Chevron Left
Back to Introduction to Probability and Data with R

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!

Filter by:

1201 - 1225 of 1,306 Reviews for Introduction to Probability and Data with R

By Casey S

•

Nov 11, 2017

This course to me had some very clear un-explicit limitations, pros and cons:

- The lectures are fantastic and have a good sequence for beginners

- The course is very holistic in its approach, meaning that it covers theory and application very broadly and gives you a good sense of how different aspects of the field of statistics relate to eachother

- The coverage of the R programming language is insufficient for the requirements for using it in the final assignment, I can't stress this enough for beginners. I highly suggest you take a foundational course in R, highlighting syntactical structure of the language, prior to taking this course

- The labs are great for learning the primary components of R, but they don't give you real practice coding. There is very little to no explanation of certain functions in R and there are no videos on it. I do not feel at the end of this course I have a very good understanding of the structure of the language of R, I do however feel I was assessed as if I should have.

- I felt the quizzes were appropriately rigorous for a beginner such as myself.

Most important bottom line is: If you are a true beginner like myself I urge you to first take a course more targeted to R before starting this specialization. Otherwise, like myself, I think you will feel very overwhelmed at the end.

By Jeremy L

•

Jul 6, 2018

The course is divided into 5 sections, each of which you have a week to complete (if you want a certificate). The first 4 sections/weeks are well designed and involved a mixture of lectures (most were good), reading assignments in a textbook (free online access), practice problems, and a weekly quiz. Along the way students learn how to use R through a handful of walk-through examples. In general this works. That said, the last two R assignments are a mess. For the 4th week, the instructors put together a demonstration for using R to ask and answer some basic research questions. The document they put together for this demonstration, however, is so full of typos and grammar mistakes, and worse, heaps of nearly incomprehensible sentences and phrasings, that it is almost worthless. It was really painful to get through it. The final R task is to work with a real-world data set, ask a few research questions, and use R to do some basic statistical analysis of the data. Working with a real-world data set is great. That said, I felt as if the instructors were asking students to do far more with R and statistics than we had learned in the class. I saw many similar opinions about this assignment online. And in grading my peers, I noticed that other students didn't know how to complete the project either.

By Nayyer I

•

Apr 28, 2020

The course is great in terms of building foundational concept for data analysis and lab assignments were ok. The I think often the time listed for any class is a little underestimation of time commitment. The course has offered me a lot of new concepts to learn and was good refresher for many other. But the final project was a huge disappointment for me. The students have been given a huge datasets that leaves students struggling to figure out where to start. In order to understand the data, students have to go to various links to see what the data is, how it is collected and definition of each variables. Then there are more than 300 variables and you need to pick few to do something you think is interested. Finally, the project needs a good level of expertise in "R" and course does not teach you that at all. I would suggest that for future courses reduce the number of variables depending on what most students have been using. Draft a quick summary and report about key information of data and share that on course page rather than links to web pages, and finally let students use the software that they may feel interesting. Not everyone is skilled to use R.

By Nenad P

•

Oct 4, 2021

I'd say the name is somewhat misleading, in the sense that very little of R is taught, even for an introductory course. You only get shown several functions without much context and no big picture understanding. Comes down to rote learning in the end. Probability-wise, since I've already had some background skills, this is also a shallow level look into the basics, with barely any theoretical setup or even a bit of historical background to some concepts to really flesh it out. The fact that we haven't even noted down the function for a normal distribution and explained the difficulty in calculating it by hand (therefore, using R or a table) is kind of a disappointment. I believe this is down to my own expectations, thinking this would be something useful to people who already have some background in STEM, but it seems to be aimed at total beginners. Will probably continue with the specialization, but I can't say my certificate is of much worth without it.

By Efe A

•

Feb 23, 2018

The videos, readings and quizzes are excellent, they are well organized and follow a logical sequence. The level is also suitable for a beginner and pleasant enough to watch after a busy day at work !

