Course Logistics Help Center Learn more.

Course Overview:

The main components of this course are:
  • video lectures with in-video quizzes,
  • seven weekly quizzes, and
  • two peer assessed homework assignments.
We expect that the typical workload for this course is 6-8 hours per week.

Content Presentation:

The course will consist of lecture videos containing integrated in-video quiz questions. New material will be posted each week. The in-video quizzes do not form part of your grade for the course. Optional extra videos are available for students who wish to learn to do their own statistical analyses using the R statistical computing package (http://www.r-project.org/); however, no computing is required to complete the course.

Weekly Quizzes:

There will be a quiz in each of weeks 1 through 7. It is recommended that the videos be viewed and the corresponding quiz submitted by the due date which is the end of the week they are posted. To accommodate variation in students' schedules, quizzes will have a final, hard deadline that is one week later than the due date (two weeks later for Quiz 1 only). You may submit quizzes late up until the hard deadline without penalty, but no credit will be given for any work completed after the hard deadline.

Each weekly quiz will have 10 questions worth one point each, for a total of 10 possible points. You are allowed to attempt each quiz multiple times if you wish, and we will count your highest score of all your attempts.

Peer Assessed Homework Assignments:

Each of weeks 4 and 8 will have a peer-assessed homework assignment. The deadlines for your submitted answers will be the ends of weeks 4 and 8. At that point we will shift to the peer-review phase of the process, and you will be asked to review five of your peers' submissions, based on an evaluation guide that we will provide for you. The deadline for your reviews in the peer assessment phase will be one week after the deadline to submit answers. In the final phase, you will see the feedback provided to you by your peers. For more information, see the Coursera FAQ for the question How do peer assessments work?

Homework assignments will be assessed on a credit / no-credit basis. To receive credit, you are required to participate in both the assignment and the peer-review phase. Full credit will be given to all students who both complete the assignment and provide peer-assessment to at least five other students. Zero credit will be given to students who do not complete both steps.

Discussion Forums:

The forums provide a place for students to meet others with shared interests and compare notes on what they’ve learned in class. They also create a community to support and help one another through problems. Please be respectful of one another at all times. Also, it will help the process if you look for the correct forum before posting your questions or topic, and also search that forum to see if there is already a thread on that issue.

Please refer to the Coursera Code of Conduct for discussion etiquette.

Course Grading Scheme:

Your final course grade will be calculated as the sum of your 7 quiz grades (maximum 70%), plus 10% for completing the week 4 homework assignment and peer assessment, plus 20% for completing the week 8 homework assignment and peer assessment, for a maximum possible course grade of 100%.

Statement of Accomplishment:

In order to earn a Statement of Accomplishment, you must get at least 81% for your final course grade.

Textbook:

There is no formal textbook or required reading for this course. However, if you would like to investigate some resources that cover the material at a similar level, here are some recommendations.

  • Traditional textbooks. There are many excellent textbooks that cover the material in the course. Here are three of our favourites:
    • Introduction to the Practice of Statistics, by David S. Moore and George P. McCabe. (The book is currently in its fifth edition, but any edition will do.)
    • Stats: Data and Models, Canadian edition, by Richard D. De Veaux, Paul F. Velleman, David E. Bock, Augustin M. Vukov, and Augustine C.M. Wong. (The original version of the book, by the first three authors only, is also recommended.)
    • Statistics, by David Freedman, Robert Pisani, and Roger Purves.
  • Online textbooks. There are also many resources online. For a free online textbook, try one of the following:

Questions or Difficulties:

If you have questions, please post to one of the Discussion Forums for the course. We can't promise to answer all the questions (there are over 30,000 students enrolled!) but our team will do what we can, and you are strongly encouraged to work together.

Another place to look for information is the Coursera Support Centre documentation where you will find answers to many questions you may have.

Other Supporting Resources:

Optional extra videos are available for students who wish to learn to do their own statistical analyses using the R statistical computing package (http://www.r-project.org/). Data files for use in R are available as links on the Video Lectures page, to the right of the video(s) in which they are used. However, no statistical computing is required to complete the course.

Accessibility:

We are committed to making our site as accessible as possible to all students, including those with disabilities. In order to help you succeed in your studies, we guarantee English-language subtitles on all lecture videos, and we continually strive to make our web platform even friendlier to screen readers and other accessibility-related software.
If you encounter an accessibility problem, or if you need additional accommodations beyond those described above, we want to know right away, please contact accessibility@coursera.org with any of your questions or needs.

Minimum Technical Requirements:

You will need to be able to access video content as well as navigate through the interactive tools, quizzes and peer assessment assignments provided on this web site in order to complete the course. While wide bandwidth is helpful, you may also use the "download" function to the right of the each video clip link if you need to store it locally in order to access the content more effectively. The Coursera Support Centre provides information regarding minimum computer and browser requirements. Some of the Coursera platform tools require a recent browser, so please ensure you have a recent version available when completing quizzes and assessment.
Created Tue 24 Jul 2012 1:31 AM PDT
Last Modified Fri 22 Nov 2013 8:53 AM PST