Spring 2016
SYLLABUS and other useful information
Lectures:  TR 2:10  3:30, Snedecor 3121 
Instructor:  Philip Dixon
pdixon at iastate.edu 2121 Snedecor Hall
5152942142

Office Hours:  Th: 910am, 12pm. 
Questions::  Please feel free to email pdixon at iastate.edu anytime with questions or comments. 
Text:  Bivand, Pebesma and GomezRubio, 2013. Applied Spatial Data Analysis with R, 2nd ed. Springer 
Goals:

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  
1  Jan 12, 14  Spatial Data, Sources of randomness, Graphical Spatial Analysis 

2  Jan 19, 21  Statistical Preliminaries, Using R 

36  Jan 26  Feb 18  Geostatistics Variograms, Kriging 

7  Feb 26  Exam 1 due, 5 pm  
78  Feb 23  Mar 3  Areal data, Moran's I  
911  Mar 8  31  Spatial point patterns  
12  Apr 8  Exam 2 due, 5 pm  
1214  Apr 521  Topics determined by class interest. Probably including: Spatial analysis of designed experiments Simulation of spatial data and others 

15  Apr 2628  Project Presentations  
Finals week  May 6, 9:4511:45  Project presentations (potentially)  
Details:
Student background:  The official prerequisite for Stat 406 is 6 credits in statistics. I will assume you know applied nonspatial 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 graduatelevel 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:

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 onepage summary of your proposed project will be due midsemester.
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, 9:4511:45. The project grade will be based on your presentation, your attendance at other presentations, and your questions about other's presentations. 
Other
questions: 
Please ask in class or email me: pdixon at iastate.edu 
Disability accommodation: 
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 5152947220 or email disabilityresources@iastate.edu . 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: 
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 5152941020 or email dsosas@iastate.edu, or contact the Office of Equal Opportunity and Compliance at 5152947612. 
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 academicissues@iastate.edu. 