However Rstudio/r instructions and lab assignments need improvement. The specialization description puts a lot of emphasis on R giving the impression that these skills are also going to be taught from scratch. However there is not enough instruction and feedback. Judging from some assignments I have read it definitely seems like most of the students already have a comfortable working knowledge of R. If you are like me, a complete beginner, you will have to learn a lot from additional sources and your assignment will look like a mess (but you will most likely pass !)

By Ted T

•

May 5, 2020

I didn't get on with this course, I'm afraid. I found that the R explanations were somewhat lacking for what I needed. Some sections I could complete absolutely fine but then it got suddenly much harder to do what was required. While that's part of learning and language, it wasn't helpful for the stage in my learning experience (during each week's classwork).

I'm not an idiot. I was able to complete the full course, including the last stage project but it just didn't teach all that well. I don't feel much more confident in R.

I'd also say that the course relies quite a lot on the open source textbook. The instructor did write it - fair play - but I'm paying Coursera for the privilege of following something that's free.

By Michael S

•

Oct 7, 2019

The course lectures were very good and informative. However, this course does need some work. First, the text revision references were confusing. The homework assignments were a confusing as to where they should be performed; on our own or within GitHub. I have used R before and was using this course as a refresher. The course series definitely needs a optional introductory course in use of R, R Studio, GitHub, and R Markdown language. Similar to the JHU Data Science specialization. Finally, the course project was a bit deep for introductory Probability and Data. Need to make the course project less demanding or drop the need for a final course project until later courses

By Tabitha V

•

Oct 29, 2020

The instruction in statistics is understandable and complete. The final homework problem/test is way outsized for this introductory level course. The meager instruction in R - tucked between the video instruction in statistics - is insufficient to tackle the huge data set that is provided for open analysis. The data set (brfss2013) is too large for R Studio Cloud to handle, which is very limiting. The statistical questions that could be asked from the data are infinite and beyond what was taught in the course. The Week 5 final project ended up being months of frustration without the solid support in R.

By Nicholas R

•

Oct 5, 2017

Problems with the course: Despite getting high grades, I felt like I had forgot much of the material by the end. There should be more quizzes, a mid-term, and more peer-reviewed projects. Didn't teach R basics which made it hard to learn the language and complete the final project w/o a lot of research. Content was generally great.

Problems with the platform: Video skips randomly, submitting ID was buggy (wouldn't save), and the chance that you might not get enough peer reviews and have to delay to the next session is nuts. Just require that people submit more reviews!

By Kaylee L

•

Mar 29, 2019

Since the reason I took this course was learning R programming, I think this course focuses too much on data theories. From my perspective, it would be better if this course could put more efforts on R programming skills. In addition, when students raise questions on the forum, these questions were seldomly answered by tutors. It is obvious that there were some bugs of coursera platform for a long time, but these bugs were not fixed. However, I learnt how to start R programming by joining this course, which was really helpful to me.

By Justin S

•

Aug 29, 2022

It gives a good explanation on the statistical/probability concepts, but I wish there were more RStudio projects. For example, after each video topic, it would be great to then have a mini-project to do in RStudio related to the video material. There are only 3(? maybe 4) labs in this course, and the labs do not cover all of the material presented. I feel that the course definitely needs a lab working with Normal and Binomial distribution. But again, an RStudio project for each video would be great.

By Alexander S

•

Oct 15, 2019

On the whole I thought the theoretical content of the course was good, and that the supporting materials were quite helpful. I would strongly caution prospective students about the amount of time that is actually required to complete the course requirements. Specifically, I found that the amount of time that was, in actual practice, required to learn even the basics of R and to then apply this to actually doing the final assignment vastly exceeded the time suggested by the course instructions.

