Economics 203 Syllabus Economic Statistics II Sections AL1, BL1 Fall 2011

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Economics 203 Syllabus Economic Statistics II Sections AL1, BL1 Fall 2011 Instructor: Professor Joseph A. Petry Office: 116 David Kinley Hall Phone: 333-4260 e-mail: jpetry@illinois.edu Office hours: Th 8:30 9:30 Lecture hours: M/W 3:00 3:50 (AL1); M/W 4:00 4:50 (BL1) Lecture Section: AL1, BL1 Lecture Location: 141 Wohlers Hall Lab Time: Varies by TA section Lab Days: Friday Lab Location: 901 W. Oregon, Room 101 TA Office Hours: See Compass for schedule TA Contacts: Head TA Yashar Heydari Baradehi heydari1@illinois.edu Others TBA Course Website: https://compass.illinois.edu Homework Platform: http://lon-capa.uiuc.edu Required Texts: Keller, Statistics for Management and Economics, Ninth Edition (7 th or 8 th editions would be fine as well). South-Western/Cengage. Petry, Economics 203 Course Packet. Fall 2011. Required Materials: Basic financial or statistical calculator. You should ALWAYS bring your calculator to class! We have found that the Texas Instruments BAII Plus is useful, and is often used in other classes. We will provide basic instructions in the use of this calculator in class (and only this calculator). To insure fairness for all students, calculators with functionality beyond the BAII Plus, will NOT be permitted for use on exams. Graphing calculators therefore will NOT be permitted during exams. 1

Course Objective: Statistics is the means by which we extract information from data. That's it, nothing more! And yet, by the end of this course you will have spent at least two full semesters learning how to best accomplish this. A famous statistician once said: "without data, we are just another person with an opinion". Obtaining data, and analyzing it properly, can vastly enhance the influence you have in your professional life and community, as well as allow you to make better decisions in your personal life. Our own real-world experience has taught us that statistics is probably the single most useful tool one can learn as a student, irrespective of your major. As you will find, statistical analysis can be applied to nearly every field of human endeavor. We have put together a course that we hope will make learning this important material as successful and enjoyable as possible. In designing the specifics of the course, we have laid out four key objectives that we hope to accomplish before the semester ends. These four objectives have guided all our decisions in terms of course structure, content and administration. At the end of this course, students should: 1. Understand the relevance of statistics in their future course-work and professions 2. Be trained to identify the proper statistical technique to apply to a problem 3. Be adept at finding the answers to statistical queries using excel 4. Be able to properly interpret the results of their analysis. Course Content: Students must have completed a course on probability and statistical analysis before becoming eligible to take Economics 203. The best course to meet this requirement is Economics 202 at the University of Illinois. Inferential Statistical Analysis is the common thread tying the topics of Economics 203 together. In this course we briefly review single population cases of hypothesis testing and confidence interval formation before extending this analysis to two population cases. We emphasize mean, variance and proportion as the parameters of interest. We also cover single-factor Analysis of Variance. The most significant portion of the course is regression analysis. We consider simple and multiple regression, consider assumption violations and how to handle them as well as consider qualitative variables, transformations, curvilinear relationships and model building. We end the course with time series analysis. Course Grade: Mid-term Exam I 20% Mid-term Exam II 25% Final Exam 30% Homework 20% Project I 2.5% Project II 2.5% 2

Grading Scale: The scale used to assign letter grades in the course will be established by the instructor at the end of the semester. A +/- scale will be used. The cut-offs for +/- will also be established by the instructor at the end of the semester. Once the scale is assigned by the instructor at the end of the course, no exceptions will be made. We do not round grades up. Exams: There will be three exams (two midterms and a final) given during the semester. Each mid-term will only cover the material since the last exam. The final exam will be comprehensive. Basic calculators will be permitted, and you will be provided with a formula sheet--identical to the one at the back of your course-packet for use during the exams. Students are required to have their University of Illinois Student ID with them to take their exam. Students who do not have their ID with them for the exam may not be allowed to take the exam. This policy is necessary for us to insure the integrity of the exams. We only offer conflict exams if a student qualifies for such an accommodation under university guidelines. The university policy is stated in the Student Code. If a student is unable to attend the conflict exam, then the weight of the missed exam will be added to the weight of the final exam at the end of the semester. If you believe you are eligible for a conflict exam, you must notify your TA in writing during the first week of class. If you do not notify your TA in a timely fashion, you may not be eligible for the conflict. Homework: Statistics can only be learned one way--doing a lot of problems. As a result, homework represents an important part of this course. You will be assigned homework after nearly every lecture. All homeworks are to be turned in electronically using Lon- Capa. Homework is due no later than 3:00am, the Monday morning of the week following the lecture. No late homeworks are accepted. If you are having trouble with your homework, please check the Compass Discussion Board for assistance, it is monitored closely by our TAs for this purpose. Emergencies, illness and the like do occur for even the best students, so to account for this, we will drop your two lowest homework scores at the end of the semester. There will be NO make-up homework as a result however. This policy will apply even if your absence was excused. Projects: There will be two projects assigned during the course. These are an important part of the overall course, as they are designed to replicate the application of statistics in the real-world. Each project will be done in teams of four students. Teams will be formed in lab with guidance from your TA. If you are not in class the day that the teams are formed, it is your responsibility to track down your team. To receive credit for each of the projects, you must complete the version of the project that is assigned to your team, and each team member must submit the completed quiz individually. Project I will be an application of simple regression, and is modeled around a project that students taking Finance 300 (Financial Markets) are required to complete. Project II is an application of multiple regression involving the real estate market. This project involves material you learn in Finance 241 (Fundamentals of Real Estate). 3

