Back to Introduction to Probability and Data

4.7

stars

3,799 ratings

•

876 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....

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.

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 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 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 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 fheinrichs

•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.

By Subodh R

•Aug 23, 2018

A perfect course for the introduction to the world of Statistics. I will try to improve upon the review with my further studies and try to look at anything that you might have missed but so far it looks like this course covers all the bases.

By Tibor R

•Jan 29, 2018

The theoretical and practical part is very good, but in the project there are a lot of practical question to confront basically alone, without the needed help. The things were functioning in an unknown way... It was hard - at least to me.

By Nilesh W

•Sep 06, 2019

Great self-paced course along with good reason material. The project assignment needed a lot more than the 2.5 odd hours that were estimated. Give yourself more time for the assignment and practice the RStudio assignments in earnest.

By Ian R

•Jul 26, 2016

While the final project was a little unclear in terms of its parameters and there were several small file problems, this was overall a very well constructed course, especially in terms of its content before the final project.

By sabrina r

•Mar 01, 2020

Solid course! You will have to do work outside of what is provided to learn R if you don't have programming knowledge prior. HOWEVER, the final project is when you will really learn how to use the software - learn by doing!

By Nicole C

•May 10, 2020

Course was great, except for the final project which takes much longer to complete than it says, and requires a lot of outside research on how to use R to be able to finish. Other than that very informative and affordable!

By Steve W

•Apr 08, 2017

It takes many more hours to complete the work than the estimates provided. For example the final project took me about nine hours, versus the 2.5 hours listed.

Still, a well-rounded course and it has already proven useful.

By María J O

•Jun 07, 2016

The content is very well structured, the explanations are clear and full of useful examples. Some concepts were a bit difficult to grasp and required reviewing outside the material of the course. In general, excellent.

By Mario S V

•Apr 17, 2018

It should go deeper in teaching R and how the logic on coding works. Moreover, it should teach how to learn and apply new codes, since the final project demands more coding than what was in previous lessons.

By Natalie R

•Apr 25, 2019

The concepts are taught very clearly and thoroughly, but they leave you hanging out to dry a bit with R. R is not an easy program and they could do a little more hand holding in this *Introductory* course.

By eugenie p

•Aug 10, 2016

If you have prior knowledge of R, then this course will help to brush up your statistics. The pacing of the material is very good. The examples used are relevant and interesting. Great course in general.

By Alfredo J N

•Jan 29, 2019

The course is excellent. The only drawback it is the peer review assignments. After you finish your assignment you need search for peers to review your and ask at least three people to do this for you.

By John H

•Mar 27, 2020

The instructions for the final project need to be much clearer. I had a hard time figuring it out, and all of the projects I peer-edited were done poorly. Otherwise, I enjoyed the course very much!

By Michael

•Jul 06, 2019

Good but questions lacked clarity in what is expected. i.e. "Work out the Boy to Girl ratio" - in what fashion do we do this, as it appeared to be the same as simply working out the "proportion of b

By Adam A

•Jun 10, 2017

A good introductory course to data analysis, statistics and the R programming language. Recommended to people who are new to data analysis and also those who are experienced and could use a refresh.

By Holi W

•Dec 14, 2017

The lectures were very clear and concise and the examples were very relevant. Some of the R instructions left a little something to be desired, but nothing a little time and google couldn't solve.

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