I’m on the last legs of my program now (not *my* last legs). My eighth core course to date is **Spatial Statistics**.

Statistics can help us to understand facts by grouping them into patterns that make sense for the data. For example, consider the graph to the right. It is a scatterplot where each point represents the value of magnesium for a given value of calcium in limestone.

It is clear from the pattern of the points that there is relationship between these two values. As calcium increases, magnesium decreases. But can we define this relationship more precisely?

Looking at the second graph we see a *regression line* drawn through the points. This line tells us the expected value for magnesium for a given value of calcium.

Now there may never be an exact calcium / magnesium value along the regression line. Also, if we add more points to the scatterplot and recalculate, the regression line is likely to change. The point of the regression is not to foretell all future calcium / magnesium points. Rather, it gives us a clear picture of the relationship between calcium and magnesium as it exists now.

Pingback: womens nike air max thea 599409 416 blue white trainers amazon.co.uk shoes bags

Pingback: cheap professional sports jerseys twitter.com

Pingback: throwback matt lengel 82 houston texans jersey

Pingback: uk trainers nike flyknit trainer oreo

Pingback: 872087 001 nike internationalist lt17

Pingback: john undercover clothing

Pingback: nike tiempo legend v dove grey uk trainers

Pingback: vert gris adidas climacool boost

Pingback: nike logo basketball pinterest.com

Pingback: vert noir nike dunk sky hi essential