Warning: This document is for the development version of IntroQG. The main version is master.

Lesson overview

In this week’s lesson we will learn a few ways in which observations (data) can be compared to predictions. As was the case last week, we will continue to focus more on quantitative and geological concepts, rather than learning new Python skills.

  1. Least squares regressions
  2. Linear correlation
  3. Goodness-of-fit calculations
  4. Exercise 2

Learning objectives

After completing this week’s lesson you should be able to:

  • Understand the general concept of fitting a model to data
  • Calculate the goodness-of-fit for discrete point data using the weighted sum of the squared errors
  • Calculate unweighted best-fit lines to x-y data using a least squares regression