Data Analysis and Statistical Inference

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10/10 stars
based on  21 reviews
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Course Details

Cost

FREE

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  • On demand

Course Provider

Coursera online courses
Coursera's online classes are designed to help students achieve mastery over course material. Some of the best professors in the world - like neurobiology professor and author Peggy Mason from the University of Chicago, and computer science professor and Folding@Home director Vijay Pande - will supplement your knowledge through video lectures. They will also provide challenging assessments, interactive exercises during each lesson, and the opportunity to use a mobile app to keep up with yo...
Coursera's online classes are designed to help students achieve mastery over course material. Some of the best professors in the world - like neurobiology professor and author Peggy Mason from the University of Chicago, and computer science professor and Folding@Home director Vijay Pande - will supplement your knowledge through video lectures. They will also provide challenging assessments, interactive exercises during each lesson, and the opportunity to use a mobile app to keep up with your coursework. Coursera also partners with the US State Department to create “learning hubs” around the world. Students can get internet access, take courses, and participate in weekly in-person study groups to make learning even more collaborative. Begin your journey into the mysteries of the human brain by taking courses in neuroscience. Learn how to navigate the data infrastructures that multinational corporations use when you discover the world of data analysis. Follow one of Coursera’s “Skill Tracks”. Or try any one of its more than 560 available courses to help you achieve your academic and professional goals.

Provider Subject Specialization
Humanities
Sciences & Technology
4679 reviews

Course Description

The Coursera course, Data Analysis and Statistical Inference has been revised and is now offered as part of Coursera Specialization “Statistics with R”. This course introduces you to the discipline of statistics as a science of understanding and analyzing data. You will learn how to effectively make use of data in the face of uncertainty: how to collect data, how to analyze data, and how to use data to make inferences and conclusions about real world phenomena.
Reviews 10/10 stars
21 Reviews for Data Analysis and Statistical Inference

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Greg Hamel profile image
Greg Hamel profile image
10/10 starsCompleted
  • 116 reviews
  • 107 completed
5 years ago
Duke’s Data Analysis and Statistical Inference is an introduction to statistics with an optional computational component using the R programming language. The course runs about 8 weeks and covers a considerable amount of ground in that time. It starts with the basics of data and data collection methods but quickly moves on to cover probability, the normal distribution, the binomial distribution, hypothesis testing, confidence intervals, Z and T statistics, ANOVA and Chi squared tests and linear regression. The course is a bit of a whirlwind tour that packs a lot into each lecture. The PDF slides that go along with the videos are a great resource to review the information dumped in each lecture. Many students complained that the course requires more time than the original estimated amount of around 6-8 hours per week. The course was later updated with an estimate of 8-10 hours per week, which is on the conservative side. If you come i... Duke’s Data Analysis and Statistical Inference is an introduction to statistics with an optional computational component using the R programming language. The course runs about 8 weeks and covers a considerable amount of ground in that time. It starts with the basics of data and data collection methods but quickly moves on to cover probability, the normal distribution, the binomial distribution, hypothesis testing, confidence intervals, Z and T statistics, ANOVA and Chi squared tests and linear regression. The course is a bit of a whirlwind tour that packs a lot into each lecture. The PDF slides that go along with the videos are a great resource to review the information dumped in each lecture. Many students complained that the course requires more time than the original estimated amount of around 6-8 hours per week. The course was later updated with an estimate of 8-10 hours per week, which is on the conservative side. If you come in with some prior knowledge of stats and R you can get through in 3-5 hours per week. The professor is engaging and does a good job going through the material while providing adequate face time. The slides are very informative and the video quality is excellent. There are periodic in-lecture quizzes that help test your understanding of the material as you go along. I felt that the frequency of in-lecture quizzes was just about right in this course. Grading is based on performance on weekly quizzes one midterm and one final exam. You need a cumulative grade of 80 percent or more to get a certificate and you only have 1 attempt on the exams, so it is a bit harder to earn a certificate in this course than it is for most MOOCs. If you choose to go the computational route, a portion of your grade is based on 8 programming labs using the R programming language. You can do the labs on your own or use a convenient web-based programming environment provided by the instructor. The labs provide a basic introduction to R and each one explores some of the concepts introduced in the lectures. The labs take about 30 minutes to an hour and a half depending on your level of experience with programming and R. In the computational track you’ll also complete a final project involving a statistical analysis of two variables, either from a data set provided by the instructor or a data set you find on your own. The project lets you use the concepts you’ve learned both in class and in lecture on your own. I suspect the project is a bit intimidating to those who are new to R because it involves more computation than the labs and you don’t have the training wheels that the labs provide. The project grade is based on the median score of 3 or more peer assessments. This is a great course for anyone looking to learn statistics that moves fast enough not to bore those who know a bit of statistics coming into the course.
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10/10 starsCompleted
  • 1 review
  • 1 completed
6 months, 1 week ago
Quite comprehensive and insightful! There were many concepts that I learnt at college that I could only make sense of when I took this course! If you're looking for an introductory Statistics course, take this one!
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10/10 starsCompleted
  • 2 reviews
  • 1 completed
3 years, 1 month ago
This course IMHO is far better than the one provided by Johns Hopkins. Great course for anyone like me who have not worked with statistics for 4-5 years. i would recommend it to anyone interested.
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Student profile image

