Course Information for
OPRE504: Data Analysis and Decisions
Monday 6:00 PM at the Business Center Room 309

This is a Web-text companion site for the Web-enhanced textbooks:
Business Statistics    Forecasting    Excel    Course E-Labs   Statistical Resources    Financial Keywords and Phrases

Lecture Notes on Sakai: Sequential Sessions   (Use your ID, and Password: Technical Difficulties: 410- 837-5078)

The MENU for the Week of Monday January 28, 2013:

1. Any Questions?
2. A Short Version of Course Syllabus
3. What Math Do I Need for This Course? (Word.Doc)
4. Bring-in your scientific calculator and textbook in every class meeting.

You should check your UB e-mail often because the tutorial sessions' day, time and the place (at UB) are being sent out, in advance to each one of you using your UB e-mail address.

I am looking forward to working with you and hope that you will find the course both enjoyable and informative.
Professor Hossein Arsham                        


  1. Homework Assignments to Do Before Each Class Meeting and Sample Tests
  2. Welcome Message
  3. Academic Policy Statement
  4. Group, Individual and Elluminate Tutorial
  5. Course Description
  6. Course Structure, Its Ingredients & Learning Objects
  7. What Math Do I Need for This Course? (Word.Doc)
  8. Required Textbook, and Further Readings
  9. Course Requirements, Grading Criteria & System :
  10. The Course Objectives and Its Link to Business School Mission
  11. Your Fellow Students' and Advice
  12. Instructions for Homework Assignment
  13. Computer-assisted Learning: E-Labs and Computational Tools
  14. I Am Confused: How to know when to apply
    what formulas and calculations in word problems.
  15. The Main Web Sites I Recommend
  16. After This Course Is Over: Statistical Concepts You Need For Life (Word.Doc)

         Companion Site:

To search the site, try Edit | Find in page [Ctrl + f]. Enter a word or phrase in the dialogue box, e.g. "grade" or "exam" If the first appearance of the word/phrase is not what you are looking for, try Find Next.

Academic Policy Statement

The University of Baltimore and the UB/Towson MBA program comprises a community of students, faculty, administrators, and staff who share a commitment to learning. As the practice of academic honesty is essential to learning, the university has established a policy for academic honesty. Students enrolled in the UB/Towson MBA program can find the MBA policy online in the Student Handbook Student Handbook at Students enrolled in other graduate business programs can find the UB policy statement online in the Student Handbook at

All members of our community share responsibility for actively fostering academic honesty, actively discouraging academic dishonesty, and engaging in ongoing discussion of activities that may violate the spirit of honesty. Although the academic integrity policy places primary emphasis on fostering honesty, it also provides clear consequences for behavior that violates the policy, together with fair procedures for judging alleged cases of dishonesty.

Group, and Individual Tutorial

  1. Group and Individual Tutorial

    You may have to seek tutorial help to improve your algebraic computational and Statistical Problem Solving skills from the Achievement and Learning Center (ALC) located at (AC) Room AC 113 or by sending an email to: or by calling at (410) 837-5385. Professor Yoosef Kkhadem ( is the Coordinator of Stat Service at ALC. He is knowledgeable, and has both experience and patient. We are fortunate in having the following tutors being assigned for this course.


A Fact: My past students, who utilized this tutorial service throughout the semester, improved their course grade substantially.

Dear Student

Welcome to: Business Statistics

I am looking forward to working with you and hope that you will find the course both enjoyable and informative.

This is a course in statistics appreciation, i.e. to acquire a feel for the statistical way of thinking. An introductory course in statistics designed to provide you with the basic concepts and methods of statistical analysis for processes and products. The course is tailored to meet your needs in the MBA, and MS programs. Accordingly, all the application problems are borrowed from business and economics such as: Process control (production), Evaluation of the effects of a promotional campaign (marketing), Understanding how your workers approach their jobs (personnel), and Planning the process of ordering supplies (logistics). By the end of this course you'll be able to think statistically. The cardinal objective for this course is to increase the extent to which statistical thinking is embedded in management thinking for decision making under uncertainties. It is already an accepted fact that "Statistical thinking will one day be as necessary for efficient citizenship as the ability to read and write." So, let's be ahead of our time.

