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4 out of 4 people found the following review useful

a year ago

This is the last course of specialization "Statistics with R". The first three courses were excellent but surprisingly this last course is a complete disappointment. I dropped the course after failing the first quiz multiple times even i carefully followed the lecture videos. Quiz questions were too complex (at least f
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This is the last course of specialization "Statistics with R". The first three courses were excellent but surprisingly this last course is a complete disappointment. I dropped the course after failing the first quiz multiple times even i carefully followed the lecture videos. Quiz questions were too complex (at least for me) based on the lecture videos. Previous three course contained a reading section that was very helpful but this course does not have that reading section part. Course instructor mine cetinkaya rundel was good at delivering lectures as always but as i could not relate quiz questions with video lectures.

6 months ago

This is definitely a challenging course. However, I took in that spirit and am really enjoying it so far. As well as Bayesian statistics, you can learn R/markdown through the very well constructed labs and the advanced, but really helpful extra pdfs put out by Merlise Clyde. I haven't done the rest of the specialisatio
Read More

This is definitely a challenging course. However, I took in that spirit and am really enjoying it so far. As well as Bayesian statistics, you can learn R/markdown through the very well constructed labs and the advanced, but really helpful extra pdfs put out by Merlise Clyde. I haven't done the rest of the specialisation, but did do the earlier stand-alone course fronted by Mine Cetinkaya (an absolutely brilliant lecturer).

The material and the pace is such that most of the lectures alone are not enough in one go to deliver understanding. How many lectures are? But you can watch them again, read the transcript and download the slides, as well as the supplementary pdfs. There is also a helpful list of useful Wikipedia/Stack Exchange articles on the many of the main topics. And, you can try out the ideas in R, as the lecturers encourage you to do.

You can do the quizzes as often as you want. When you get a question wrong, there are helpful hints and you are directed at learning outcomes that the question addresses.

The topic is intrinsically interesting. The course, with its mixture of R markdown files and Git not only delivers that but does it in a modern way that is conducive to learning how reproducible research can be done.

I am about to start the project, which looks like a really interesting opportunity to apply all that we have learned, while also getting the hang of putting together a markdown document along the way.

The material and the pace is such that most of the lectures alone are not enough in one go to deliver understanding. How many lectures are? But you can watch them again, read the transcript and download the slides, as well as the supplementary pdfs. There is also a helpful list of useful Wikipedia/Stack Exchange articles on the many of the main topics. And, you can try out the ideas in R, as the lecturers encourage you to do.

You can do the quizzes as often as you want. When you get a question wrong, there are helpful hints and you are directed at learning outcomes that the question addresses.

The topic is intrinsically interesting. The course, with its mixture of R markdown files and Git not only delivers that but does it in a modern way that is conducive to learning how reproducible research can be done.

I am about to start the project, which looks like a really interesting opportunity to apply all that we have learned, while also getting the hang of putting together a markdown document along the way.

1 out of 1 people found the following review useful

a year ago
**dropped** this course.

This looks like a half-cooked course. It has everything to be an excellent course, like the quality of the other courses from the same group, but fails to deliver a correct learning experience. As of November of 2016, it still needs some polishing.

1 out of 1 people found the following review useful

a year ago
is taking this course right now.

Concepts are abruptly introduced with no apparent thread. The instructors present these as if they are obvious.

This leaves the student scratching their heads.

This leaves the student scratching their heads.

8 months ago

This course is a real challenge for those with no backgrounds in Statistics. The course is the fourth in the framework of a five-course specialisation (Statistics with R) and, the general impression, is that this course is not balanced with the remainder of the specialisation. The three first courses are easy to follow
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This course is a real challenge for those with no backgrounds in Statistics. The course is the fourth in the framework of a five-course specialisation (Statistics with R) and, the general impression, is that this course is not balanced with the remainder of the specialisation. The three first courses are easy to follow, and there is book in addition to further understanding. This fourth course, on the contrary, lacks the appropiate materials and the video lectures are noticeably harder. I would only encourage you to enroll it if you feel confident with Statistics, probability, set theory,...

8 months ago
**completed** this course, spending **4 hours** a week on it and found the course difficulty to be **medium**.

I have a background in applied statistics and I thought this course was pretty challenging. I'm not sure how this course was deemed to be appropriate for a beginner because I think I would have been frustrated and confused if I did not have prior familiarity with the topic.
I thought the discussions comparing the fre
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I have a background in applied statistics and I thought this course was pretty challenging. I'm not sure how this course was deemed to be appropriate for a beginner because I think I would have been frustrated and confused if I did not have prior familiarity with the topic.

I thought the discussions comparing the frequentist approach and outcomes to Bayesian techniques was most useful. Using R to do Bayesian modeling was something I wanted to learn how to do but the modeling techniques, diagnostics, and plots are easily transferable to SAS programming.

I thought the discussions comparing the frequentist approach and outcomes to Bayesian techniques was most useful. Using R to do Bayesian modeling was something I wanted to learn how to do but the modeling techniques, diagnostics, and plots are easily transferable to SAS programming.

12 months ago
**partially completed** this course.

Well, I find the lectures to be good, but the quizes are at times confusing and especially the last course. Sometimes using confusion to filter our learners to classify them according to bell curve can be drastic if too much confusion existed.

0 out of 6 people found the following review useful

0 out of 5 people found the following review useful