Student

10/10 starsCompleted
3 years, 5 months ago
One of the most approachable courses in statistics for beginners. The explanations are very clear and there are a number of follow up examples. The courses also emphasizes the use of R which is becoming more frequently used in statistics and data science as a whole.
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Hamideh Iraj profile image
Hamideh Iraj profile image
10/10 starsCompleted
  • 70 reviews
  • 60 completed
3 years, 12 months ago
I first learned about this course in Johns Hopkins Data Science Specialization courses. Students talked about this course in a very positive manner. I became very curious about this course and I decided to take it. I am really satisfied with what I have learned and I feel very good about statistics now. It completely removed my bad memories of statistics. This course was nicely organized with very flexible schedule (no need for late days), phenomenal use of real world examples and beautiful slides (Sometimes I could not take my eyes off the slides). The exercises were carefully designed and I could learn simply by watching videos and doing exercises. (I did nothing special) If you are new to statistics, do not lose this course.
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Yuliana profile image
Yuliana profile image
10/10 starsCompleted
  • 3 reviews
  • 2 completed
3 years, 10 months ago
The course is intense and challenging. It provides a great introduction to statistics and R. To earn a certificate, you will have to get 80% cumulative score on quizzes, labs, exams and the project. I would highly recommend buying the book - having it on hand helped a lot.
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Joyce Chan profile image
Joyce Chan profile image
10/10 starsTaking Now
  • 1 review
  • 0 completed
3 years, 11 months ago
I can say that this course has been the most sucessful in helping me get a good grasp of Statistical Inference! Good examples, along with exercises in DataCamp.
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Heonkyu Jin profile image
Heonkyu Jin profile image
10/10 starsCompleted
  • 5 reviews
  • 5 completed
4 years, 2 months ago
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Chris Alford profile image
Chris Alford profile image
10/10 starsCompleted
  • 2 reviews
  • 2 completed
4 years, 5 months ago
This course should be a model for all other MOOCs, and really shows the potential for what MOOCs can offer in terms of (free) online learning. The amount of work that has gone into putting this course together is really quite astounding and shows in just about every aspect of the course. The lectures are great and the professor is very talented. You cover a huge amount of ground very quickly, and for people new to statistics or who don't have a strong maths background (like me, the last time I studied maths was over 10 years ago!) can struggle a bit in places. However, there is also a very good free-to-download course textbook which helps explain each topic in more detail, so if you're struggling with one of the lectures this is a great reference point. Another excellent aspect of this course is that all of the things you learned are illustrated using real life examples There are very clear learning objectives established for each ... This course should be a model for all other MOOCs, and really shows the potential for what MOOCs can offer in terms of (free) online learning. The amount of work that has gone into putting this course together is really quite astounding and shows in just about every aspect of the course. The lectures are great and the professor is very talented. You cover a huge amount of ground very quickly, and for people new to statistics or who don't have a strong maths background (like me, the last time I studied maths was over 10 years ago!) can struggle a bit in places. However, there is also a very good free-to-download course textbook which helps explain each topic in more detail, so if you're struggling with one of the lectures this is a great reference point. Another excellent aspect of this course is that all of the things you learned are illustrated using real life examples There are very clear learning objectives established for each module, which helps greatly with revision. The quizzes and particularly the exams are difficult - they really make you think about what you have learned. You can't just look over your notes and pick the right answers - you actually have to apply the knowledge. The forums are also very helpful for when you're struggling with a particular aspect of the course - even the professor posts there! The optional R content and the corresponding project are a must - if you don't think you have the time to do this part then I would suggest delay taking this course until you do, as there's only so much of the course you can really apply without the use of statistical software. This part of the course was also very well structured - taking you from a complete beginner in R programming to being able to put together a data analysis project report using only R. All in all, if you're looking for an introductory statistics course - this is the one to choose!
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Guillermo Reales profile image
Guillermo Reales profile image
10/10 starsCompleted
  • 3 reviews
  • 3 completed
4 years, 6 months ago
Indeed an amazing course for everyone interested in learning Statistics.
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Kumar Iyer profile image
Kumar Iyer profile image
10/10 starsCompleted
  • 1 review
  • 1 completed
4 years, 10 months ago
This was a truly awesome course; and ought to be a benchmark for not only statistics courses (John Hopkins, are you listening?), but for all MOOCs as well. The lectures are crisp and clear. Dr. Mine engages you with interesting examples all throughout. You can see for yourself how much effort the team has put into making the course content. I can go on and on about how well paced and relevant the quizzes, labs(via datacamp, another wonderful offering from Duke), mid-terms, project and the final exam have been. You literally have to sweat it out in order to get past these hurdles. But in the end, you feel it is all worth it. I don't have anything to dislike about the course. Through the discussion forums, I could see students leave with a lump in their throat after the course got over. I think that sums up everything.
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Mizar83 . profile image
Mizar83 . profile image
8/10 starsCompleted
  • 9 reviews
  • 8 completed
4 years, 11 months ago
