Spatial Statistics for GIS Using R

Spatial Statistics for GIS Using R

This course will teach you spatial statistical analysis methods to address problems in which spatial location. This course will explain and give examples of the analysis that can be conducted in a geographic information system such as ArcGIS or Mapinfo.

This course will teach you spatial statistical analysis methods to address problems in which spatial location. This course will explain and give examples of the analysis that can be conducted in a geographic information system such as ArcGIS or Mapinfo.

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Overview

Spatial data are everywhere. Spatial statistical analysis gets behind the map to ask about the data that are mapped and pose questions about the patterns we see. In this course you will learn about the relationship between maps and the data they represent and how such data are coded in the R environment. You will explore point pattern analysis, spatial autocorrelation statistics, and geostatistical interpolation to estimate values across a continuous contour type map.

Learning Outcomes

After completing this course, you will be able to describe spatial data using maps and correctly implement spatial data in R. Students will analyze patterns in point, area, and field data. You will learn to detect non-randomness, measure spatial autocorrelation and create contour maps.

  • Describe spatial data using maps
  • Describe and implement the ways spatial data is represented in R
  • Use spastat to analyze patterns in point data, and detect non-randomness
  • Use spdep to analyze patterns in area data, and measure spatial autocorrelation in lattice data
  • Use gstat to analyze continuous field data and create contour maps

Who Should Take This Course

GIS users, scientists, business analysts, engineers and researchers who need to create, use and analyse maps of geographic data.

Instructors

dr-david-unwin

Prof. David Unwin

Prof. David Unwin, until his retirement in 2002, was Professor of Geography at Birkbeck College, University of London, where he retains an Emeritus Chair in the subject. His work using and developing spatial statistics in research stretches back some 40 years, and he has authored over a hundred academic papers in the field, together with a series of texts and a series of edited collections at the interface between geography and computer science. Having developed the world's first wholly internet-delivered Master's program in GIS in 1998, David Unwin has considerable experience of teaching and tutoring online.  Most recently, in 2012 David has been awarded the Ron F Abler Honor of the Associ...
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Course Syllabus

Week 1

Introducing geo-data and their representation in R

  • Introducing geographical data
  • Representing geographical data in R

Week 2

Analyzing point events using spatstat

  • Introductory methods for detecting non-randomness in dot/pin map distributions

Week 3

Analyzing lattice data using spdep

  • Detecting and measuring spatial autocorrelation in lattice data

Week 4

Analyzing geostatistical data using gstat

  • Creating contour-type maps using inverse distance weighting and geostatistical methods

Class Dates

2020

Jun 5, 2020 to Jul 3, 2020

Oct 23, 2020 to Nov 20, 2020

2021

No classes scheduled at this time.

2022

No classes scheduled at this time.

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Prerequisites

You should be familiar with introductory statistics to the level of correlation and regression.

Introductory Statistics

We assume you are versed in statistics or have the equivalent understanding of topics covered in our Statistics 1 and Statistics 2 courses. but do not require them as eligibility to enroll in this course. Please review the course description for each of our introductory statistics courses, estimate which best matches your level of understanding of the material covered in these courses, then take the short assessment test for that course. If you can not answer more than half of the questions correctly, we suggest you take our Statistics 1 and Statistics 2 courses prior to taking this course.

You should also be familiar with basic operations in R, as covered in R Programming – Introduction Part 1.

R Programming – Introduction Part 1

This course provides an easy introduction to programming in R. NOTE: Jan. 10 session is still open – register for a later class and email ourcourses@statistics.com to switch.
Topic: Data Science, Using R | Skill: Introductory | Credit Options: ACE, CAP, CEU
Class Start Dates: May 15, 2020, Sep 11, 2020

What Our Students Say​

This was a great class. I learned a lot and enjoyed the format. The lessons, assignments, feedback, and discussions were all informative.  I appreciate Professor Unwin's efforts to include references to web sites, journal articles, and books that will be very useful in the future. Thank you!

Frank Voss
United States Geological Survey

This was the first class I've taken in a long time, the first online course I've ever taken, and my first statsics.com course.  I found it very easy to navigate and was pleasantly surprised at how involved the instructor was in the online discussion.  Great class!

Linnea Spears-Lebrun
AECOM

Frequently Asked Questions

Can I transfer or withdraw from a course?

We have a flexible transfer and withdrawal policy that recognizes circumstances may arise to prevent you from taking a course as planned. You may transfer or withdraw from a course under certain conditions.

  • Students are entitled to a full refund if a course they are registered for is canceled.
  • You can transfer your tuition to another course at any time prior to the course start date or the drop date, however a transfer is not permitted after the drop date.
  • Withdrawals on or after the first day of class are entitled to a percentage refund of tuition.

Please see this page for more information.

Who are the instructors at the Institute?

The Institute has more than 60 instructors who are recruited based on their expertise in various areas in statistics. Our faculty members are:

  • Authors of well-regarded texts in their area;
  • Advisory board members;
  • Senior faculty; and
  • Educators who have made important contributions to the field of statistics or online education in statistics.

