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學生對 约翰霍普金斯大学 提供的 探索性数据分析 的評價和反饋

4.7
5,972 個評分
874 條評論

課程概述

This course covers the essential exploratory techniques for summarizing data. These techniques are typically applied before formal modeling commences and can help inform the development of more complex statistical models. Exploratory techniques are also important for eliminating or sharpening potential hypotheses about the world that can be addressed by the data. We will cover in detail the plotting systems in R as well as some of the basic principles of constructing data graphics. We will also cover some of the common multivariate statistical techniques used to visualize high-dimensional data....

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Y

2017年9月23日

Very good course! It provide me the foundation in learning how to plot and interpret data. This will definitely strengthen my "R programming" to generate publication type figure for my genomics data!

CC

2016年7月28日

This is the second course I have taken from Roger Peng and both were outstanding. I have a strong math background, but not much of a background in stats, but this course was very approachable for me.

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776 - 探索性数据分析 的 800 個評論(共 843 個)

創建者 Johnnery A

2019年11月17日

Excelente

創建者 Khobindra N C

2016年5月18日

Excellent

創建者 Rohit K S

2020年9月20日

Nice!!

創建者 Tae J Y

2017年3月31日

Good!

創建者 Edward A S M

2019年12月5日

Good

創建者 木槿

2018年11月2日

good

創建者 Anup K M

2018年9月27日

good

創建者 Isaac F V N

2017年4月18日

Nice

創建者 Chan E

2016年3月22日

nice

創建者 Adur P

2017年12月28日

A

創建者 Saurabh K

2017年4月27日

G

創建者 deepak r

2016年10月2日

d

創建者 Jose O

2016年2月11日

Insights delivered by the course were great. However, I think it emphasizes too much the lattice and basic plot systems to the point it is redundant with functionality on ggplot. It should focus more on concepts and techniques for delivering richer and meaningful graphics using ggplot rather than talking that much about technicalities on the basic plot and lattice systems.

Assignments were too basic and don't reflect all the concepts learned in the lessons e.g. clustering, which I think are of great interest for researchers.

創建者 Ahmed M

2016年8月24日

The course is quite good and informative in the first two weeks covering a lot of information and a lot of exercises.

Week 3 is very unrelated and hard the videos and exercises are bad, and I had to do this part by myself again.

Also when we get to the final course project doesn't cover any of these techniques.

In my opinion, week 3 should be replaced with something more related to plotting systems and distributions, also one project would be enough.

創建者 Andrew V

2016年6月10日

The course covers very limited subset of plots and mostly oriented to R-specific technical routines rather than overall approaches. Case-study example is helpful and contrary to the most comments I do appreciate the final course project: this how most problems are stated in real life. If you would like to cover more fundamental concepts behind exploratory analysis I would recommend other sources.

創建者 Mohammad A A

2019年3月11日

It was a very useful course with some meaningful homework. My only criticism is that sometimes the theory and the practice are not well connected. Particularly the discussion of PCA, hierarchical clustering, k-means clustering and others. It would be benefit by providing more meaningful reading for those interesting in better connecting the two

創建者 Arne S

2019年8月31日

did not like the swirl-tutorials. they were very tedious and sometimes labelled correct commands as false (e.g. when you typed = instead of <- for assigning a value to a variable)

also I was surprised that for a beginner programming course in R you had to apply specific functions such as grepl without the function being introduced in the course

創建者 Haggai Z

2017年8月27日

unfortunately this course was not in the same class as earlier courses

cases presented were not interesting or self explained.

concepts were wage and the lectures were boring

i think i need to take parallel course for the same knowledge targets i want to really understand this

創建者 Thomas G

2016年4月26日

A lot of broken swirl(), which wouldn't be so bad except *a lot* of this course is based entirely on swirl(). Also the swirl() text was almost verbatim of the lectures one has just watched.

All in all, good information, but the swirl() badly needs an update.

創建者 Ray O C

2016年12月29日

The first two weeks were good. The third was a bit confusing and the 4th one just felt like padding. A more in depth study of ggplot would probably be more beneficial as I felt like we were only scratching the surface with it

創建者 Toby K

2016年3月1日

Excellent overview of plotting and clustering. However, there were a few bits that were required for good completion of the projects that weren't covered in detail. Overall an excellent course and specialization.

創建者 Ralph M

2016年3月8日

Good course overall. There tends to be many lectures that are just lists of commands. Also, they don't seem to be updating the material. Many lectures are several years old and still have typos in them.

創建者 Shorouk A

2021年10月22日

The course only provide how to use the tools technically, but not statistically. also the only hands-on complete project is peer-reviewed, which means we don't get to know what we need to improve, etc.

創建者 Samer A

2018年3月30日

It's pity that the final assignment doesn't involve the clustering and the principal component analysis. It was quite a demanding topic and I was looking forward to practicing it through solving tasks.

創建者 Fabiana G

2016年6月23日

Course feels somewhat abandoned by instructors. Content is okay, but can't help the feeling that it's basically a cash cow - students would benefit a lot if instructors were move involved.