Lesson 2 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.

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

Lesson materials
----------------

.. Lesson material will be made available after class.


Lesson notebook file(s)
~~~~~~~~~~~~~~~~~~~~~~~

.. admonition:: Lesson 2 notebook file(s)

    `Least squares demonstration notebook <../../notebooks/L2/least-squares-from-class2025.html>`__

Lesson video(s)
~~~~~~~~~~~~~~~

.. admonition:: Lesson 2 - Least squares, correlations, and goodness-of-fit
    :class: admonition-youtube

    ..  youtube:: 1g0CmxV3LD0

    Dave Whipp, University of Helsinki @ `Quantitative Geology channel on Youtube <https://www.youtube.com/channel/UClNYqKkR-lRWyn7jes0Khcw>`_.