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.
제공자:
존스홉킨스대학교이 강좌에 대하여
최근 조회 43,231회
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지금 바로 시작해 나만의 일정에 따라 학습을 진행하세요.
완료하는 데 약 55시간 필요
영어
자막: 아랍어, 프랑스어, 포르투갈어 (유럽), 중국어 (간체자), 이탈리아어, 베트남어, 한국어, 독일어, 러시아어, 영어, 스페인어
배울 내용
Understand analytic graphics and the base plotting system in R
Use advanced graphing systems such as the Lattice system
Make graphical displays of very high dimensional data
Apply cluster analysis techniques to locate patterns in data
귀하가 습득할 기술
- Cluster Analysis
- Ggplot2
- R Programming
- Exploratory Data Analysis
유연한 마감일
일정에 따라 마감일을 재설정합니다.
공유 가능한 수료증
완료 시 수료증 획득
100% 온라인
지금 바로 시작해 나만의 일정에 따라 학습을 진행하세요.
완료하는 데 약 55시간 필요
영어
자막: 아랍어, 프랑스어, 포르투갈어 (유럽), 중국어 (간체자), 이탈리아어, 베트남어, 한국어, 독일어, 러시아어, 영어, 스페인어
제공자:
존스홉킨스대학교
The mission of The Johns Hopkins University is to educate its students and cultivate their capacity for life-long learning, to foster independent and original research, and to bring the benefits of discovery to the world.
강의 계획표 - 이 강좌에서 배울 내용
완료하는 데 19시간 필요
Week 1
This week covers the basics of analytic graphics and the base plotting system in R. We've also included some background material to help you install R if you haven't done so already.
완료하는 데 19시간 필요
15개 동영상 (총 109분), 6 개의 읽기 자료, 7 개의 테스트
완료하는 데 17시간 필요
Week 2
Welcome to Week 2 of Exploratory Data Analysis. This week covers some of the more advanced graphing systems available in R: the Lattice system and the ggplot2 system. While the base graphics system provides many important tools for visualizing data, it was part of the original R system and lacks many features that may be desirable in a plotting system, particularly when visualizing high dimensional data. The Lattice and ggplot2 systems also simplify the laying out of plots making it a much less tedious process.
완료하는 데 17시간 필요
7개 동영상 (총 61분), 1 개의 읽기 자료, 6 개의 테스트
완료하는 데 13시간 필요
Week 3
Welcome to Week 3 of Exploratory Data Analysis. This week covers some of the workhorse statistical methods for exploratory analysis. These methods include clustering and dimension reduction techniques that allow you to make graphical displays of very high dimensional data (many many variables). We also cover novel ways to specify colors in R so that you can use color as an important and useful dimension when making data graphics. All of this material is covered in chapters 9-12 of my book Exploratory Data Analysis with R.
완료하는 데 13시간 필요
12개 동영상 (총 77분), 1 개의 읽기 자료, 4 개의 테스트
완료하는 데 5시간 필요
Week 4
This week, we'll look at two case studies in exploratory data analysis. The first involves the use of cluster analysis techniques, and the second is a more involved analysis of some air pollution data. How one goes about doing EDA is often personal, but I'm providing these videos to give you a sense of how you might proceed with a specific type of dataset.
완료하는 데 5시간 필요
2개 동영상 (총 55분), 2 개의 읽기 자료, 2 개의 테스트
검토
- 5 stars74.16%
- 4 stars21.23%
- 3 stars3.42%
- 2 stars0.73%
- 1 star0.43%
탐구 데이터 분석의 최상위 리뷰
IS 제공2020년 11월 25일
This is a great course. The basics are explained very clearly and very easy to understand. I highly recommend this course for those who wish to start in Data Analyst / Data Science track.
RS 제공2017년 2월 13일
Nice course, but too much focus on "R" as a tool.... Industries don't use R as much... The course must be made more generic and independent of R - understand it is not easy to do but ....
CC 제공2016년 7월 28일
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.
LS 제공2019년 10월 31일
Good introduction. The swirl exercises kind of reproduce the lectures though- felt like it might not have been the most efficient use of time to go over the exact same example again.
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