Simon Fraser University
Engaging the World

Course Outlines

Spring 2026 - EASC 305W D100

Quantitative Methods for the Earth Sciences (3)

Class Number: 2494

Delivery Method: In Person

Overview

  • Course Times + Location:

    Jan 5 – Apr 10, 2026: Tue, 8:30–10:20 a.m.
    Burnaby

  • Prerequisites:

    EASC 101; MATH 152, PHYS 121 or 126 or 102 or 141, and STAT 201 or 270 (all with a grade of C- or better), and six units in any 200-division or higher EASC courses.

Description

CALENDAR DESCRIPTION:

Implementation of mathematical methods and numerical techniques for problem solving in the Earth Sciences. Examples and lab assignments will use Excel spreadsheets and/or Matlab computer programming/display software. Concepts covered include quantitative techniques for field data and error analysis in the geosciences, basic computer programming concepts and numerical modeling of Earth processes. Students with credit for EASC 305 may not take this course for further credit. Writing/Quantitative.

COURSE DETAILS:

In the Earth sciences, we deal with a variety of data acquired by geological mapping, geochemical analysis, and geophysical surveys. Although such data may be quite different, they can have certain common characteristics; for example, some types of data are recorded as a function of time or geographic location. Consequently, there are certain standard approaches to representing such data, understanding their significance, and analysing uncertainties. Students will learn how data can be organised and gain practical experience with some basic techniques that will enable them to develop algorithms for data analysis. While simple data analysis can sometimes be carried out using spreadsheets, many problems will require the use of advanced programming languages such as Python. Geospatial analysis and 3D modelling of various data sets will involve the use of QGIS and Leapfrog Geo, respectively. Lectures will provide the background to the various methods, with the computer-based lab assignments and term project helping to develop skills in technical report writing, practical programming, field data analysis, and 2D/3D modelling.

Provisional course topics:

  • Introductory computing with Python
  • Introductory GIS and 3D modelling
  • Technical writing and Professional presentation skills
  • Univariate/bivariate statistics, tests of statistical significance
  • Principal component analysis
Analysis of spatial data: interpolation, variograms and kriging

Grading

  • Lab Exercises (equally weighted) 20%
  • Term Project - Integrated GIS & 3D modelling 50%
  • Exam 1 15%
  • Exam 2 15%

NOTES:

Python, Leapfrog and QGIS software will be available in the computer lab

Materials

RECOMMENDED READING:

Davis, J.C., 2003, Statistics and Data Analysis in Geology, 3rd Edition, Wiley, ISBN: 978-0-471-17275-8

Petrelli, M., 2021, Introduction to Python in Earth Science Data Analysis: From Descriptive Statistics to Machine Learning, Springer, ISBN: 978-3-030-78054-8

REQUIRED READING NOTES:

Your personalized Course Material list, including digital and physical textbooks, are available through the SFU Bookstore website by simply entering your Computing ID at: shop.sfu.ca/course-materials/my-personalized-course-materials.

Registrar Notes:

ACADEMIC INTEGRITY: YOUR WORK, YOUR SUCCESS

At SFU, you are expected to act honestly and responsibly in all your academic work. Cheating, plagiarism, or any other form of academic dishonesty harms your own learning, undermines the efforts of your classmates who pursue their studies honestly, and goes against the core values of the university.

To learn more about the academic disciplinary process and relevant academic supports, visit: 


RELIGIOUS ACCOMMODATION

Students with a faith background who may need accommodations during the term are encouraged to assess their needs as soon as possible and review the Multifaith religious accommodations website. The page outlines ways they begin working toward an accommodation and ensure solutions can be reached in a timely fashion.