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Dr. Ka-fu Wong

Dr. Ka-fu Wong. ECON1003 Analysis of Economic Data. An Introduction to ECON1003. GOALS. Survey Time Introduce briefly Teaching team A learning model and teaching philosophy Course features Textbook Course requirements Office hours What will be covered in this course

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Dr. Ka-fu Wong

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  1. Dr. Ka-fu Wong ECON1003 Analysis of Economic Data

  2. An Introduction to ECON1003 GOALS • Survey Time • Introduce briefly • Teaching team • A learning model and teaching philosophy • Course features • Textbook • Course requirements • Office hours • What will be covered in this course • First week assignment l

  3. Time for survey (10-15 minutes) The survey helps us understand you better. The results will also be used as illustrative examples in class. Personal information such as names and student ID will be kept strictly confidential. This is not a quiz, but please treat this survey as a quiz. Do not talk to your classmates.

  4. The teaching team Instructor: Dr. Ka-fu WONGhttp://kafuwong.econ.hku.hk Teaching Assistant: Miss Alice LEE

  5. A learning model What I hear, I forget. What I hear and see, I remember a little. What I hear, see and ask questions about or discuss, I begin to understand. When I hear, see, discuss and do, I acquire as knowledge and skill. What I teach to another, I master.

  6. A learning model To hear and see: Please attend the lectures and tutorials. To ask questions about or discuss: Please actively participate in lectures and tutorials. Discuss with your classmate, TA and instructor. To do: Projects / Presentations / Project reports / Labs / Homework assignments. To teach to another: Teach your parents and friends who do not know much about Statistics.

  7. Teaching philosophy Learning should be enjoyable. That is why we have labs and projects. What we learn can be use to understand and analyze real-world issues. If we enjoy what we are doing and learning, and can apply what we learn to real-world issues, we will learn faster and do much better. Given that students are willing to put in efforts, Learning should not be difficult. The instructor and the TA are here to help you.

  8. Course features that facilitate learning 1. Class website: To remind students about deadlines and to link students to relevant materials. 2. Lecture in Powerpoint format: Allow us to use our lecture time more effectively and cover slightly more materials and examples. 3. Downloadable Powerpoint notes: Save notes-jotting time. Help students focus more on the explanations in lecture.

  9. Course features that facilitate learning 4. Labs in class and tutorials : Aim to make learning more enjoyable and memorable. 5. Projects / presentations / project reports: Help students reinforce their learning experience and gain other valuable skills. 6. Quizzes in class: Help students reinforce their learning experience. 7. Electronic tutorials: econ1003-help@kafuwong.econ.hku.hk Allow us to help students around the clock.

  10. Textbook • Lectures will be based onStatistical Techniques in Business and Economics, written by Douglas A. Lind, William G. Marchal and Robert D. Mason: Irwin- McGraw-Hill Book Company, 11th edition, 2001. • The book comes with a CD-ROM containing powerpoint lecture notes, Excel add-on, self-testing quiz, and a software of Visual Statistics. • For projects and lab assignments, you will need to use the Excel add-on. • For review, you are advised to use the self-testing quiz. • For visual illustration of statistical concepts, you will find the software Visual Statistics useful. • In short, you will need a copy of the textbook.

  11. Course Requirements 0% Attendance 0% Review exercises 30% Projects Quizzes 40% 30% Final examination

  12. 0% Attendance You are required to attend all lectures and tutorials. Generally, students who skip lectures and tutorials do poorly in the course. We want to make sure that students get a solid training in Statistics. Attendance will be taken at lectures and tutorials. When you miss more than two lectures and tutorials, our TA will call to check why you have been missing. This mechanism aims to help, not to punish students.

  13. 0% Review exercises We will hand out review exercises weekly: Please do not hand them in. The TA will not grade them. However, our TA will provide solutions. Advice:Try to work on the problems by yourself. Whenever you have trouble getting the correct answers, discuss with your classmates, consult your TA and your instructor, in that order. At least 80% of the quizzes questions will be similar to the review exercises.

  14. 30% Projects The project is intended to expose you to the use of statistics in real problems of your choice. The presentations and project reports also help improve and test our understanding of the subject.. It allows us to sharpen our skills in statistical analysis, oral presentations, written presentations, and teamwork.

  15. 30% Projects Team work: • Students will be randomly assigned into groups of two to work on two projects. The team as a whole is responsible for the project analysis and implementation. • Individual team members take turns writing the project reports and giving the presentations. The person who gives the oral report cannot be the person who authors the written report. • Thus each project receives three grades, an analysis grade that is given to every team member, a writing grade that is given to the report's author, and a presentation grade that is given to the presenter.

  16. 30% Projects Five-minute Presentations: • These presentations will be Powerpoint based. • Please hand in a softcopy of your Powerpoint file, via email. • Presentation will be video-recorded so that presenters has a chance to see their own performance. • Your performance will be graded by your peers and TA. • The instructor will randomly check the grading and videos to make sure that the grading has been fair. • In case of grade disputes, we can sit down to view the tape together.

