Back to Introduction to Probability and Data with R

4.7

stars

4,360 ratings

•

1,021 reviews

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....

AA

Jan 24, 2018

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.

HD

Mar 31, 2018

The tutor makes it really simple. The given examples really helped to understand the concepts and apply it to a wide range of problems. Thank you for this. Wish I could complete the assignments too.

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By Ihor F

•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

•Jun 09, 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 Deleted A

•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

•Jun 30, 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

•Jan 07, 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

•Aug 04, 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

•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

•Oct 05, 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 a e r

•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

•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 Khaleel O

•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

•Nov 30, 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 Ying T

•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 Sarah G

•Feb 02, 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

•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

•Aug 02, 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

•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.

By Tomasz J

•May 26, 2017

Very good introduction to statistics, even for those already forgot maths.

Do not take this course as introduction to R. The course does not explain basics of R (e.g. lists vs vectors, data_frame vs data.frame). I'd suggest anyone to take an introduction to R first or simultaneously with this course.

By Eddie A

•Aug 17, 2020

This is a nice intro with some good lectures. My only criticism is that the estimated reading times and the estimated time for the week 5 projects were way off, for me at least. I suspect that, if you're starting from scratch at stats, they will be way off for you as well.

By Jorge F M

•Aug 21, 2020

I would separate my feedback en two ways. First, I think is a good basics statistics course. but second, I feel is a bit weak in R topics. Its mean, it does not prepare you well for the last project. It could be stongest in R codes, plots, etc. througth the first 4 weeks.

By 闫龙

•Aug 27, 2018

In general , I think this course is very useful and is well designed, I've learned a lot from it.

However, I think it would be better if students are provided with video lesson about Rstudio , it will help to understand R programming especially for the beginner.

By Bruno D G

•Jan 11, 2019

Very clear and well presented course. Best course in stats I had in my life. I removed one star as the time suggested for studying and doing the assignment is well over what is suggested in the course. Make sure that you have plenty of time in front of you :o)

By Felix H

•Sep 22, 2017

Concise introduction to the field, easy to grasp and hands-on. A bit shallow on the theoretical side (optional material would be nice), you just learn what you need and no more. Practical assignments are well designed and give you a great introduction to R.

By Liew H P

•Sep 18, 2017

I had some statistics background in my undergraduate training. While my primary focus of taking this course was learning R, I manage to learn some new things too. Through the course, I was able to learn very basic codes and would love to continue to do so.

By Marta C

•Oct 09, 2018

The materials and lectures were very good and detailed regarding probabilities and data. I felt the difficulty of the final project (in particular with regards to the R component) was not adequate for a beginners course and it required a lot of research.

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