The projects will be completed using Excel. Each individual in the team will need to turn in the answers as obtained through your group work via Lon-Capa, similar to a Homework assignment. The difference between the Projects and Homework is that the Projects are more involved, and will take considerably more effort than a typical homework. They also count for more in your final grade. Groups will be given a number of weeks to complete each project. There will be NO written report required as a part of the Projects. Class Participation: There is no such thing as a stupid question. Dialogue is not only strongly encouraged, it is critical to your understanding of the material. Vocalizing your questions often helps you solidify what you do and do not understand. It also provides your instructors important feedback on the areas in which we need to spend more time. This can be a challenge in a large lecture. As in all things, we do the best we can under the circumstances. During lecture, we will encourage questions and we will solicit input. If we call on you, please relax, we are NOT trying to intimidate you or embarrass you in any way--far from it. We are trying to encourage active listening, and to keep you engaged in the course. This will greatly assist you in learning the material. If you do not know the answer, we will move on to another student, no worries. Compass Discussion Board: Illinois Compass will be used to post announcements, as well as to give you an opportunity to ask questions online about course content using the Discussion Board. This is also a great source of help on your homework. Our TAs are diligent in answering student questions on the Discussion Board, so please take advantage of this resource. You are responsible for checking for announcements on Compass before each class session. Excused Absences: On occasion, an emergency may arise which prevents you from taking an examination or otherwise performing in the course. To be considered for an excused absence, you must provide the proper documentation explaining your absence. This is done by providing verification through the Office of the Dean of Students. The Office of the Dean of Students is located in the Turner Student Services Building, 610 E. John Street, Champaign, 333-0050. Providing a McKinley Health Center Visit Record is NOT acceptable verification for an absence. Upon obtaining the letter or email from the Emergency Dean, this information must be provided to your Instructor and TA. At this point, the Instructor and TA will determine whether an accommodation is appropriate. Academic Integrity: Violations of academic integrity as given in the Code on Campus Affairs will be taken extremely seriously. Students found cheating in the course (or helping others to cheat) will be penalized according to the Code's guidelines. 4

Lecture Date Topic / Event Homework 1 Aug 22 Course Introduction. HW#1 2 Aug 24 Overview of Inference. Hypothesis testing Review. HW#2 3 Aug 29 Confidence Interval Review. HW#3 4 Aug 31 Single Population Variance. HW#4 5 Sep 7 Two Population Difference in Means, Independent Samples, HW#5 Population Variances Known. 6 Sep 12 Two Populations Difference in Means, Population Variances HW#6 Unknown (assumed equal, assumed unequal). 7 Sep 14 Two Population Means, Matched Pairs. HW#7 8 Sep 19 Two Population Difference in Proportions. HW#8 9 Sep 21 Two Population Ratio of Variances. HW#9 10 Sep 26 One-Way ANOVA. HW#10 11 Sep 28 Flex day. Review as possible. HW#11 Oct 2 Exam I Review Session. 12 Oct 3 Exam I. 7:00-9:00 pm. No Lecture today. 13 Oct 5 Simple Linear Regression. Estimating the Model. HW#13 Oct 7 Project 1 Introduced. 14 Oct 10 Simple Linear Regression. HW#14 15 Oct 12 Simple Linear Regression. HW#15 16 Oct 17 Simple Linear Regression. HW#16 17 Oct 19 Simple Linear Regression. HW#17 Oct 23 Project I Due. Get this done BEFORE break!! 18 Oct 24 Multiple Regression. HW#18 19 Oct 26 Multiple Regression. HW#19 Oct 28 Project 2 Introduced. 20 Oct 31 Multiple Regression. HW#20 21 Nov 2 Multiple Regression. HW#21 22 Nov 7 Multiple Regression. HW#22 23 Nov 9 Flex day. Review as possible. HW#23 Nov 13 Exam II Review Session. 24 Nov 14 Exam II. 7:00 9:00 pm. No Lecture today. 25 Nov 16 Time Series. HW#25 Nov 19 27 Thanksgiving Break!! 26 Nov 28 Time Series. HW#26 27 Nov 30 Time Series. HW#27 Dec 4 Project 2 Due. 28 Dec 5 Time Series. HW#28 29 Dec 7 Flex day. Last day of classes. HW#29 Dec 8 Reading Day. Dec 11 Final Exam Review Session. Dec 12 Final Exam for Lecture AL1. 1:30 4:30 pm. Dec 12 Final Exam for Lecture BL1. 7:00 10:00 pm. 5