BUS 304 STAT
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|BUS 304EX - BUSINESS STATISTICS |
|Summer 2009 |
|Meeting Time(s) |
|Lecture: MWF 12:00 – 15:25 MARK 309 |
|Lab: MWF 15:35 – 16:35 MARK 309 |
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|(CRN 30135) |
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|First Half (July 8 – July 22, 2009) |
|Instructor: Chetan (Chet) Kumar, Ph.D. |
|Office: Markstein Hall 444 |
| College of Business Administration |
| California State University San Marcos |
|Phone: (760) 750-4207 |
|E-mail: ck_courses@csusm.edu |
|Office hours: MWF 11:00-11:50 am and by appointment |
|Second Half (July 24 – Aug 11, 2009) |
|Instructor: Mohammad Oskoorouchi, Ph.D. |
|Office: Markstein Hall 431 |
| College of Business Administration |
| California State University San Marcos |
|Phone: (760) 750-4219 |
|E-mail: moskooro@csusm.edu |
|Office hours: MWF 11:00-11:50 am and by appointment |
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|Course Website and Email |
|Course materials are available for download from WebCT / the instructors’ website. Students shall use the email addresses listed above to |
|contact instructors. The email subject fields should start with “BUS 304” to indicate a course-related email. |
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|Course Overview |
|Business Statistics is a course on distilling useful business information by collecting, organizing, and processing data. In this course, |
|you will learn basic descriptive statistical methods, sampling methodology, how to draw inferences from samples to larger populations and |
|how to make predictions based upon historical relationships between variables. Especially, students are expected to learn how to use |
|statistical software such as Microsoft Excel to solve real world problems. |
|My experience has shown that statistics is best taught through a series of clear and carefully worked examples. Therefore, theoretical |
|background in descriptive and inferential statistical methods will be provided, however a great deal of time will be spent on teaching you |
|how to apply the theory to the real world. Statistics is not about memorizing formulas. Instead it is about recognizing the appropriate |
|statistical test to perform in a given situation. This requires practice on the part of the student. As we cover the topics, if you do not |
|have a clear understanding of one topic it is wise to seek help immediately. The next topic will build upon the previous one. Please allow |
|us to assist you as soon as you find that you have questions. |
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|Course description and objectives |
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|In order to stand out in today's competitive job market, new business school graduates need to bring to an organization special skills and |
|abilities that give them the potential to hit the ground running and contribute immediately. One area where a student can have an immediate |
|competitive advantage over both new graduates and existing employees is in the application of statistical analysis skills to business |
|problems. Our intent in this course is to build your statistical back ground and to give you the statistical skills necessary to meet the |
|needs of business and the real-world decision-making problems. In this course, we discuss real-world applications as a motivation for |
|learning business statistics. We will focus on decision making and business applications and provide you with an understanding of the roll |
|of business statistics in decision making. |
|To enhance the students' appreciation for business statistics, we emphasize computer-based analysis, rather than manual computation. To this|
|end, Microsoft Excel is used extensively throughout the course. |
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|Learning Outcomes |
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|Following this course the students should |
|Know the data collection methods and understand how to categorize data. |
|Construct and interpret a scatter plot, joint frequency table, pareto chart, frequency histogram and various types of bar charts. |
|Compute and understand the mean, median, mode and variance for a set of data. |
|Compute the coefficient of variation and z scores and understand how they are applied in decision-making situations. |
|Be able to apply the common rules of probability and to identify the types of processes that are presented by discrete probability |
|distributions. |
|Understand the main approaches to assessing probabilities and determine probabilities associated with binomial. |
|Be able to discuss the important properties of the normal probability distribution and calculate probabilities using the normal distribution|
|table and be able to apply the normal distribution in appropriate business situations. |
|Understand the concept of sampling error and the importance of the Central Limit Theorem. |
|Be able to determine the mean and standard deviation of the sampling distribution of the population mean. |
