Skip to main content

Spatial Statistics in R

Learn how to make sense of spatial data and deal with various classes of statistical problems associated with it.

Start Course for Free
4 Hours16 Videos60 Exercises9,205 Learners4950 XPSpatial Data Track

Create Your Free Account

GoogleLinkedInFacebook

or

By continuing, you accept our Terms of Use, our Privacy Policy and that your data is stored in the USA.

Loved by learners at thousands of companies


Course Description

Everything happens somewhere, and increasingly the place where all these things happen is being recorded in a database. There is some truth behind the oft-repeated statement that 80% of data have a spatial component. So what can we do with this spatial data? Spatial statistics, of course! Location is an important explanatory variable in so many things - be it a disease outbreak, an animal's choice of habitat, a traffic collision, or a vein of gold in the mountains - that we would be wise to include it whenever possible. This course will start you on your journey of spatial data analysis. You'll learn what classes of statistical problems present themselves with spatial data, and the basic techniques of how to deal with them. You'll see how to look at a mess of dots on a map and bring out meaningful insights.

  1. 1

    Introduction

    Free

    After a quick review of spatial statistics as a whole, you'll go through some point-pattern analysis. You'll learn how to recognize and test different types of spatial patterns.

    Play Chapter Now
    Problems in spatial statistics
    50 xp
    Simple spatial principles
    100 xp
    Plotting areas
    100 xp
    Uniform in a circle
    100 xp
    Simulation and testing with spatstat
    50 xp
    Quadrat count test for uniformity
    100 xp
    Creating a uniform point pattern with spatstat
    100 xp
    Simulating clustered and inhibitory patterns
    100 xp
    Point pattern testing
    50 xp
    Further testing
    50 xp
    Nearest-neighbor distributions
    100 xp
    Other point pattern distribution functions
    100 xp
    Tree location pattern
    50 xp

In the following tracks

Spatial Data

Collaborators

tommyjee
Tom Jeon
richie
Richie Cotton
Barry Rowlingson Headshot

Barry Rowlingson

Research Fellow at Lancaster University

Barry Rowlingson is a Research Fellow in the Lancaster Medical School, part of the Faculty of Health and Medicine at Lancaster University. His primary field of research is statistical applications in epidemiology and other health-related areas. He plays assorted instruments, takes pictures in exotic places, and drives an old Land Rover.
See More

What do other learners have to say?

Join over 10 million learners and start Spatial Statistics in R today!

Create Your Free Account

GoogleLinkedInFacebook

or

By continuing, you accept our Terms of Use, our Privacy Policy and that your data is stored in the USA.