Online Spring, Fall, and Summer Credit: 3 graduate Instructor(s): John Long |
Course Description
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
R
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.
The summer course may require up to 15 hours per week, since it is an 8 week course
instead of a typical 16 week course.
Instructor(s)
Dr. John Long is an Associate Professor of Environmental Physics and the Chair of
the Department of Science and Mathematics at Northern State University. He has a BS
in Applied Mathematics from the State University of New York, a MS degree in Environmental
& Ecological Statistics and a PhD in Ecology and Environmental Sciences, both from
Montana State University. His area of expertise is the mathematical, statistical,
and physical aspects of the environment with a focus on the spatial and temporal modeling
of land-use/land-cover changes. Dr. Long is also a part of the SEA-PHAGES team trained
by the Howard Hughes Medical Institute to discover new viruses in environmental samples.
Prerequisites
M121 - College Algebra or equivalent
Time Commitment:
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.
Required Books/Materials
- The Statistical Sleuth: A Course in Methods of Data Analysis
Edition: third Author(s): Fred Ramsey, Daniel Schafer Publisher: Brooks Cole; 3rd edition (May 2, 2012) ISBN13: 978-1133490678 ISBN 10: 1133490670 Price new: $141hardcover; $147 paperback on Amazon.com (Less expensive used copies
and electronic versions should be available online.)
Computer Requirements:
- 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
start date.
For More Information
For course information: Please contact Marni Rolston 406-994-2029 mrolston@montana.edu
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
system, MyInfo.
Registration requires a PIN number. Learn how to find your PIN.
Once you have your PIN, learn how to register through MyInfo.
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