I do admire students with full-time jobs, families and a strong commitment to their education. I will gladly help you if something unexpected in your life happens -for example, an unexpected trip related to your job, an illness, etc.

This Web site is created for you. No one needs to be ashamed of what he or she does not know or how long it takes to master new information. Learning on the Web can be nonjudgmental and self-paced. Using advantages of this technology to expand learning opportunities is particularly crucial because we live in a time when learning is becoming a necessity not a luxury.

The letters in your course number: OPRE, stand for OPerations RE-search. OPRE is a science assisting you to make decisions (based on some numerical and measurable scales) by searching, and re-searching for a solution. I refer you to What Is OR/MS? for a deeper understanding of what OPRE is all about. Decision making process must be based on data neither on personal opinion nor on belief. Here is how people avoid making serious decisions. Do you use some of these strategies?

By the end of this course you'll be able to apply statistical concepts and methodologies when performing data analysis. You will learn how to execute these analyses using a variety of computers and computer-based tools. You will even learn how to do many of these analyses using that most personal of computer tools, the scientific/business calculator and statistical computation

To be competitive, business must design quality into products and processes. Further, they must facilitate a process of never-ending improvement at all stages of manufacturing. A strategy employing statistical methods, particularly statistically designed experiments, produces processes that provide high yield and products that seldom fail. Moreover, it facilitates development of robust products that are insensitive to changes in the environment and internal component variation. Carefully planned statistical studies remove hindrances to high quality and productivity at every stage of production, saving time and money. It is well recognized that quality must be engineered into products as early as possible in the design process. One must know how to use carefully planned, cost-effective experiments to improve, optimize and make robust products and processes.

The Devil is in the Deviations: Variation is an inevitability in life! Every process has variation. Every measurement. Every sample! Managers need to understand variation for two key reasons. First, so that they can lead others to apply statistical thinking in day to day activities and secondly, to apply the concept for the purpose of continuous improvement. This course will provide you with hands-on experience to promote the use of statistical thinking and techniques to apply them to make educated decisions whenever you encounter variation in business data. You will learn techniques to intelligently assess and manage the risks inherent in decision-making. Therefore, remember that:

Just like weather, if you cannot control something, you should learn how to measure and analyze, in order to predict it, effectively.

If you have taken statistics before, and have a feeling of inability to grasp concepts, it is largely due to your former non-statistician instructors teaching statistics. Their deficiencies lead students to develop phobias for the sweet science of statistics. In this respect, the following remark is made by Professor Herman Chernoff, in Statistical Science, Vol. 11, No. 4, 335-350, 1996:

"Since everybody in the world thinks he can teach statistics even though he does not know any, I shall put myself in the position of teaching biology even though I do not know any"

Plugging numbers in the formulas and crunching them has no value by themselves. You should continue to put effort into the concepts and concentrate on interpreting the results.

Even, when you solve a small size problem by hand, I would like you to use the available computer software and Web-based computation to do the dirty work for you, visit statistical computation.

You must be able to read off the logical secrete in any formulas not memorizing them. For example, in computing the variance, consider its formula. Instead of memorizing, you should start with some whys:

i. Why we square the deviations from the mean.
Because, if we add up all deviations we get always zero. So to get away from this problem, we square the deviations. Why not raising to the power of four (three will not work)? Since squaring does the trick why should we make life more complicated than it is. Notice also that squaring also magnifies the deviations, therefore it works to our advantage to measure the quality of the data.

ii. Why there is a summation notation in the formula.
To add up the squared deviation of each data point to compute the total sum of squared deviations.

iii. Why we divide the sum of squares by n-1.
The amount of deviation should reflects also how large is the sample size. Therefore, we must bring in the sample size (n) while computing the variance. That is, in general larger sample size have larger sum of square deviation from the mean. Okay. Why n-1 and not n. The reason it is when you divide by n-1 the sample's variance provide a much closer result to the population variance than when you divide by n, on average. You note that for large sample size n (say over 30) it really does not matter whether you divide by n or n-1. The results are almost the same and acceptable. The factor n-1 is so called the "degrees of freedom".