  17. 30% Projects Three to five page Written reports: • No more than five pages. • Please hand in a softcopy of your report, via email. • All papers should be easy to read, i.e. typed (word processed) in a standard 12pt font with reasonable margins and 1.5 to double spaced. • When writing up the project, in addition to your discussion of results, you should include a clear description of the experiment, including how the data was collected, and a summary of steps of your analysis. The collected data and questionnaire (if any) should be included in a data appendix. • The TA (and possibly your peers) will be grading it. • The instructor will randomly check the grading to make sure that the grading has been fair.

  18. 30% Projects Project topics: • Two types of projects. • Type A will involve simple plots of data, summary statistics, and analysis – in the first half of the semester. • Type B will involve estimating the relationship among variables and testing their significance – in the second half of the semester. • The team is free to choose among a pool of projects (supplied by the instructor, to be announced later). You are encouraged to choose topics outside this pool. However, if you have different project topics, you must get approval from your instructor.

  19. 30% Projects Examples of Type A Project topics: • Visit at least 30 foreign exchange shops (including banks). Record the buy and sell exchange rate of RMB to HK dollars. Based on simple plots and summary statistics, are the buy and sell spread (difference between buy and sell price) different between bank and non-bank foreign exchange shops. • Visit the library and ask the librarian (reference counter) to help locate the electronic data series of HK stock prices. Collect the prices of two stocks, one over 10 dollars and one below 10 dollars. Compute their mean and standard deviations of daily percentage change in prices. Based on the plots and these summary statistics, which stock is more risky? Which stock is more profitable to hold? • Randomly ask 50 HKU students the average amount of time per week they spent on studying in the semester before the survey. Summarize the data in a plot. Compute the means and standard deviations. Ask your friends from different local universities the same question. Are they within the two standard deviations from the mean at HKU?

  20. 30% Projects Examples of Type A Project topics: • Find the all the Mark-Six Jackpot in year 2001 and 2002 (available from on-line). Summarize the data with a plot. Compute the mean of the Jackpot for 2001 and 2002. Are the mean of 2002 within the two standard deviations of 2001? And vice versa? • Visit at least 30 shops selling vegetables from two different districts. Include at least 10 shops from each district. Record the price of selected vegetable. Summarize the data with plots. Compute their means and standard deviations. Is the mean of the first district within two standard deviations of the second district? And vice versa? • Follow at least 30 policemen. Record the time taken before the policemen stop and question you. Summarize the data with a plot. Compute the mean and standard deviation. Follow a policewoman. Record the time taken before the policewoman stops and questions you. Is policewoman’s time within the two standard deviations of the policemen’s?

  21. 30% Projects Examples of Type B Project topics: • Visit at least 30 shops selling vegetables from two different districts. Include at least 10 shops from each district. Buy one pound of vegetable from each shop. Record the selling price, the seller’s sex and your guess of his /her age. Weight the vegetables at home. Compute the deviation of the weights from one pound. Is there a relationship between the deviations and the selling price, the seller’s sex and age? • Visit at least 30 bakery shops. Record the price of “pineapple” and “chicken tail”. Also record whether they have a policy of price reduction after certain hour. Is there a relationship between the “normal price” and the price reduction policy and whether the bakery is a chain store? (For interest: ask the shopkeepers what they do with the unsold bread.)

  22. 30% Projects Confused? Worried? • You may be confused at this stage but no need to worry. • We will have two lectures demonstrating what we expect, in great details. One lecture for type A projects, one for type B. • We will discuss the guidelines of grading the projects. Being a grader yourself, you will clearly know what everyone expect. • We will help develop interesting topics with you.

  23. 40% Quizzes The coverage of quizzes is cumulative, i.e., they cover all course materials up to the quiz date but generally will focus on the last review exercise set. The quizzes will be held in biweekly on Fridays. 14/2, 28/2, 14/3, 4/4, 25/4, 9/5 The tests aim at testing how well you have learned so far. If you do badly in the quizzes, you may be asked to talk to our TA or the instructor. Togetherwe try to figure out the things we can do to improve your performance. The conversation is to discover problem before it’s too late.

  24. 40% Final Examination Final examination is similar to quizzes. The coverage of final examination is cumulative, i.e., they cover all course materials up to the quiz date. Generally, if you have done your work for all the quizzes, you should do well in the final examination. Review session will be given before the final examination.

  25. Office hours Instructor: Dr. Ka-fu WONG Monday, Wednesday 2:00-3:00p.m., or by appointment, or by email. Open door policy Teaching Assistant: Miss Alice LEE To be announced. May be reached by appointment, or by email.

  26. No guarantee of passing The instructor and our TA are committed to help you learn and do well in this course. The chance of failing this course should be small. The rest depends on you.

  27. Coverage • We will try to cover up to simple linear regressions. • If time permits, we will cover some non-parametric statistics.

  28. First week assignment • Buy a copy of the Textand Read Chapter 1. • Find and search through the class website. • Do some causal reading of • Cohn, Victor (1989): News & Numbers: A guide to reporting statistical claims and controversies in health and other fields, Iowa State University Press. • Spirer, Herbert F., Louise Spirer, and A.J. Jaffe (1998): Misused Statistics, Marcel Dekker, Inc. • Gallery of Data Visualization: The Best and Worst of Statistical Graphics http://www.math.yorku.ca/SCS/Gallery/

  29. An Introduction to ECON1003 - END -

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