without prior knowledge/teachings of R. I had to struggle a lot in completing the assignments.

by Laura L M


regular course content was fine for a refresher. what I really wanted was the intro to R. the lab, however, was the WORST. I ended up going to YouTube to figure out half the stuff I needed to do. Why am I paying for that? I was really poorly done.

by Hsueh-han W


Statistics part is fair enough, but R part is absolutely not.

Giving the document of R does not mean teach you. You even have to make a difficult R project in the end of the course, but without any tutorial or example to make so.

by Deanna K


The course materials (book & lectures) are clear enough, but the introduction to and support for using R/RStudio is completely lacking. Unless you already know R/RStudio, steer clear of this course and find another.

by Saishwar T S


Suffered a lot of difficulties with the various material provided as they contain a lot of problems. Data does not load properly for labs, errors in code etc.

by Hanspeter A


Problem is the OpenIntro Statistics 3Rd edition is not available. So Learning Objectives are not possible to follow since 4th edition is not same as 3rd.

by Gabriel C


The book is very good at explaining the concepts clearly, the videos are too confusing, therefore, we must focus on the content of the book.

by Sailaja M


I think that the teaching and tutorials in R should have been included instead of letting the student figure out all the R coding.

by Saumya Arya


The teachers dont focus on teaching R , but rather on only the basics statistics.

by Aaron D


Mediocre. Not much in the way of help for using R

by Arunav C


Very poor explanation skills

by Darrell W



by Alexander C


Before you start this specialization you should check the start date for the final capstone course and make sure that it aligns with the time you anticipate wanting to take it (add a few days for the annoying bottleneck of getting peer reviews back for your assignment in course 4 since you will not be allowed to enroll in course 5 until all of the first four are completed).

When I made it to the capstone course there was a full month until the start date so all of the assignments are locked until then. I am far from the only one this happened to. Others on the forum for the course are complaining about two-month waits. This seems like a naked cash grab since the specialization is a monthly subscription. Honestly, it would be better if they did just surprise you with an extra $50 charge to do the capstone because at least you would have the option of paying and getting started on finishing up the specialization.

Otherwise, the specialization isn't really maintained any more. For the first three courses it doesn't matter much because it's all pretty easy (my rating for the first three would actually be two stars as stand-alone courses probably). In the third week of the fourth course the instructor is swapped out for a new instructor who is utterly incomprehensible, using terms and ideas that haven't actually been introduced. The accompanying text is similarly incomprehensible. I say this as a math person who has subsequently gone to other resources to learn this specific material. The problem is not that the material just gets harder, but that the quality of instruction drops through the floor. So beware of that.

by Paul A


Avoid, this is a crash grab. The instructors don't seem to know a whole lot of R, or are unwilling to teach what they know. Making the labs work is a hassle on itself, not to mention the final assignment outrageous demands come out of nowhere and blindside you.

The introduction of R to the statistics and probability subjects is shallow at best. To learn the same amount of statistics and R on this course; a good textbook, some videos and a tutorial on R will give you better results on a fraction of the time.

The language used on the quizzes and labs is obscure to say the least. You have to navigate through what feels like booby traps in the hopes of figuring out what you're supposed to answer, not to mention the multiple choices are trap them selves. On the quiz feedback it actually said several times, things like: "Although this is partially correct, this other answer is more correct."

The quizzes took me back to my dreaded time in university where the teachers were out to fail you. Allegedly the instructor has a PhD and focused on pedagogy, to be honest I didn't feel this pedagogy approach anywhere and more like a padded resume.

by James B C


By the textbook it appears to be a very vanilla Stat 101 course, chapter 2 of the textbook did cover some conditional probability and Bayes theory otherwise very similar to stat 101 course I took in 1978. In other words, not exactly 21st century data science. Taught at high school / college freshman level (one of the exercises was writing mean and standard deviation with Greek letters -- pure busywork). The textbook inaccurately described a data set with several different data types as a "data matrix" a word usage that conflicts with both linear algebra and the statistical language R. This course is an obsolete and lame intro to statistics; I would recommend instead either Stanford's Introduction to Statistical Learning or the Coursera's Data Science Specialization.

by aparna j


Before assigning such a tough project in week 5 using R, the course should have dealt with R more thoroughly along with theory about probability. Week 5 mentions project to be of 2hrs, but it took me 1 week to understand R all by myself and then complete the assignment somehow. I would say, i chose the wrong course. Highly dissapointed. Should have opted some other course to learn R in depth.

by Michael K


The very first setup of R packages is broken. I paid $49 dollars because I waited 2 days past the 7 day free trial. After spending hours reading through the forums of many people having many different configuration problems, it is clear that the content creators should have fixed these issues on their end. Instead they leave students to figure it out.

by Pamela G


While the videos and quizzes were easy to use, I had extreme difficulty using the DataCamp and could not find any tutorials that would answer my questions. Also, am unable to complete the course because of technical difficulties with RStudio. The course should have more online resources for those with little experience.

by Niharika K


For Beginners, it is very difficult to understand the mechanism of how R works without the video guidance. Though reading is available, but it does not give a good understanding due to the complexities of R.

by Bo W


thanks for your effort to make videos, but this is the first time find a class that i can not submit my answer to check if it is correct or not before my account is upgraded. Disappoint to Coursera and Duke.

by Piotr Z


The course was not very helpful for me, as practical cases with R were poorly developed and the final data capstone project is badly formulated which makes it extremely difficult to pass.

by Manoj G


Speed is very fast for a basic level student. The data explanation and correlation demonstrated is not clear.