CP524: Computer Application of the Advanced Statistical Methods and Techniques to City and Regional Planning

Spring 2012-13

Instructor: Prof. Dr. Ayse Gedik (gediksensei@gmail.com)




Introduction and the Purpose of the Course

The course mainly emphasizes “application” of statistical thinking.  This course will provide students an opportunity to synthesize concepts, the logical bases of specific statistical methods and techniques, their “application and interpretation”.  


In the application phase of our course, SPSS will be used. It is important to remember that SPSS is ONLY a TOOL for you.  The course is NOT a SPSS course.  SPSS will be explained in 3-4 hours only.  Subsequently, you will learn spss by doing your lab exercises and homework.


The course basically will include subjects related to selection and description of data, evaluating the data set in terms of the assumptions of the related techniques, formulation of the hypotheses, carrying out the appropriate tests, and interpretation of the results. The subjects such as the mathematical proofs will not be covered.


During the first two weeks, students are asked to learn or review some basic notions of the statistics (such as, descriptive statistics, and hypothesis testing (meaning of null hypothesis, Type I and II errors, hypothesis testing, and significance level).   This first step is very important.  Otherwise, you cannot understand your required readings and the lectures.


Subjects to be Included

Statistical methods and techniques to be discussed will be mainly related to regionalization/grouping:

* Introduction, and overview of descriptive statistics and hypothesis testing

* Anova (analysis of variance)

* Discriminant a. (and logistic regression)

* Factor a.

* Cluster a.

* Regression a.

The purpose is not to include many techniques; but to learn the common principles and pitfalls in statistical analyses so that you can carry out reliable and meaningful statistical analyses on your own in the future. 


The Method of the Course

The course will be in the form of a combination of lectures and seminars; and the use of computers rather than merely formal lectures.  Computer package program of SPSS/WIN 20.0) will be used on personal computers in Regional Planning studio our in the computer room at the Faculty of Architecture. 


Besides attending the lectures, required readings, lab exercises and homeworks are very important for you to understand the course.  Remember the famous saying:






(a)  Lab Exercises: After each technique, you will work on your “lab exercise” in the computer lab.  I and your Research Assistant will help you.  The “lab exercises” will be same as the examples presented and explained in the SPSS Manuals.   It is for your benefit, if you carry out these examples, before you start working on your “homework”.  This might be important for you since you will do your homework on your own without my direct help. 


(b) Homework:  You will have one homework. You can do your homework alone or as a team of maximum two students.  Each of you will have a different data set out of which you will produce your hypothesis.  It is recommended that your homework be on Anova because it is simpler than other techniques; and thus it will be easier for you to learn the basic principles of carrying out the statistical techniques and their interpretation. 


(c) Exam:  You will have one short exam for each subject/technique (after you submit your respective “lab exercise”).  The exam will partly be an open-book exam.  You are allowed to bring to the exam one page of A4 size (back and front) on which you can write anything you like related to the exam.  



* Lab exercises:   30 %                           

* Homework:        35 %

* Exam(s):            35 %



Extensive reading list is attached.  However, the main source of your readings is listed below.   The pages from the SPSS manuals will be available in the photocopy room.


***  SPSSWIN manuals (application manuals with step-by step empirical examples, and user manuals about running the program).


***  J.F. Hair, R. E. Anderson, R. L. Tatham, W. C. Black (1998) Multivariate Data Analysis, Fifth Edition, NY: Prentice Hall (Call No: QA 278  1134).


***  B. G. Tabachnick, L. S. Fidell (2001) Using Multivariate Statistics, Fourth Edition,

London: Allyn and Bacon (Available in the Book Store).


*** Other optional readings will be in the Files-Dosya (1 and 2) under CP524 in the photocopy room.  The lists are attached.


***Internet sources (from universities) will be referred during the lectures.