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Learner Reviews & Feedback for Introduction to Probability and Data with R by Duke University

4.7
stars
5,562 ratings

About the Course

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....

Top reviews

AA

Feb 24, 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!)

AM

Feb 7, 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!

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1001 - 1025 of 1,306 Reviews for Introduction to Probability and Data with R

By Tom B

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Jan 16, 2018

Great introduction/review of basic stats concepts. I think the course designers assume a knowledge of/familiarity with R beyond what they claim in the Course Description. The weekly labs were somewhat helpful, but could benefit from providing the students with a bit more instruction on the functions of R. The learning curve during the Week 5 project was a little steep for a complete novice like me, but overall I found this course worthwhile.

By Alycia K

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Mar 11, 2018

I had to drop this course because I had too many other things on my plate, but hope to enroll again another time. I thought the course was well structured, with very good examples, or explanations, of experiment design. Thanks to the instructors for providing free access to external materials. I thoroughly enjoyed what I was learning. Currently, the only reason I didn't give 5 stars is because of the trouble I kept having with R Studio.

By A W

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Aug 24, 2016

The course videos are good, but the R programming is not well explained. I've enrolled in other Coursera courses that use R, Python or Octave, and they all provide clear demo videos for beginners to get up to standard with the code. This course doesn't do that so it's not a good intro to R, which is a shame because working in statistics these days is all about using R and similar tools so there should be a stronger emphasis on that.

By Sam P

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Jul 21, 2020

Overall, I think the lessons, the lectures and exercises were presented in a very clean and effective way. Unfortunately, the research project was a real leap in terms of cleaning data and working within R. I did not feel that exercises adequately prepared one for the final project. I think this either needs to be scaled back or there needs to be far more discussion and practice with handing R data before the project.

By Ihor F

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Dec 28, 2016

Presentation of the content, course slides and labs are best from what I've seen on Coursera. The only downside was that to my feeling the final project and the course content are somehow disconnected. The course itself deals with introduction to probability, while final project is EDA. I don't think there was enough materials on EDA in the course, so the final project took more effort and was confusing at first.

By Laura P A M

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Jun 9, 2020

Me gustó mucho el curso y siento que aprendí bastante sobre cómo hacer visualizaciones con R.

Sin embargo recomiendo que para el proyecto enseñen un poco mejor cómo transformar el archivo Rmd en HTLM.

I really liked the course and I feel like I learned a lot about how to make visualizations with R.

However I recommend that for the project they teach a little better how to transform the Rmd file into HTLM.

By Sina S H

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Oct 5, 2020

I enjoyed the course very much and found its implementation very clear. The intermediate questions and the quizzes helped to solidify the learning content. Dr. Mine Çetinkaya-Rundel is very sympathetic and it' s easy to follow her explanations. The final assignment, however, was relatively difficult and definitely took more time than was indicated. All in all, I would recommend the course.

By Joseph A

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Jan 1, 2021

I was able to equip myself with basic statistical knowledge through this course. I do feel like the R program could be taught a little bit better. But overall, I am very comfortable with the course content and I cant wait to keep learning and use all that I have learned in the upcoming projects. I especially liked the peer-reviewing part as I was getting more insights into other's works.

By Deleted A

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Jun 26, 2017

Really good foundation course for those who aren't familiar to statistics and gives out great resources to learn or refresh some material. For the assignments, I like how they give an option of either doing it from the DataCamp website or RStudio. I wish there was somewhat a better way of understanding the R libraries in the assignment, but I just don't know what. Overall, I love it.

By Kanchan K

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Jun 29, 2017

This course enables one to start right from basics and develop strong fundamentals in exploratory data analysis. One thing that could be improved is providing for more "R programming" commands or reference materials which can be used by the learner to gather more variations of the commands used in that section and thereby improve code and formatting of plots/graphs.

By Bryan L

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Jan 7, 2020

This is a useful statistical course for anyone who seeks to gain a basic understanding of probability. The R coding assignments are especially useful but one could benefit more if they already knew how certain functions works in R. The dplyr package is especially emphasized and I suggests going to Youtube to know the main functions that are used for data wrangling.