This was just an example for you to show as how to question the formulas rather than memorizing them. In fact when you try to understand the formulas you do not need to remember them, they are parts of your brain connectivity. Clear thinking is always more important than the ability to do a lot of arithmetic.

When you look at a statistical formula the formula should talk to you, as when a musician looks at a piece of musical-notes he/she hears the music. How to become a statistician who is also a musician?

The objectives for this course is to learn statistical thinking; to emphasize more data and concepts, less theory and fewer recipes; and finally to foster active learning using, e.g., the useful and interesting Web-sites.

For my teaching philosophy statements, you may like to visit the Web site On Learning & Teaching.

Feel free to contact me via phone, fax, or email. There is a lot of material to cover, so let's start now!

Course Description

Statistical data analysis for managerial decision making. Includes an examination of summary measures, probability, random variables and their distributions. Presents estimation and hypothesis testing, correlation and regression analysis and ANOVA, and their applications to business problems. The use of statistical data analysis software is an integral part of this course
Prerequisite: Graduate standing.

Course Learning Objectives

Preamble: The Merrick School of Business is strongly committed to the improvement of student learning through the assessment of our undergraduate and graduate degree programs. As part of this process, rubrics have been developed to provide students with qualitative guidance about what level of performance meets, exceeds or falls below expectations for specific skills and learning objectives. Students are encouraged to review the rubrics located on the Merrick School website Merrick School of Business Assessment to understand expectations for effective communication, analytical and problem solving skills, ethical reasoning, and other skills necessary in business.

Content Outline:

  1. Introduction to business statistics and data collection
  2. Descriptive statistics, summary measures, contingency tables and probability concepts.
  3. Properties of discrete probability distributions including Binomial distribution
  4. Properties of continuous probability distributions including Normal distribution
  5. Sampling distribution of the mean
  6. Confidence interval estimation of the mean and proportions.
  7. Hypothesis testing: Single population, two populations, z-test, t-test, one-tailed and two-tailed tests, chi-square tests, F-test for the variances, analysis of variance (ANOVA), and regression analysis.
  8. Spreadsheet modeling for business decision making.

When you have successfully completed this course, you will be able to:

  1. Obtain an appreciation for the breadth of statistical applications in business.
  2. Learn how to construct and interpret summarization procedures for quantitative and qualitative data.
  3. Learn how to use probability information in the decision making process. 4. Understand the importance of sampling and how results from samples can be used to make inferences about population parameters.
  4. Learn how to construct and interpret interval estimate of a population mean.
  5. Learn how to formulate and test hypotheses about a population mean.
  6. Understand how regression analysis can be used to develop an equation that estimates how two variables are related.
  7. Learn how the analysis of variance procedure can be used to determine if means of more than two populations are equal.
  8. Understand the role that statistical data analysis plays in managerial decision making process.
  9. Learn how to use statistical software for computations, visit e.g., statistical computation.

Course Structure, Its Ingredients & Learning Objects

Course Structure: Your course materials are divided into the following ordered topics:

An overview of statistical thinking; Descriptive statistics; The meaning of probability; Random variables and Probability Distributions; Goodness-of-fit tests; Runs test; Point estimate and confidence interval; Tests of hypotheses for one and two population; Contingency tables; Regression analysis and Analysis of variance.

Course Ingredients: The Course Ingredient Components Include:

  1. A set of Technical Keywords and Phrases,
  2. A Collection of Problem-Solving Methodologies, and
  3. Managerial Interpretations, Their Implications and Applications.

