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.


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

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 (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

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.