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Exploratory Data Analysis

This course covers the essential exploratory techniques for summarizing data. These techniques are typically applied before formal modeling commences and can...
4.7
☆☆☆☆☆ 4.7/5
(5,882 reviews)
160,141 students
Created by
Roger D. Peng, PhD

8.9

Classbaze Grade®

N/A

Freshness

8.6

Popularity

8.7

Material

Detailed Analysis »

Exploratory Data Analysis
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Platform: Coursera
Price: check current price
Video: 5h 2m
Language: English

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Classbaze Rating

Classbaze Grade®

8.9 / 10

CourseMarks Score® helps students to find the best classes. We aggregate 18 factors, including freshness, student feedback and content diversity.

Freshness

Course content can become outdated quite quickly. After analysing 71,530 courses, we found that the highest rated courses are updated every year. If a course has not been updated for more than 2 years, you should carefully evaluate the course before enrolling.

Popularity

8.6 / 10
We analyzed factors such as the rating (4.7/5) and the ratio between the number of reviews and the number of students, which is a great signal of student commitment.

New courses are hard to evaluate because there are no or just a few student ratings, but Student Feedback Score helps you find great courses even with fewer reviews.

Material

8.7 / 10
Video Score: 8.3 / 10
The course includes 5h 2m video content. Courses with more videos usually have a higher average rating. We have found that the sweet spot is 16 hours of video, which is long enough to teach a topic comprehensively, but not overwhelming. Courses over 16 hours of video gets the maximum score.
The average video length is 4 hours 49 minutes of 559 Data Analysis courses on Coursera.
Detail Score: 7.8 / 10

The top online course contains a detailed description of the course, what you will learn and also a detailed description about the instructor.

Extra Content Score: 9.8 / 10

Tests, exercises, articles and other resources help students to better understand and deepen their understanding of the topic.

This course contains:

10 articles.
0 resource.
0 exercise.
19 tests or quizzes.

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About the course

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.

What can you learn from this course?

What you need to start the course?

The course creator has not defined the requirements for this course.

Who is this course is made for?

The course creator hasn’t defined the level of this course.

Are there coupons or discounts for Exploratory Data Analysis ? What is the current price?

Access to most course materials is FREE in audit mode on Coursera. If you wish to earn a certificate and access graded assignments, you must purchase the certificate experience during or after your audit.

If the course does not offer the audit option, you can still take a free 7-day trial.
The average price is $8.1 of 559 Data Analysis courses. So this course is 100% cheaper than the average Data Analysis course on Coursera.

Will I be refunded if I'm not satisfied with the Exploratory Data Analysis course?

Coursera offers a 7-day free trial for subscribers.

Are there any financial aid for this course?

YES, you can get a scholarship or Financial Aid for Coursera courses. The first step is to fill out an application about your educational background, career goals, and financial circumstances. Learn more about financial aid on Coursera.

Who will teach this course? Can I trust Roger D. Peng, PhD?

Roger D. Peng, PhD has created 35 courses that got 156 reviews which are generally positive. Roger D. Peng, PhD has taught 1,337,275 students and received a 4.65 average review out of 156 reviews. Depending on the information available, we think that Roger D. Peng, PhD is an instructor that you can trust.

Learn everything about

Roger D. Peng, PhD

Bloomberg School of Public Health
Johns Hopkins University
Roger D. Peng is a Professor of Biostatistics at the Johns Hopkins Bloomberg School of Public Health and a Co-Editor of the
Simply Statistics blog. He received his Ph.D. in Statistics from the University of California, Los Angeles and is a prominent researcher in the areas of air pollution and health risk assessment and statistical methods for environmental data. He is the recipient of the 2016 Mortimer Spiegelman Award from the American Public Health Association, which honors a statistician who has made outstanding contributions to health statistics. He created the course Statistical Programming at Johns Hopkins as a way to introduce students to the computational tools for data analysis. Dr. Peng is also a national leader in the area of methods and standards for reproducible research and is the Reproducible Research editor for the journal
Biostatistics. His research is highly interdisciplinary and his work has been published in major substantive and statistical journals, including the
Journal of the American Medical Association and the
Journal of the Royal Statistical Society. Dr. Peng is the author of more than a dozen software packages implementing statistical methods for environmental studies, methods for reproducible research, and data distribution tools. He has also given workshops, tutorials, and short courses in statistical computing and data analysis.
Roger D. Peng, PhD's full profile and courses »
Go to class »

8.9

Classbaze Grade®

N/A

Freshness

8.6

Popularity

8.7

Material

Detailed Analysis »

Exploratory Data Analysis
Go to course »
Platform: Coursera
Price: check current price
Video: 5h 2m
Language: English

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