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Overview

By now we’ve looked at functional modeling in some detail, and at linearization of our parametric functional models.

Now it’s time to benefit from all that work – you’re finally ready to estimate the parameters of interest!

This topic is a quick but practical introductory treatment of: 1) geospatial estimation using least squares; 2) using Excel to make quick work of the basic estimation process; and 3) the basics of error propagation.

By the time you’re done, you will have what you need to solve a whole bunch of practical parametric geospatial estimation problems on your own.

What I’m sharing here is one of the most practical bits of my toolbox and I hope it helps you as much as it’s helped me.

Unlike most of our other topics so far, this is another that contains an animated whiteboard video. This means that you can check out the lecture and examples on your own time and at any time – now as you take the course, or in a year’s time when you need to check in again for something you’re coding, or even further down the road.

Completing this will also earn you a mini-badge (if you are signed in).

Directions

1. Watch the video in the lessons below and do the associated self-assessments.

2. We won’t be covering this material in class so be sure to add to your “perfect set of lecture notes” as you see fit. As always, these are carefully designed to help you do well on the related quiz and final exam. Be sure your notes make everything handy because just like skipping a class, you likely won’t have time on an exam or on the job to watch the videos for the first time.

3. Once you’ve finished, you’ll pick up the associated mini-badge (as long as you’re signed in). I don’t mark the mini-badges in the course, as you know. They’re just a way for you and me to know when you’ve finished the task. As usual, the content itself will be audited through the self-assessments. And we’re always happy to help with those, so don’t hesitate.