The majority of our instructors have more than five years of teaching experience online at the Institute.

Please visit our faculty page for more information on each instructor at The Institute for Statistics Education.

Please see our knowledge center for more information.

What type of courses does the Institute offer?

The Institute offers approximately 80 courses each year. Topics include basic survey courses for novices, a full sequence of introductory statistics courses, bridge courses to more advanced topics. Our courses cover a range of topics including biostatistics, research statistics, data mining, business analytics, survey statistics, and environmental statistics.

Please see our course search or knowledge center for more information.

Is the Institute for Statistics Education certified?

The Institute for Statistics Education is certified to operate by the State Council of Higher Education for Virginia (SCHEV). For more information visit: http://www.schev.edu

Please see our knowledge center for more information.

Visit our knowledge base and learn more.

FAQs + Knowledge Base

Related Courses

Mapping in R

This course will teach you how spatial data may be visualized in R and provides a review of a number of other diverse methods for visually representing geographical information in R.
Topic: Analytics, Data Exploration, Using R | Skill: Intermediate | Credit Options: CAP, CEU
Class Start Dates: May 1, 2020, Nov 20, 2020

R Programming – Introduction Part 1

This course provides an easy introduction to programming in R. NOTE: Jan. 10 session is still open – register for a later class and email ourcourses@statistics.com to switch.
Topic: Data Science, Using R | Skill: Introductory | Credit Options: ACE, CAP, CEU
Class Start Dates: May 15, 2020, Sep 11, 2020

R Programming – Introduction Part 2

This course is a continuation of the introduction to R programming.
Topic: Data Science, Using R | Skill: Introductory, Intermediate | Credit Options: ACE, CAP, CEU
Class Start Dates: Mar 13, 2020, Jul 17, 2020, Nov 13, 2020, Mar 12, 2021

Additional Course Information

Organization of Course

This course takes place online at The Institute for 4 weeks. During each course week, you participate at times of your own choosing – there are no set times when you must be online. Course participants will be given access to a private discussion board. In class discussions led by the instructor, you can post questions, seek clarification, and interact with your fellow students and the instructor.

At the beginning of each week, you receive the relevant material, in addition to answers to exercises from the previous session. During the week, you are expected to go over the course materials, work through exercises, and submit answers. Discussion among participants is encouraged. The instructor will provide answers and comments, and at the end of the week, you will receive individual feedback on your homework answers.

Time Requirements

This is a 4-week course requiring 10-15 hours per week of review and study, at times of your choosing.

Homework

Each week has an associated assignment, which, together with following the Lesson, should take 15 or so hours to complete. The assignments are designed to complement and extend the materials in the lesson and will be marked and commented upon by the instructor.

In addition to assigned readings, this course has an end of course final project (required for PASS and ACE candidates).

Course Text

The required text for this course is Geographic Information Analysis, 2nd revised edition by O’Sullivan, D. and Unwin,D. J.

Please order a copy of your course textbook prior to course start date.

Software

R software is used in this course.

Software Uses and Descriptions | Available Free Versions
To learn more about the software used in this course, or how to obtain free versions of software used in our courses, please read our knowledge base article “What software is used in courses?” 

Course Fee & Information

Enrollment
Courses may fill up at any time and registrations are processed in the order in which they are received. Your registration will be confirmed for the first available course date unless you specify otherwise.

Transfers and Withdrawals
We have flexible policies to transfer to another course or withdraw if necessary.

Group Rates
Contact us to get information on group rates.

Discounts
Academic affiliation?  In most courses you are eligible for a discount at checkout.

New to Statistics.com?  Click here for a special introductory discount code.  

Invoice or Purchase Order
Add $50 service fee if you require a prior invoice, or if you need to submit a purchase order or voucher, pay by wire transfer or EFT, or refund and reprocess a prior payment.

Options for Credit and Recognition

This course is eligible for the following credit and recognition options:

No Credit
You may take this course without pursuing credit or a record of completion.

Mastery or Certificate Program Credit
If you are enrolled in mastery or certificate program that requires demonstration of proficiency in this subject, your course work may be assessed for a grade.

CEUs and Proof of Completion
If you require a “Record of Course Completion” along with professional development credit in the form of Continuing Education Units (CEU’s), upon successfully completing the course, CEU’s and a record of course completion will be issued by The Institute upon your request.

ACE CREDIT | College Credit
This course has been evaluated by the American Council on Education (ACE) and is recommended for the the upper division baccalaureate degree, 3 semester hours in data mining, statistics, or computer science. Please note that the decision to accept specific credit recommendations is up to the academic institution accepting the credit.

ACE Digital Badge
Courses evaluated by the American Council on Education (ACE) have a digital badge available for successful completion of the course.

INFORMS-CAP
This course is recognized by the Institute for Operations Research and the Management Sciences (INFORMS) as helpful preparation for the Certified Analytics Professional (CAP®) exam and can help CAP® analysts accrue Professional Development Units to maintain their certification.

Supplemental Information

There is no supplemental content for this course.

Miscellaneous

There is no additional information for this course.

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Spatial Statistics for GIS Using R
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