By Ziyue L

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Aug 4, 2020

It is a good introductory level course and I appreciate the instructor's hard work. Two suggestions though. It would be more convenient for us, if you could compress all the lecture slides into one or four files. Besides, peer reviewed project was less unsatisfied. I would prefer to receive grades and comments from the lecturer or mentors, even if pay for it.

By Christopher T

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Aug 20, 2016

Solid and efficient introduction to content, does not do enough teaching in R for the final project - which is *fine* because finding things out for yourself is the best way to learn, but R help online is often so dense that it's not that helpful to a beginner. More responsive mentors - especially nearer the end of the course - would be really helpful.

By Robert W

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Oct 5, 2019

This course is a very good introduction to statistics. The lectures are well paced and engaging. The reading materials augment the lectures nicely by providing more details and workable exercises. There is a new edition of the reference book and the lecture material has not been updated to match the new edition, but the previous editions are available.

By Ahmed I

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Sep 18, 2017

Very good course on Statistics with application in the R programming language ,a great intro for anyone who want to understand statistical concepts used in research , data science.

Although the course require no background in R , I would advise to take an introduction in R programming before hand in order to be able to finish the final project easily .

By Ashley T

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Sep 17, 2019

In my opinion, the final assignment could have been more effectively and meaningfully answered if students have had prior knowledge in data wrangling/ cleaning in R. I don't think this information was made known throughout the course. Otherwise, this course provided a good overview on the fundamentals of basic statistical visualisation and analysis!

By Lostfinger F

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Jan 16, 2021

It was very helpful, I like the course rhythm, how they constructed in a systematic way, I have really learned a lot!

however! As new to R, it took me too much time figuring out some very basic operations, I don’t feel I can get efficient help about technical problems here. If there were some video instructions about R, would ne very very nice.

By Khaleel O

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Dec 19, 2017

The course content, resources and teaching were very good but the course is much more demanding than advertised. The course was advertised for Beginners but in truth it is much more for students of Intermediate Skill and Experience. As a working adult I would have preferred more realistic, expected completion timelines for the tasks.

By James F

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Nov 29, 2017

The course was good but I found the final project to be quite disjoint from the course work. The course included a lot of normal approximation to binomial distribution and calculating probabilities based on binomial draws. The final project seemed very much directed towards looking for correlations in data and mastering ggplot2!

By Eddie T

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Jul 11, 2017

The content is pretty good especially with the concepts well-explained by Dr. Mine, in my opinion, which is much better than John Hopkins' series. However, the R programming assignment is not designed for beginners and it's quite often to get stuck at the final project. For this reason, I gave 4 star for this course.

By Davor P

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Jan 3, 2021

When reviewing peer assignments I got the impression that many of them (2/3 of my reviews) knew the review questions before submitting their work. This was kind of annoying when reviewing because I got the impression that I was not reviewing a research study on the data but instead a question and answer document.

By Sarah G

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Feb 2, 2017

Good professor, good exercises to review what you've learned.

My only complaint - if considered that - is that R was difficult for me to learn and work with, especially when I'll be using SPSS for my own statistical needs moving forward. I'd like for there to be an option within the course to use SPSS instead of R.

By Bruno A

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Feb 18, 2020

Good introductory course, nicely blending stats and R-coding.

The R-coding is a "take the plunge" approach (with a good example to help before the final assignment): this creates first some pain for those who knew nothing about R at the beginning of the course, but this makes for very good practise in the end.

By Justina N

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Aug 2, 2020

I learned a lot of this i should have known during earlier statistics courses. The founding knowledge is well laid out and structured. The pace made me feel both fully in control and slightly out of depth at the same time. This made it an interesting course that made me race through it (in a positive way).

By Anne E

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Aug 13, 2018

Good overview. My only misunderstanding was about the Markdown document that wasn't functional until I changed the format (bottom right in the source, as R Markdown) and the "knitting" that I still haven't figured out. Otherwise very clear, and lots of great examples to illustrate and fix the knowledge.