|Construct and interpret a confidence interval estimate for a single population mean using both the standard normal and t distribution. |
|Determine the required sample size for estimating a single population mean. |
|Formulate null and alternative hypotheses for applications involving a single population mean. |
|Know how to use the test statistic, critical value, and p -value approach to test the null hypothesis. |
|Calculate and interpret the simple correlation between two variables. |
|Understand the basic assumptions behind single and multiple regression models. |
|Recognize some potential problems if regression analysis is used incorrectly. |
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|Textbook |
|A Course in Business Statistics (4th edition) by David F. Groebner, Patrick W. Shannon, Phillip C. Fry and Kent D. Smith, Prentice Hall, |
|2006 (available in the Bookstore) |
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|Other course materials |
|You will need a calculator for this course to be used with homework and in-class quizzes and exercises. You may also bring it to the tests. |
|A basic calculator that adds, subtracts, multiplies, divides and finds square root will be sufficient. You may not use a cell phone to do |
|calculations during the exams. You should also have a recent version of Microsoft Excel (with data analysis add-in installed) on your |
|computer to finish your homework and written project. You may also need a USB memory stick to save in-class exercise files. |
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|Grading Procedure |
|You final grade will be computed on a basis of 100 points. The grading formula can be found below. How the final grade translates to the |
|letter grades is also given. I DO NOT use a curve. |
|1. Individual Homework (IH; 25%): There will be multiple individual homework assignments during the whole semester (there will be typically |
|be 1 homework assignment each for every textbook chapter discussed - the total number of assignments will be announced in class). Each of |
|them will be equally weighted. Students should use Microsoft Word to finish the homework and print out a hard copy to be submitted to the |
|instructor at the beginning of the class session when they are due. Electronic submission is not accepted. |
|Most of the assignments are associated with the lab experiments. Attendance is important to finish the homework. An average student should |
|be able to finish the homework during the lab session. Assignments have to be submitted in class on time unless otherwise stated. 5 minutes |
|late is same as one day late. Late submission will be deducted 20% from the original score each day. |
| 2. Mini-Projects 1 and 2 (MP1 and MP2; 12.5%): The objective of the Group Project is to permit students to solve statistical problems and |
|tailor course concepts to their own interests, whether they are in MIS, HTM, GSCM, GBM, M&M, Accounting, or Finance related areas. The |
|project designed to acquaint students with one specific area of application of statistics. The project groups will choose (or be given) a |
|topic of interest, conduct a survey to gather data (or collate secondary data) for the topic, and statistically analyze the survey (or |
|secondary data) to arrive at conclusions and recommendations. Further details of the project will be discussed in class. All students have |
|to submit a hard copy of the assignment as a group on the due dates. Any project deliverables turned in after the deadline (5 minutes late |
|is the same thing as 24 hours late) will lose 20% for every 24-hour period that the assignment is late. |
| All CSU students must demonstrate competency in writing skills as a requirement for graduation. This requirement mandates that every course|
|at the university must have a writing component of at least 2500 words (approximately 10 pages). To achieve this requirement in this course,|
|each assignment team (grouped as 3-5 students) is required to submit a 10 page report for each mini-project. All the students are required |
|to contribute equally in assignments. |
|Sample Format for Mini-Project Outline |
|(The outline should address the following questions) |
| - The topic you chose |
| - The reason why you chose this topic |
| - Your plan for this project (survey details, respondent profile, tentative survey sample size, any available secondary data to|
|prove or disprove, methodology of analysis, |
|limitations, etc.) |
|Sample Format for Mini-Project |
|1. INTRODUCTION |
|2. OBJECTIVE(S) / AIM(S) |
|3. RESEARCH METHODOLOGY |
|5. 4. SURVEY AND ANALYSIS (PRIMARY SOURCES) |
|5. RESULTS / CONCLUSIONS |
|6. RECOMMENDATIONS |
|7. SCOPE FOR FURTHER WORK |
|8. BIBLIOGRAPHY/LIST OF REFERENCES |
|9. APPENDIX |
| 3. Two Exams (Ex1 and Ex2; 25% each): There will be two in-class exams scheduled at the middle of the semester and the end of the semester,|
|respectively. Refer updated course schedule for all dates. |
|Final Grade Formula: |
|Final Grades= IH*25%+MP1*12.5%+MP2*12.5%+Ex1*25%+Ex2*25% |
|Final Letter Grade: |
|94 ................
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