By Dan H

•

Jun 3, 2019

The textbook is excellent, though it would be helpful to provide some suggestions for a more rigorous treatment of the material. Lectures are well presented and organized. Assessments (which, unfortunately, are what drive teaching/learning outcomes) are of a lower quality. The course project has potential, but poorly executed as a peer review assignment. I have no confidence that anyone with this credential will have met the course objectives. Don't hire based on this course.

By Yevgeniy G

•

Nov 20, 2016

Slow down. Introduce more R before asking to create projects in R. Only because I know other programming language was I able to finish week 5. Also very strong group of mentors... God bless you mentors!

Disconnect between course objectives and programming assignments / labs. Reading book you learn one thing, watching lectures another and then unrelated labs, which then culminate in something totally different during week 5?

By Omer N

•

Aug 28, 2017

The lectures are relatively good, though not of consistent quality. Some material is explained very welland some in a bit of a disorganized fashion. The assignments require a level of R knowledge which is neither taught directly nor stated as a prerequisite. For those familiar with cleaning and exploring data with R (ggplot2 and dplyr especially are important packages) this is an excellent course.

By Nikoleta K

•

May 13, 2018

It is a fine point to start for a beginner and you do learn the statistics part of the course in a constructive way, but I believe when it comes to learning R it is lacking. You get to learn coding, but not enough as in to be able to apply it in different sort of research! The teaching provided for R is limited and situational, and this is not because it is the introductory course.

By Joseph D

•

Oct 12, 2021

Overall a decent course to introduce basic statistics and calculations. A couple of things that I did not like is that the readings don't match the latest edition of the book - they're assigned out of the 3rd edition not 4th - and it's not clear that that is the case. One of the quizzes had a question from the previous week's learning objectives and it threw me for a loop.

By Noah W

•

Jun 19, 2019

Overall I learned a lot in this course, although that comes with a caveat. Some of the more difficult content was breezed over, and I found myself searching outside the coursework to get a better explanation (particularly with probability and most of the R tools.) That being said, if this course is useful as a series of benchmarks to guide you with your own research.

By Dhruvin S

•

Jun 27, 2020

The statistical portion is one of the bests and the professors makes the understanding very easy with numerous examples; however, if you are planning to learn anything about R in this course, then it not for you. The portion dealing with R is highly vaguely explained, which makes it very difficult and frustrating while doing the quizzes; so enroll accordingly.

By Danielle B

•

Sep 24, 2020

The statistics and probability portions were very good, but there was almost no instruction with regards to R programming. The project at the end felt very much like an intermediate project instead of an intro project. I spent far more time Googling/YouTubing the gaps in instruction than I actually did completing the project.

By Ivana V

•

Sep 8, 2020

The course content was very helpful, and provided a great refresher of probability. However more guidance is needed for the lab exercises. Due to firewalls, I could not access some of the required R content. It would have been nice if the lab exercises reflected the information that was taught in the weekly modules.

By Nathan P

•

Jul 30, 2016

I took this course hoping for a fundamental education in utilizing R for statistical analysis. Unfortunately, this course focuses heavily on statistical methods and very little on explaining the R processes used. Good for introductory stats students, not great for those interested in furthering their knowledge of R.

By Peter C

•

Oct 18, 2018

I thought the lectures were a very helpful re-introduction to statistics but felt very disconnected from the assignments in rstudio. I felt lost when I got to the final project. I would recommend incorporating rstudio into the lecture so the students can follow along and practice writing r scripts.

By Alexis J G H

•

Dec 1, 2023

This is an excelent course in statistics but not R; you are barely taught how to set R for data analysis; conversely, the modules focus on developing the capacity to understand basic statistics interpret results and be able to perform probabilistic thinking, but nothing related to data analytics.

By mallory w

•

Oct 8, 2018

I really liked it! Some basic R mechanics were undertaught and I'm very lucky that my data scientist brother volunteered an hour of his time to catch me up. However, I can say that this course genuinely held my interest all the way through with authentic examples and challenging exercises.