Top Free Classes

Class Calendar User forum Blog
Follow us to get notified about new classes

Help your friends find these classes

Sign up for free personalized recommendations. Sign up is free and easy.
Search for classes 
Data Analysis and Statistical Inference


Data Analysis and Statistical Inference

Mine Çetinkaya-Rundel Duke University @Coursera
Class Start: 2014-09-01 2014-09-01 18:00:00 2014-09-01 19:00:00 35 Course 'Data Analysis and Statistical Inference' starts at Coursera Course starts at Coursera:


See more details at TopFreeClasses [] false YYYY-MM-DD
Duration: 10 weeks
Approximate Workload: 6-8 hours/week
Certificate: Yes
Level: intermediate
Rate this class Go to the class
This course introduces you to the discipline of statistics as a science of understanding and analyzing data. You will learn how to effectively make use of data in the face of uncertainty: how to collect data, how to analyze data, and how to use data to make inferences and conclusions about real world phenomena.

Click here to review this class

Anonymous (Singapore, Singapore) , 2014-05-04
Time consuming, but this course is well worth the money on signature track! This will give you a very solid understanding of statistic, which is the basic of so many other fields: experimental research, lean, and machine learning just to name a field.

Unmissable if you want to broaden your knowledge on how to do things with scientific rigor.

Please log in to vote or edit

Anonymous (Singapore, Singapore) , 2014-05-04
Thisi is one of the best course I ever took online or at university.
The content is challenging but the professor explains it so well that it is a pleasure to come back for more every week.

Its not easy, you have to work a lot to succeed but if you do, you will be very happy with this class.

Please log in to vote or edit

Bart , 2014-05-01
Great, great course. A well balanced mixture of theory, examples, labs and to learn software and projects to test your skills in the 'real' world.

The teacher explains the concepts very clearly. The course layout and order of topics is excellent. The difficulty is does not change overall. The free and open textbook is the best I've come across. It is packed with footnotes to datasets, and has more than enough examples and exercises to get you through the midterm and the exam.

The teacher is very active on the forums and even organised a Google hangout session you can join.

The focus of this course is definitely not on mathematical proofs, probability theory or working through problems analytically, but geared towards practical approaches using given formula's or R to get results on every day problems.

Integrated into the course is the datacamp environment that helps you to learn the software R by playing with data. The nature of these task mirror the theory discussed that week. There are some glitches in this new environment (during the first run of this course), and the tasks are not really challenging.

The quizzes are quite good. Many of the questions test your insight rather than ask you to do tedious algebra.

The peer reviewed research projects are time consuming, great fun and an excellent way to get your hands wet with real data, R and doing some real data analysis.

One of the best courses I've taken.

Please log in to vote or edit

Anonymous (Singapore, Singapore) , 2014-04-21
This course has a fairly high standard for passing (80%). Though this can be frustrating, it ultimately drives you to buckle down and learn the material. Those who cannot devote a decent amount of time to the course will feel lost if they have no former introduction to the topic. If you can devote the time, it is rewarding and very well taught. Highly recommended.

Please log in to vote or edit

Anonymous (Singapore, Singapore) , 2014-04-18
Very demanding, but worth it.

Please log in to vote or edit

Anonymous (Singapore, Singapore) , 2014-03-11
awesome class

Please log in to vote or edit

Included in collections
Data Science
Data Science tracks
25 courses
Data analysis using R
11 courses
Similar classes
Stat2.3x: Introduction to Statistics: Inference
Ani Adhikari
UC Berkeley @EdX
Start date: 2014-06-02
Stat2.2x: Introduction to Statistics: Probability
Ani Adhikari, Philip B. Stark
UC Berkeley @EdX
Start date: TBA
Introduction to Statistics
Sebastian Thrun
Stanford University @Udacity
Start date: always available
Data Analysis
Jeff Leek
Johns Hopkins University @Coursera
Start date: TBA

© 2012-2016, TFC Online LLC | Home | Terms of Use and Privacy Policy | About Us