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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

5,981 個評分


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....




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!



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.


801 - 探索性数据分析 的 825 個評論(共 844 個)

創建者 Fabiana G


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.

創建者 Ashish T


Great introduction to the plotting libraries in R and visualization of data.

However the introduction to hierarchical clustering, and Principle component analysis was extremely vague.

創建者 Asier


The course content applies to R. The teachers focused on the programming language rather than the application of the existing graphs to explore data.

創建者 Gianluca M


A nice introduction to the three plotting systems in R. The second part is devoted to clustering, but it is not detailed enough to be really useful.

創建者 Andreas S J


Important and interesting stuff - but lots of it is repeated too much, which make it seem like 4 weeks is too much for the material.

創建者 Dylan P


I would have liked an assignment to focus on the clustering methods and I think dimension reduction was reviewed way too quick.

創建者 ozan b


Course is good in general but "HIERACHICAL CLUSTERING" part is hard to understand and is not clear, should be explained more.

創建者 Casey B


Good class - links and slides have not been updated recently. Frustrating to finish without the exact linkts to the data.

創建者 Katharine R


Good course, but the SWIRL exercises (and a few quiz questions) needed to be updated for the latest version of ggplot2.

創建者 Johnny C


In general was good, but there were some lectures and exercises which were disorganized ("plots with colors")

創建者 Erkan E


I wish there several comprehensive examples of exploring some real data as guided by the course instructors.

創建者 Mehrdad P


The course was overall ok, but I wish discussions about k-means, PCA and SVD were divided into two courses.

創建者 Daniel P


I've learned plotting in R. I expect to learn more in four weeks of "Data Science" specialization.

創建者 Stuart A


Course hasn't been updated in a long time, some of the data needed for the projects has migrated.

創建者 Francisco M R O


The third and fourth week were a big leap in knowledge and not really well explained, for me.

創建者 sandeep d


Excercises are very good. But I believe lecture could be more interesting and easily taught.

創建者 Guy P


It misses an assignment which will allow to practice the clustering skills.

創建者 Alex s


It focus too much on the tools and a little bit on the analysis

創建者 Amit O


faced many technical difficluties in pratcice exerices in swirl

創建者 Victor M C T


The swirl labs failed, I never could load the "field" module.

創建者 Eduardo V K


There seems to be some outdated info in several tests.

創建者 Rafael A


First two weeks are too repetitive with other courses

創建者 Kevin F


pretty brief and basic. no assessment on clustering.

創建者 Erwin V


Interesting stuff, but not a lot of detail

創建者 Oscar P G P


It's necessary for more examples!!!!