Introductory course in Data Analysis, but not an easy, pass for all course. The teacher is VERY good, and her lectures are always interesting, complemented by very good planned slides. She explains the concepts very clear, even if a little fast. The quizzes, midterm and exams are quite difficult, and they are not a simple and easy repeat of the lectures, actual thinking is involved here (luckily!). The labs are easy and fast, and designed so that everyone gets 100% just going through them. The project is a nice idea, even if it suffers from all the drawbacks of peer assessment for a very open-ended assignments. Points detracted for no reason sparked several threads in the forum.
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Alex Parij profile image
Alex Parij profile image
10/10 starsCompleted
  • 2 reviews
  • 2 completed
4 years, 11 months ago
Amazing course. Perfect course structure and interesting lectures. The weekly lectures are almost good in length. The first weeks were too long and the last ones about linear regression were about right Not only you learn statistics but also R programming , so it's theory and applied knowledge. The exams are hard if you don't have a lot of time to prepare yourself.
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Jessica Susser profile image
Jessica Susser profile image
10/10 starsCompleted
  • 4 reviews
  • 3 completed
4 years, 11 months ago
This is an excellent course on introductory statistics! Dr. Çetinkaya-Rundel presents the subject clearly and provides excellent online learning resources. The format of the labs (datacamp) is extremely helpful for learning R for someone with very little experience in the subject (such as myself). This course is very fast-paced and rigorous and the student will need to invest a significant amount of time and energy in it if they wish to earn a certificate. But I would highly recommend it, it is by far the best online resource I've found for learning statistics.
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Siddharth N profile image
Siddharth N profile image
10/10 starsCompleted
  • 3 reviews
  • 3 completed
4 years, 10 months ago
Course was reasonably comprehensive. Tests were good.
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Dean Wang profile image
Dean Wang profile image
10/10 starsTaking Now
  • 6 reviews
  • 5 completed
5 years ago
I would say this is by far the most well organized class. The teacher present the material very well and the lecture notes ae excellent for study and review in the future. The lab work is very helpful. I missed the peer review submission by an hour. Definitely will try in the future.
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Ant Super profile image
Ant Super profile image
10/10 starsTaking Now
  • 9 reviews
  • 7 completed
5 years ago
This course made me pick up learning the statistics basics. I've had some knowledge of the rough concepts, but before I didn't find the motivation to look at them thoroughly. The course, however, is fast-paced, interesting and informative. The quizzes really help to understand some details.
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Bart olomeus profile image
Bart olomeus profile image
10/10 starsCompleted
  • 15 reviews
  • 13 completed
4 years, 8 months ago
Great, course. A well balanced mixture of theory, examples, labs and projects to test your skills in the 'real' world. The teacher explains the concepts very clearly. The course layout and order of topics is excellent. The difficulty is does not change overall. The free and open textbook is the best I've come across. It is packed with footnotes to datasets, and has more than enough examples and exercises to get you through the midterm and the exam. The teacher is very active on the forums and even organized a Google hangout session you can join. The focus of this course is definitely not on mathematical proofs, probability theory or working through problems analytically, but geared towards practical approaches using given formula's or R to get results on every day problems. Integrated into the course is the datacamp environment that helps you to learn the software R by playing with data. The nature of these task mirror the theory dis... Great, course. A well balanced mixture of theory, examples, labs and projects to test your skills in the 'real' world. The teacher explains the concepts very clearly. The course layout and order of topics is excellent. The difficulty is does not change overall. The free and open textbook is the best I've come across. It is packed with footnotes to datasets, and has more than enough examples and exercises to get you through the midterm and the exam. The teacher is very active on the forums and even organized a Google hangout session you can join. The focus of this course is definitely not on mathematical proofs, probability theory or working through problems analytically, but geared towards practical approaches using given formula's or R to get results on every day problems. Integrated into the course is the datacamp environment that helps you to learn the software R by playing with data. The nature of these task mirror the theory discussed that week. There are some glitches in this new environment (during the first run of this course), and the tasks are not really challenging. The quizzes are quite good. Many of the questions test your insight rather than ask you to do tedious algebra. The peer reviewed research projects are time consuming, great fun and an excellent way to get your hands wet with real data, R and doing some real data analysis. One of the best courses I've taken.
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Ahmed Issawi profile image
Ahmed Issawi profile image
10/10 starsTaking Now
  • 1 review
  • 0 completed
5 years, 1 month ago
This class should be mentor for the online courses .Well organized lectures , nicely quizzes and labs
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timothy235 profile image
timothy235 profile image
10/10 starsCompleted
  • 12 reviews
  • 10 completed
3 years, 8 months ago
This course is destined to become THE online statistics course. Very good lectures, well explained, excellent speaker, professional level graphics, an accompanying free online textbook, and supporting websites of interactive tutorials and 'explore statistics' applets. Not only is this an excellent introductory statistics course, its production values set a new standard for other moocs to achieve. Very highly recommended.
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Student

6/10 starsCompleted
4 years ago
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