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Quantitative Methods in Planning URP 210
Course Description
This course is designed as a fundamental course in statistical concepts and methods. The basic ideas of the analysis of data and statistical inference are introduced; various methods are explained in sufficient detail so that the student can apply them. Many examples and exercises, chosen from the fields of Architecture and Urban Planning, are given to help the student understand the statistical applications as well as to show interesting questions that can be answered by statistical analysis.
Place and Time of Instruction
- Place: Room # 008 in FED,
- Time: Wednesday from 9:00 am. to 12:00 am.
Prerequisites
- Basic skills of mathematics.
- Basic computer skills of Windows and Microsoft Office.
Teaching Methods
- Theoretical Lectures.
- Mathematical problem solving training.
- SPSS Lab Training.
Course Objectives
1-Overall Aims of the Course:
(1) To emphasize using quantitative methods and principals those are common to urban and regional planning applications.
(2) To introduce a wide range of basic and advanced statistical methods; starting with the simple descriptive methods and reaching to the advanced methods of statistical inference and testing hypotheses.
(3) To enable students to use and integrate proper statistical methods within their different studios' projects in other courses.
(4) To prepare students to implement the scientific research methodology.
2- Intended Learning Out Comes of Course:
a. Knowledge and understanding:
a1- To know about different statistical applications in the field of Urban and regional planning.
a2- To know about different statistical packages; their capabilities and limits.
a3- To focus on using SPSS (Statistical Package for Social Science) in the purpose of implementing different statistical analysis applications.
b. Intellectual Skills:
b1- improve and develop students' skills dealing with urban planning problems using statistical measures.
b2- improve and develop students' skills in a creative manner dealing with planning problems through preparing them to adopt (in the future) a complete quality control system depends on quantitative measures.
c. Professional and Practical Skills:
c1- improve students skills in solving the statistical problems manually through implementing different examples and exercises, mainly chosen from the field of urban planning.
c2- improve students skills in solving the statistical problems using SPSS and compare the results with the manual solutions.
c3- improve students' skills in presenting, discussing and interpreting their final results.
d. General and Transferable Skills:
d1- Through discussions students, start to prefer the scientific thinking dealing with their problems.
d2- Through lab sessions students acquire experience with precise, and quick tools for implementing statistical applications.
d3- Through reviewing solutions of the given examples and exercises students acquire experience with interpreting the statistical results.
Learning Resources
Recommended Books :
[1]
جلال مصطفى الصياد ومحمد الدسوقى حبيب. مقدمة فى الطرق الإحصائية، دار حافظ للنشر والتوزيع، جدة، 2001 (مكتبة جرير)
[2]
عز حسن عبد الفتاح و اسامه حسن عارف. التحليل الإحصائى باستخدام SPSS 14 ، الطبعة الأولى، دار حافظ للنشر والتوزيع، جدة، 2007 (مكتبة جرير)
Internet Sites :
http://www.statsoft.com/
SPSS is the software to be used during the course for implementing different statistical analysis. The training sessions will take place at the computer lab (Room # 206). During the training sessions, computer usage is restricted to SPSS and to files and directories specified by the course instructor. Students may bring and use their own laptops if they wish.
Course Requirements and Grading
Student Assessment:
Grading depends on a number of items:
* Attendance 10%
* Performance during the course (homework assignments & quizzes) 30%
* Mid-Term Exam 20%
* Final Exam 40%
Expectations from Students: Attitudes, involvement, behaviors, skills, and ethics
Students are expected to:
* Have previous knowledge of mathematical skills.
* Actively participate in course activities.
* Follow all given instructions either written or oral.
* Try all exercises either explained during a training sessions or given as homework.
* Seek help from the instructor in case they encounter difficulties while performing the task at hand.
* Turn on homework assignments in time.
Student Responsibilities to the course:
* Course Attendance is mandatory. University regulations with respect to absence will be strictly enforced. Repetitive absence with no acceptable excuse may lead to student exemption from the course.
* Students should do their best to complete all given assignments in time. All students are required to submit both a hard copy and a CD including all the work done during the course activities; all homework assignments, and lab training work. Late submission of assignments may lead to grade reduction, or even assignments refusal.
* Respecting to students' work in the lab, they should take every precaution to keep their files safe. No excuses on the pretext of file loss or damage will be accepted.
Important Rules of Academic Conduct:
* Due to the accumulative nature of the course, understanding of calculations of statistical methods depends on the comprehension of the previous ones. Students are thus required to arrive to class in time. Late arrival with no acceptable excuse would be considered absence, and attendance may be denied. Even if attendance is granted, late students are responsible for all related assignments, since missed parts of a lecture or a lab session would not be repeated for late students.
* Students are trusted unless they behavior otherwise. Any instances of dishonesty or cheating such as duplicating other students work would be taken seriously. Any submitted work that is found to be a duplicate of the work of others would lead to the punishment of all students involved.
* No food or drinks are allowed in the lab.
* Students are expected to follow all agreed upon academic rules of conduct, to show respect to their instructor, classmates, and to the place. Any student who fails to do so would be asked to leave. Proper punishment would be decided either by the instructor or by the department board.
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