Flexible, affordable statistics education.
Designed to help you master the software you need to enhance your skills and the practical experience you need to get ahead.
Designed to help you master the software you need to enhance your skills and the practical experience you need to get ahead.

This online course covers the application of Bayesian statistical methods to environmental data and decision-making and EPA's DQO's.
Instructor(s):Environmental consultants, regulators, policy-makers, researchers and managers. Any analyst who has difficulty translating traditional statistical analysis into decisions.
Dates:Add $50 service fee if you require a prior invoice, or if you need to submit a purchase order or voucher, pay by wire transfer or EFT, or refund and reprocess a prior payment. Please use this printed registration form, for these and other special orders.
Courses may fill up at any time and registrations are processed in the order in which they are received. Your registration will be confirmed for the first available course date, unless you specify otherwise. Multiple course registrations may be entitled to tuition discounts; read more.
The course provides decision analysis approach to environmental statistics and EPA's DQO's
Traditional frequentist methods in statistics are often ill-suited to environmental problems, where the analysis of data typically must result in decisions with costs and benefits attached. These costs and benefits are rarely included in traditional statistical analyses. In this course, participants will learn to incorporate knowledge or estimates of the "state of the world," as well as the costs and benefits of alternative actions (or inaction), via the application of Bayesian statistical methods to environmental data and decision-making.
This course is a core requirement or elective in the following Program(s) in Advanced Statistical Studies (PASS):
Prerequisite(s):If you are unclear as to whether you have mastered the requirements, test yourself with these placement exams here.
Participants should also be familiar with the materials covered in Introduction to Bayesian Statistics.
This course takes place over the internet, at statistics.com for 4 weeks. During each course week, you participate at times of your own choosing - there are no set times when you must be online. Course participants will be given access to a private discussion board. In class discussions led by the instructor, you can post questions, seek clarification, and interact with your fellow students and the instructor.
The course typically requires 15 hours per week. At the beginning of each week, you receive the relevant material, in addition to answers to exercises from the previous session. During the week, you are expected to go over the course materials, work through exercises, and submit answers. Discussion among participants is encouraged. The instructor will provide answers and comments, and you will receive individual feedback on your homework answers.
As you begin the class, you will be asked to specify your category.
This course offers continuing education units (CEU's). For those successfully completing the course (generally this means marks of 50% or better on the homework), 5.0 CEU's and a record of course completion will be issued by Statistics.com, upon request.
Course materials will be provided.
Software:R is used in several homework exercises for weeks 3 and 4, but a lack of facility with R will not prevent you from gaining most of the benefit of this course. Functionality in Excel can, to a large degree, substitute for the use of R. For more information about obtaining free or nominal cost versions of standard software packages, click here.