What Is Managerial Interpretations? The decision problem is stated by the decision-maker often in some non-technical terms. When you think over the problem, and finding out what module of the software to use, you will use the software to get the solution. The solution should also be presented to the decision-maker in the same style of language, which is understandable, by the decision-maker. Therefore, just do not give me the printout of the software. You must also provide managerial interpretation of the solution in some non-technical terms.

Learning Objects: There are varieties of sources in helping you to understand the foundation of statistical thinking for decision making. Each of the following items provides you with different perspective on our weekly topics.

  1. Textbook: Your textbook is the main source reading and the exercise before your each class meeting.
  2. Lecture Notes: Lecture notes are not your textbook substitute. They are designed to meet your needs, as I perceive while lecturing.
  3. Live Lectures & Handouts: The lectures are the bases of your interactions as a learning process, with your classmates and me.
  4. External Web Sites: The external weekly Web sites are directly relevant to the topics of the week. These reviews serve you as specialized "invited speakers" to our classroom.
  5. Computer Assisted Learning: My teaching style deprecates the 'plug the numbers into the software and let the magic box work it out' approach. The E-labs is an effective tool for experimentation in serving your needed "hand on experience" for understanding the managerial implication of the concepts for yourself. Visit e.g., statistical computation, and the professional software SPSS.

I am sure that your careful readings and effective use of the above learning objects, provide various perspectives, create a deeper understanding of the topic, together with the wholeness and manifoldness of this course.

Required Textbook, and Further Readings

Required Textbook for OPRE504: Business Statistics by Examples , 5th ed., by Terry Sincich, ISBN number: 0-02-410441-8, Prentice Hall, New Jersey, 1996.

A copy of the textbook is available in Langsdale Library at Reserved Circulation desk (under call no. B-40). You must have a valid student ID with you to use the book.

Your textbook is available at the UB Bookstore, (410) 837-5604.

The textbook chosen for this course is excellent. It is a modern, well written and clear account of the issues facing anyone doing business statistics. It is easy to read, has broad coverage and is eminently suitable for self study with many examples.

Further Readings: There are some Business Statistics, and general statistics textbooks that you may find helpful. They are located at the Langsdale Library.

Business School Mission

Merrick School of Business Mission Statement: Our mission is to prepare our diverse mix of students in collaboration with the business community to succeed in a dynamic global economy. The goal is to make excellence accessible. We achieve our mission by: Learning Style For This Course: An efficient and effective learning begins with asking yourself How to Study? I would like to insist that most parts of this course require a particular learning style. The effective and efficient learning style for this course is doing your homework assignments on a regular weekly basis and learning from your mistakes whenever I provide feedbacks.

I am sure you will be enthusiastic about the topics covered in this course throughout the semester and beyond. Enthusiasm is one of the most powerful engines of success. When you do study for this course, do it with all your might. Put your whole mind into it during the semester. Stamp your work with your own personality when submitting them to me. Be active, be energetic, be enthusiastic and honest, and you will accomplish the objectives of this course. Remember that, learning-to-learn was never achieved without enthusiasm.

Assessment Techniques: The following techniques will be used to assess a student’s performance

Link to Business School Mission:

  1. Integration of functional areas is accomplished by emphasizing applications related to statistics.
  2. Life long learning skills are developed by the processes involved in structuring problems, building statistical models for a variety of decision making situations.
  3. Information technology implications are addressed by requiring students to use popular statistical software in obtaining solutions to statistical models.
  4. Impact of globalization is introduced through statistical modeling which is universal.
  5. Ethical dimensions are included by addressing integrity issues in data collection and estimating the necessary parameters to build the statistical models.
  6. Collaboration is emphasized by encouraging students to work in groups to learn.
What Do You Mean By:

Course Requirements, Grading Criteria & System

Grading Criteria
Homework assignments 30%
Mid-term examination 30%
Final examination 40%


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Lecture Notes on Sakai: Sequential Sessions
Homework Assignments to Do Before Each Class Meeting and Sample Tests

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