UPP 503 Data Analysis for Planning and Management Time: Monday/ Wednesday, 1 – 2:30 pm Class Room: 2115 2ADH Instructor: Sue McNeil Office: 340 CUPPA HALL E-mail: [email protected] Phone: (312) 996 9818 Office Hour: by appointment TA: Geoff Moen Office: 244 CUPPA HALL E-mail: [email protected] Phone: (612) 386-3690 Office Hour: TBA Course Description This course introduces students to data analysis techniques most commonly used in urban planning. Topics to be covered include: presentation of data, measure of central tendency and dispersion, probability concepts, sampling, hypothesis testing and confidence intervals, analysis of categorical variables, and linear regression. Students will also learn to use the statistical computer package to clean, manage, and analyze data. Text Alan Agresti and Barbara Finley. Statistical Methods for the Social Sciences, Third Edition. Prentice Hall, 1997 (required) ISBN: 0-13-526526-6 In addition, handouts will be given to supplement the text when necessary. Blackboard CourseInfo CourseInfo is basically a Web site dedicated to this course. It can be accessed from http://blackboard.uic.edu/. You login with your UIC netid (the id you use for email) and password. I will post assignments, answers, grades, and announcements on the Blackboard CourseInfo. Communication Often, I will use the e-mail feature of CourseInfo to make important announcements regarding assignments and exams. To be included in the CourseInfo e-mail list, you must obtain an UIC e-mail account (with "uic.edu" domain) or if you are using an off-site account work with the ACCC to set it up as your UIC account before the first day of the class. Requirements •The course will be taught using a lecture format with a midterm and final exams, homework assignments, and computer assignments. Grades will be determined by: Midterm (20%) Final (30%) Homework (15%) – The lowest grade will be dropped Computer Assignments (30% - 2 submittals) Attendance and class participation (5%)•You are encouraged to form study groups; however, assignments must be done and submitted individually. •Late submittals will not be accepted. If you have to miss a class, submit the assignment in my mailbox before the class time. • The homework submittals, except for the computer assignments, do not have to be typed, but must be neat and professional, or they may not be graded. •You will need a hand calculator with a square root function. Even though other functions such as memory and power functions may be helpful, your first priority for choosing a calculator should be the ease of use. • Please turn off the cell phones before entering the classroom. Study Habits Just like sports, mathematics is learned through practice and repetition. In fact, there is some evidence to suggest that some very smart people have trouble with mathematics in school because it is the first subject where natural intelligence is not enough. In this course, you are expected to spend five to ten hours every week to "practice" statistics. There are two common mistakes that prevent students doing well in this course. The first is that they try to digest everything by reading textbooks. In this course, you will need to read the textbook and also do the problems to practice the concept you learn from reading. Reading the textbook for hours until you completely understand the content before doing problems will not help you do well in this course. You should combine reading and doing the problems. Many concepts in statistics are unintuitive, and are difficult to understand without concrete example in front of you. This textbook contains a lot of good examples. They should provide "recipes" you can use to solve problems. I will also provide plenty of examples in the class. The key for doing well in this course is to use the problems and reading assignments in combination to help you understand the concepts. The second common mistake is to fall behind by procrastinating. You will find this course to be relatively easy (although time consuming) as long as you stay on top of the materials presented each week. However, once you fall off the pace, it will be difficult, if not impossible, to catch up. If you have a problem keeping up with the course, please talk to me or Geoff before it is too late. Personal attention is a luxury we can provide at graduate level and we are here to help. Cheating and Plagiarism Discussion and interaction is a good foundation for learning. Discussion and collaboration are encouraged. However, each student is expected to turn in a complete and unique solution for homework and individual projects. When computer analysis is used each individual is expected to complete the analysis independently even when a group effort is made to identify and explore solution methods. Discussion and collaboration on in-class and take home exams (given at the discretion of the instructor) is unacceptable.If you don’t understand what plagiarism is take a look at the following website produced by the School of Education, Indiana University, Bloomington, IN. http://www.indiana.edu/~istd/overview.html Academic dishonesty (plagiarism or cheating) will be dealt with in accordance with university policy. At a minimum you will receive a zero for the work you turned in that was not your own. University policies can be found at: http://www.uic.edu/depts/sja/integrit.htm http://www.uic.edu/depts/sja/chpt3.htm#3Tentative Schedule Date Topic Reading Due Dates 1/10 Review Syllabus and Course Requirements Hand outs 1/12 No class Hand outs 1/14-1/16 Optional Math review – handouts – UTC conf room – CUPPA Hall 340. Options: Fri 1/14 2-3 pm, Mon 1/17 – 5-6pm, Tues 1/18, 5-6 pm or by appointment 1/17 No classes – Martin Luther King Day 1/19 Introduction, Sampling and Measurement Ch. 1, 2 (read carefully) Homework 1 due Homework 2 due 1/24 Tables and graphs Ch. 3.1, 3.2 1/26 Homework 3 due 1/31 Measures of central tendency and variation Ch. 3.3, 3.4, 3.5, 3.6 2/2 Homework 4 due 2/7 Probability and sampling distributions Ch. 4.1, 4.2, 4.3 2/9 Homework 5 due 2/14 Probability and sampling distributions (cont.) Ch. 4.4, 4.5 2/16 Homework 6 due 2/21 2/23 Confidence intervals, sample size requirement Ch. 5.1, 5.2, 5.3, 5.4, 5.6 Homework 7 due 2/28 Midterm exam 3/2 Computer Asst 1. 3/7 Hypothesis testing (part 1) Ch. 6.1, 6.2 3/9 Homework 8 due 3/14 Hypothesis