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Data Analysis

Jeff Leek Johns Hopkins University @Coursera
Class Start: TBA
Duration: 8 weeks
Approximate Workload: 3-5 hours/week
Certificate: No
Level: intermediate
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Learn about the most effective data analysis methods to solve problems and achieve insight.

Reviews
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Olena Bosenok , 2013-10-28
Here is what I liked about this class:
1. It is well designed course -- informative lectures with many examples and challenging but fair quizzes.
2. Clear instructions for peer-graded assignments (there were 2) with given example.
3. Incredibly helpful forum discussions and supportive students' community.
4. Good introduction to main R functions/packages with additional references.
Things that could have been better:
It would be helpful to have short in-lecture quizzes since students had to pause the video anyway to exercise.
Summary: I would recommend this course for statisticians, business analysts, and scientific researchers or college students who're interested in such careers.

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Anonymous (Singapore, Singapore) , 2013-08-02
Great class, don't miss! It get me started with R. Very practical, many exercises. Lectures are available on youtube. https://www.youtube.com/watch?v=OfgjgEXxskg&list=PLXBDYmaCbeL8efhOZS4g9W6Z3m9_hFSnT
The instructor is also a co-editor of http://simplystatistics.org/, fine source for data nerds.

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Anonymous (Singapore, Singapore) , 2013-03-20
View this course as a master class in statistics. Jeff Leek is a master statistician; he shows how experts do academic statistical research.

To benefit from this course you should:
• Know about statistics beyond the basics
• Be familiar with the process of doing academic research
• Be able to write research reports in English
• Be comfortable with the R statistical package
(tip: do the course “computing for data analysis” before you try this one)
• Want to become an academic statistical researcher yourself.

This is a very rich course. A pretty good statistician, probably could do this course three times in a row, and learn new things each time he did it.

There are two challenging assignment which each take say 20 hours to complete (but when you really dig into them, you easily can spend 60 hours on each). Watching the lectures and doing the quizzes took me about 10 hours each week.
The professor is an expert statistician; he is not an expert teacher. You probably need good study skills to follow his presentations. This is definitely not an easy introduction; it is more a statistics course for statisticians. For those who want to become serious about statistics this is a great course.

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Anonymous (Singapore, Singapore) , 2013-02-18
Excellent course. Superb lectures, great assignments, fair quizzes, understanding and engaged teacher. I've been discovering the new universe of powerful statistical models and R language and enjoying it all the way through.

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Anonymous (Singapore, Singapore) , 2013-02-06
Very impressed so far with the learning experience offered by this course.

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Troddel (Malmo, Sweden) , 2014-04-20
Very good class. Excellent assignments of exploratory nature.

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Anonymous (Singapore, Singapore) , 2013-12-17
One of the worst courses I ever took. Video are basically the teacher reading some printed phrases or R commands: no value added compared to personal reading of R manuals and tutorials. The peer reviewed projects where exposed to very subjective evaluation.. unavoidably, I presume, considering that the class do not cover adequately all the points required to complete the task. Such wide topic probably requires to be covered in more than one course and with a more involving teaching style.

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pssGuy (North Vancouver, BC) , 2013-11-20
Pretty challenging especially for newcomers to R

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Anonymous (Singapore, Singapore) , 2013-03-19
With few tweaks will be an excellent course. Challenging - yes! Boring - no!
Hands on real life data and questions. Thank you, Jeff, and team!

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Anonymous (Singapore, Singapore) , 2013-03-19
I would recommend to take Machine Learning with Andrew Ng, otherwise it could be overwhelming. I enjoyed most of the course, except for the first assignment that required knowledge of linear regression and ANOVA , but it was due the same week these topics were covered. Week 7 material needs an extra week, otherwise it's too much. Special thanks to my classmates whose forums' posts fulfilled the gap in lectures and helped with homework.

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Anonymous (Singapore, Singapore) , 2013-02-22
Early lectures were exceedingly easy, but the difficulty jumped suddenly in the third week. The professor does not adequately explain underlying concepts. On one hand, we can't fault him -- the topic of the course is performing an analysis, not on the statistical methods underlying it -- but on the other hand, teaching us to perform statistical tests without a good understanding of what we are doing will lead to poor analyses.

I really wanted to like this course, but found the content too poorly explained to continue.

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Anonymous (Singapore, Singapore) , 2013-02-01
So far, the course is good. The instructor's style is a little dry (somewhat military flavor) but the description is structured and consistent. However, keep in mind that the course pace is very slow, so if you are already somewhat familiar with the subject, you will fall asleep.

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