# MA101A Distributions, Tests and Graphics

(Difference between revisions)
 Revision as of 03:37, 7 February 2008 (view source)Jeff (Talk | contribs)m (→Tuition and Discounts)← Older edit Revision as of 21:36, 24 March 2008 (view source)Cody (Talk | contribs) m (→Tuition and Discounts)Newer edit → Line 36: Line 36: * Students paying for themselves (not getting reimbursement) and unemployed individuals (verification required), \$298 * Students paying for themselves (not getting reimbursement) and unemployed individuals (verification required), \$298 * Limited scholarships may also be available. * Limited scholarships may also be available. - * Professional members get an additional 20% discount. + * [[Membership|Professional members]] get an additional 20% discount ==Logistics== ==Logistics==

## Objective

The various statistical distributions covered will help you know when assumptions can be made about a normal distribution and how to test whether or not these assumptions are true. Essential descriptive statistics are reviewed and then used in various situations to calculate background, noise, normalization and thresholding. Additionally, hypothesis testing is introduced so that you can assess groups of observations for a particular parameter and calculate whether or not the difference between groups is significant. Data visualization using various graphs will also be reviewed. Armed with these techniques, you will be able to better deal with the challenges of data analysis. Plus, you'll be able to understand and interpret data at a more fundamental level and draw the correct conclusions about them.

The entire course will be conducted in R, a free and open-source package for statistical computing that has become an essential part of the biostatistician's toolbox. Unlike Bioinformatics.Org course CS101B (R for Biologists, Level 1), this course focuses on the mathematical principles of statistical analysis and not on the syntax and functionality of R.

No experience is required, although prior experience with a programming language will be helpful. Math skills will also be useful. This course is certified by the Bioinformatics Organization, Inc., the largest international affiliation in the field, and it will count as 10 "Continuing Scientific Education" (CSE) credits (one credit per contact hour) within the Organization. Students completing the course will receive a certificate attesting to that.

## Course outline

• Day 1: Probability distributions and how to work with them
• Day 2: Descriptive statistics for summarizing vector and matrix data
• Day 3: Student t-tests, Wilcoxon tests for analyzing one and two sample data
• Day 4: Use of the techniques covered in the previous sessions to do a biological data analysis project

## Course schedule

This course has been offered once. Access to completed courses is available to enrolled students only, because of privacy and confidentiality issues. If you are interested in an upcoming course, register using instructions below.

## Registration

Registration comprises of two steps. First, create an online account to access the educational section of our website. Second, register for this course by making a payment using either the online registration form (click on the scheduled course above; use this form only for credit card payments via secured PayPal), or by sending in the mail-in registration form (~150 kB PDF, use this form if paying by US checks, credit card or corporate purchase order). Please check the tuition rates and discounts below.

## Tuition and Discounts

The fee for this course is \$895 USD (Commercial, Government)

Discounted rates are available, as follows:

• Academic and non-profit research organizations, \$597 (USD)
• Students paying for themselves (not getting reimbursement) and unemployed individuals (verification required), \$298
• Limited scholarships may also be available.
• Professional members get an additional 20% discount

## Logistics

Online courses are offered via an online meeting system. Access information will be provided prior to the start of the course. Each lecture will last 45 to 90 minutes, depending on the topics covered. For those who cannot attend the lectures at those times, the lectures will be recorded and placed on the course website as Flash videos (resolution reduced by 30%) each day, within one day. Students will also be able to communicate with the instructor and other students via the course forums. Lecture attendance is therefore not required.

Since this will be an interactive, hands-on workshop, all attendees will need a computer with a broadband Internet connection (1 Mbps or faster is strongly recommended for those watching the live lecture), a sound card with speakers, a modern Web browser, and the Adobe Flash plugin. A microphone and webcam is not required for this course. The necessary software, lecture notes and exercises will be provided.