Contents:

• Lecture Notes

• Lab material

• Assignment

• Grade Statistics

• Grade Calculation

Course Information:

·         Title: Statistics

·         Course number: BA 615

·         Semester: Fall 2007

·         Prerequisites: Admission to the MBA Program

·         Instructor: Mohammad R. Oskoorouchi

·         Office: MARK 431

·         Telephone :  750-4219

·         E-mail: moskooro@csusm.edu

·         Homepage: http://public.csusm.edu/oskoorouchi

·         Course page: http://courses.csusm.edu/ba615mo

·         Password protected course page: http://courses.csusm.edu/ba615mo/download

·         Class hours: S: 1230 – 1515

·         Office hours: S: 1130 – 1230

Textbook:

Required Text:

·         D. F. Groebner, P. W. Shannon, P. C. Fry, and K. D. Smith, "Business Statistics: A Decision Making Approach", Prentice Hall, 7/E 2008.

Other References:

·         D. F. Groebner, P. W. Shannon, P. C. Fry, and K. D. Smith, "A Course in Business Statistics ". Prentice Hall, 4/E 2006.

·         M. K. Pelosi and T. M. Sandifer, " Doing Statistics for Business with Excel", John Wiley & Sons, Inc. second edition 2002.

·         A. H. Kvanli, R. J. Pavur and K. B. Keeling, "Introduction to Business Statistics", South-Western, Edition 6, 2003.

Course description and objectives:

In order to stand out in today's competitive job market, MBA 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 statistics, we emphasize computer-based analysis, rather than manual computation.

Learning Outcomes:

Following this course the students should

·         Know the data collection methods and understand how to categorize data.

·         Describe data using charts, graphs and numerical measures.

·         Understand the main approaches to assessing probabilities and determine probabilities associated with Binomial and Poisson distributions.

·         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, and be able to determine the mean and standard deviation of the sampling distribution of the population mean and proportion.

·         Construct and interpret a confidence interval estimate for population mean and proportion using both the standard normal and t distribution, and determine the required sample size for estimating population mean and proportion.

·         Formulate null and alternative hypotheses for applications involving population mean, proportion, or variance, understand type I and type II errors, and know how to use the test statistic, critical value, and p -value approach to test the null hypothesis.

·         Perform a single factor hypothesis test using analysis of variance manually and with the aid of Excel.

·         Understand correlation between two variables and develop single and multiple regression models and recognize some potential problems if regression analysis is used incorrectly.

Evaluation:

80% of your course grade will be based on 4 exams and 4 homework assignments, and 20% of your grade will be based on a one-unit independent study.

Homework assignments including cases: (20%)

Exam 1: Chapters 1 – 6, (15%)

Exam 2: Chapters 7 – 9, (15%)

Exam 3: Chapters 10 – 12, (15%)

Exam 4: Chapters 13 – 15, (15%)

Independent study: (20%)

Grading Standards:

Homework assignments: Homework assignments are designed to help you learn the mechanics of the methods discussed in class and to give you an opportunity to apply these concepts in a straightforward manner. In addition to their value as learning exercises, doing a careful and thorough job on the homework assignments is the best preparation for the midterm and final examinations of the course.

Homework Rules:

·         There will be 4 assignments throughout the semester which will be posted on this course page.

·         You must submit a hard copy at the beginning of the class, when it is due.

·         The first page of your report should be a cover page: your name, homework number, course number, date, etc.

·         Each problem must be answered in a separate page and in the same order as given.

·         All pages must be stapled together.

Independent study: This part of the course is intended to be the bridge between academic learning and practical application--students will actively apply what they learn in statistics to real-world applications, and complete a solid deliverable. 

This unique feature of the program does not involve class time, but is rather an outside-the-classroom activity. The purpose of these projects is to develop practical applications of your learning for your current work environment, and to build a portfolio of your work that can be used to demonstrate your capabilities to future employers.

This project is a team work activity. The size of the teams is determined based on the enrollment. All projects should be developed around one theme. The theme of this year is “technology”. Students should select a certain company, industry or service sector and focus their research on how the combination of statistics and technology would help improving and advancing the operation. Further details will be discussed in class.  Each team must submit a one-page proposal on October 13.

There will be a public website on which the abstracts of completed papers/projects will be made available to potential students, current students, and employers.  In addition, a professor may elect to sponsor a public seminar with an outside speaker or speakers on the theme selected for his or her class.  Thus you should be able to be involved in several theme-related projects/papers in one or more areas. I welcome your ideas/suggestions for a seminar related to statistics and the theme of our class.

Academic Honesty Statement: Students will be expected to adhere to standards of academic honesty and integrity, as outlined in the Student Academic Honesty Policy. All written work and oral presentation assignments must be original work. All ideas/material that are borrowed from other sources must have appropriate references to the original sources. Any quoted material should give credit to the source and be punctuated with quotation marks.

ADA statement: Students with disabilities who require reasonable accommodations must be approved for services by providing appropriate and recent documentations to the Office of Disabled Student Services (DSS). This office is located in Craven Hall 5205, and can be contacted by phone at (760) 750-4905, or TTY (760) 750-4909. Students authorized by DSS to receive reasonable accommodations should meet with me during my office hours in order to ensure confidentiality.

NOTE: It is the student’s responsibility to understand and follow the University Policies as stated in the catalog. 

Tentative Course Schedule: