Aug 26 - Dec 13, 2019
Credit: 3 graduate
Instructor(s): John Long
The modern sciences are fundamentally data-driven and this course focuses on making
sense of data, both quantitatively and conceptually. It is designed to give students
the quantitative and conceptual skills necessary for the online Masters Program in
Environmental Sciences. Topics include a review of relevant algebra skills, methods
to describe data, inferential statistical methods, sampling, experimental design,
and regression. The course uses software to do much of the computational and graphical
work so students can focus on interpretation. This course focuses on analysis and
interpretation of data in environmental science. Students will gain a working knowledge
of the statistical concepts needed for the critical interpretation of scientific research.
The course is based on readings from the textbook, course notes, and from primary
literature (journal articles). Students will complete quantitative and interpretive
exercises. In addition, students will learn the basics of the statistical program
Meeting Place and Times
Participants log in to the course at a time of day that best fits their schedule.
It is necessary to connect at least 4 - 6 times per week and spend 8 - 10 hours per
week while the course is in session, either online or offline working on course related
assignments, to stay current and successfully complete this 3 credit graduate course.
John Long, PhD. My research interests are focused on understanding changes in environmental
and agricultural systems. In particular, I focus on spatial and temporal modeling
of land-use/land-cover change and on improving satellite-based remote sensing techniques
to better monitor these changes. My approach to research is interdisciplinary, quantitative,
and highly collaborative, as it encompasses a wide variety of target systems. Current
projects include: (1) a study that has identified significant temporal changes in
the seasonality of tornado occurrences in the central US Great Plains; and (2) a project
to map bark-beetle mortality as a biofuel feedstock using aerial and satellite-based
imagery, including within-pixel percent mortality.
M121 - College Algebra or equivalent
8-12 hours per week. If you are unfamiliar with this field of study and/or method
of delivery, you may require more time.
Tuition and Fees
See the Online Tuition, Fees and Financial Aid page.
If you are also taking a face-to-face course, please refer to the MSU Fee Schedules.
- The Statistical Sleuth: A Course in Methods of Data Analysis
Author(s): Fred Ramsey, Daniel Schafer
Publisher: Brooks Cole; 3rd edition (May 2, 2012)
ISBN 10: 1133490670
Price new: $158 (Less expensive used copies and electronic versions should be available
- Internet access
- A device and browser that pass the system check for Brightspace LE, MSU's learning management system.
This course uses a learning management system. You will learn more closer to the course
For More Information
For course information: Please contact Marni Rolston 406-994-2029
How to Register
You must be accepted as a student to Montana State University to take this course.
Learn how to apply.
After your application has been accepted, you will register via MSU's online registration
Registration requires a PIN number. Learn how to find your PIN.
Once you have your PIN, learn how to register through MyInfo.