STAT 406: Spatial Statistics

Spring 2016

SYLLABUS and other useful information

LecturesTR 2:10 - 3:30, Snedecor 3121
Instructor:  Philip Dixon
pdixon at

2121 Snedecor Hall
Ames IA 50011-1210

on campus: 4-2142

Office Hours: Th: 9-10am, 1-2pm.
Questions:: Please feel free to e-mail pdixon at anytime with questions or comments.
Text Bivand, Pebesma and Gomez-Rubio, 2013. Applied Spatial Data Analysis with R, 2nd ed. Springer
1) Understand and appropriately use common methods for analyzing spatial data.
2) Be able to apply these methods to novel problems. 
Grading: Homework assignments, 25 pts each: 100 pts 
Take home exams, 75 pts each: 150 pts 
Project: 50 pts  
Course Outline :(subject to change)
Week Dates Topic
Jan 12, 14 Spatial Data, Sources of randomness,
Graphical Spatial Analysis
Jan 19, 21 Statistical Preliminaries,
Using R
3-6 Jan 26 - Feb 18 Geostatistics
Variograms, Kriging
7 Feb 26 Exam 1 due, 5 pm
7-8 Feb 23 - Mar 3 Areal data, Moran's I
9-11 Mar 8 - 31 Spatial point patterns
12 Apr 8 Exam 2 due, 5 pm
12-14 Apr 5-21 Topics determined by class interest. Probably including:
Spatial analysis of designed experiments
Simulation of spatial data
and others
15 Apr 26-28 Project Presentations
Finals week May 6, 9:45-11:45 Project presentations (potentially)

Student background: The official prerequisite for Stat 406 is 6 credits in statistics. I will assume you know applied non-spatial statistics at the level of Stat 401. Understanding spatial statistics requires some concepts of mathematical statistics (e.g. Stat 341/2 or Stat 447). I will teach what is needed. You will not be required to do any mathematical staistics, but knowing the concepts aids understanding course material.
Grading: Most, but not all, students in this class are grad students. I will use a graduate-level grading scheme (mostly A's and B's) but I reserve the right to give lower grades when appropriate.
I will expect you to ask questions about anything you don't understand, i.e., behave like a graduate student.
Computing: Spatial statistics has gone from the impossible to the possible because of modern computing. We will discuss the use of packages in R to analyze data. This is not the only way to analyze spatial data. For example, the ARC/GIS platform has a very good geostatistics module. However, R is the only platform that provides all the analyses we will use. No previous experience in R is expected. We will discuss how to use R. You will be expected to use R for homework and exams. I expect you to ask questions if you don't understand something.
"Lab time" There is no separate lab period for this course. Computing is a huge part of spatial statistics. The Thursday class period will meeting in the upstairs computer room in Snedecor (3121). Some days I will lecture there. Most days, I will discuss computing and have you work through exercises for at least part of the time. I will circulate and answer questions. You are welcome to bring and use your own laptop.


Homework assignments will be posted on the web site and announced in class.
Goal is to provide practice using statistical methods to answer interesting/relevant questions. 
Discussion with friends and classmates is strongly encouraged
Write up your answers yourself. Copying papers is not a good way to learn and will not be tolerated. 
Late homework will be penalized 3 points per day late and not accepted after solutions are posted.
Solutions will be posted on the class web page soon after the due date.
Exams: My goal is to see whether you can use what you have learned to analyze data. Exams will be take home exams. The exams are open notes and open book. I will give you study descriptions, data, and some questions to answer. You will be expected to use the computer. You must work individually, on all aspects of the exam (deciding what method to use, coding the analysis, interpreting the results, and writing up your answers). I am very willing to answer questions about code and help you fix computing problems. I will answer other questions to the extent possible. If in doubt, ask me. Don't ever ask a friend.

Because the exams are takehome, there will be no makeup exams. If you are out of town during an exam week, talk with me about options.

Projects: The project provides a chance to explore a data set or topic that interests you. Potential projects include analyzing data that you have collected, analyzing a class data set in a way not done in class, analyzing data found on the web, or learning more about a topic or extension of a topic.

A one-page summary of your proposed project will be due mid-semester.
At the end of the semester, you will give a 15 minute presentation that describes
if a data analysis: your question and data, your method(s), and your results
if researching a topic: your topic, why it is interesting, and a summary of what you have learned. You will have 5 minutes to answer questions.

I expect everyone to be engaged with the project presentations and ask questions. Part of your poject grade will be based on the number and quality of questions you ask.

Projects will be presented during the last week of class and if necessary during the regularly scheduled final exam time. The tentative final exam schedule lists Friday, May 6, 9:45-11:45.
Presentation times will be assigned randomly.
DO NOT buy tickets to leave Ames before the final exam without talking with me first. If we have project presentations during finals week, you will be expected to attend the final.

The project grade will be based on your presentation, your attendance at other presentations, and your questions about other's presentations.

Please ask in class or e-mail me:  pdixon at 
Iowa State University complies with the Americans with Disabilities Act and Sect 504 of the Rehabilitation Act. If you have a disability and anticipate needing accommodations in this course, please contact (Philip Dixon) to set up a meeting within the first two weeks of the semester or as soon as you become aware of your need. Before meeting with me, you will need to obtain a SAAR form with recommendations for accommodations from the Disability Resources Office, located in Room 1076 on the main floor of the Student Services Building. Their telephone number is 515-294-7220 or email . Retroactive requests for accommodations will not be honored.
Academic dishonesty The class will follow Iowa State University’s policy on academic dishonesty. Anyone suspected of academic dishonesty will be reported to the Dean of Students Office

To clarify how this applies to your work in this class:
On homework assignments: I encourage you to help each other interpret the problems, write code, debug code, and interpret the output. You may share code, but I encourage you to understand that code even if you didn't write it. You are required to write your answers in your own words.
On exams: You are to do all work individually.

Dead Week: This class follows the Iowa State University Dead Week guidelines as outlined here
Please note that project presentations are scheduled for dead week.
Harassment and Discrimination: Iowa State University strives to maintain our campus as a place of work and study for faculty, staff, and students that is free of all forms of prohibited discrimination and harassment based upon race, ethnicity, sex (including sexual assault), pregnancy, color, religion, national origin, physical or mental disability, age, marital status, sexual orientation, gender identity, genetic information, or status as a U.S. veteran. Any student who has concerns about such behavior should contact his/her instructor, Student Assistance at 515-294-1020 or email, or contact the Office of Equal Opportunity and Compliance at 515-294-7612.
Religious Accommodation: If an academic or work requirement conflicts with your religious practices and/or observances, you may request reasonable accommodations. Your request must be in writing, and your instructor or supervisor will review the request. You or your instructor may also seek assistance from the Dean of Students Office or the Office of Equal Opportunity and Compliance.
Contact Information: If you are experiencing, or have experienced, a problem with any of the above issues, email