MENU
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.
Tutorial Help for This Course
You may have to seek tutorial help to improve your algebraic computational and Statistical Problem Solving skills from the Academic Resource Center (ARC) at Room AC116 or by calling at (410) 837-5385. Professor Yoosef Kkhadem (ykhadem@ubalt.edu) is the Coordinator of Stat Service at ARC. He is knowledgeable, and has both experienced and patient. We are fortunate to have the following tutors being assigned for this course.
Your tutor's contact information:
- Supralerk Sorasaenee (paulultimate@yahoo.com)
- Yoosef Kkhadem (ykhadem@ubalt.edu)
A Fact: My past students, who utilized this tutorial service throughout the semester, improved their course grade substantially.
Dear Student
Welcome to: Business StatisticsI 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 504, 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 neither on belief. 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
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:
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.
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 summary measures, probability, random variables, and their distributions. Estimation and hypothesis testing, correlation and regression analysis, ANOVA, and their application to business problems are presented. The use of statistical data analysis computer packages is an integral part of this course.
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:
- A set of Technical Keywords and Phrases,
- A Collection of Problem-Solving Methodologies, and
- 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.
- Textbook: Your textbook is the main source reading and the exercise before your each class meeting.
- Lecture Notes: Lecture notes are not your textbook substitute. They are designed to meet your needs, as I perceive while lecturing.
- Live Lectures & Handouts: The lectures are the bases of your interactions as a learning process, with your classmates and me.
- 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.
- 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.
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 for OPRE330: Statistics for Managers Using Microsoft Excel and Student CD Package , 5th ed., by D. Levine, D. Stephan, T. Krehbiel, and M. Berenson, ISBN number: 13: 978-0136149903, Prentice Hall, New Jersey, 2007.
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 textbooks are available in Langsdale Library at Reserved Circulation desk (under call no. B30). You must have a valid student ID with you to use the book.
Your textbooks are 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.
Recommended Readings: The Location is referring to the Langsdale Library stacks:
Business Statistics Books:
- Basic statistics for business and economics
By Douglas A. Lind, William G. Marchal, Samuel A. Wathen
McGraw-Hill, 2003
Location: HA29 .L75 2003
- Statistics for business and economics
By David R. Anderson, Dennis J. Sweeney, Thomas A. Williams
South-Western College Pub., 2002
Location: HF1017 .A6 2002
- Learning business statistics with Microsoft Excel
By John L. Neufeld
Prentice Hall, 2001
Location: HF1017 .N474 2001
- Statistics, data analysis, and decision modeling
By James R. Evans, David L. Olson
Prentice Hall, 2000
Location: HD30.215 .E93 2000
- Statistics and data analysis : From elementary to intermediate
By Ajit C. Tamhane, Dorothy D. Dunlop
Prentice Hall , 2000
Location: QA276 .T25 2000
Statistics Books (General):
- Statistics
By Robert S. Witte, John S. Witte
J. Wiley, 2004
Location: QA276.12 .W57 2004
- Essentials of statistics
by Barry H. Cohen, R. Brooke Lea
Wiley, 2004
Location: HA29 .C655 2004
- Statistics: A short course and student manual
By Bryan Raudenbush
University Press of America, 2004
Location: HA29 .R26 2004
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:
The Course Objectives and Its Link to Business School Mission 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.
- Creating and delivering a leading edge curriculum with practical learning experiences in innovative and flexible ways;
- Maintaining intellectual currency through scholarship on business theory, practice and education; and
- Providing expertise to the private and public sectors as well as the academic community.
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.
Course Objectives: What Do I Learn?
When you have successfully completed this course, you will be able to:
- Obtain an appreciation for the breadth of statistical applications in business decision making and enhancing understanding other statistical-based courses.
- Learn how to construct and interpret data summarization procedures for quantitative and qualitative data.
- Learn how to use probability information in the decision making under risk.
- Understand the importance of random sampling and how the statistics obtained from samples can be used to make statistical inference about population parameters.
- Learn how to construct and interpret confidence interval estimate of a population mean and statistical equivalency of two populations.
- Learn how to formulate and test hypotheses about a population mean and understanding the duality between tests of hypotheses and confidence intervals.
- Understand how regression analysis can be used to develop a function that that estimates how two variables are related and its applications such as predictions.
- Learn how to conduct an analysis of variance (ANOVA) procedure to determine if two or more than two populations are statistically equal. Application of ANOVA in assessing the overall goodness-of-fit in regression analysis.
- To understand the role that statistical data analysis plays in managerial decision making under uncertainty.
- Learn how to use computer for computations and managerial interpretation of the outputs.
Assessment Techniques: The following techniques will be used to assess a student’s performance
- Homework Assignments
- Computer Assignments
- Mid-term Examination
- Final Examination
Link to Business School Mission:
- Integration of functional areas is accomplished by emphasizing applications related to statistics.
- Life long learning skills are developed by the processes involved in structuring problems, building statistical models for a variety of decision making situations.
- Information technology implications are addressed by requiring students to use popular statistical software in obtaining solutions to statistical models.
- Impact of globalization is introduced through statistical modeling which is universal.
- Ethical dimensions are included by addressing integrity issues in data collection and estimating the necessary parameters to build the statistical models.
- Collaboration is emphasized by encouraging students to work in groups to learn.
Course Requirements, Grading Criteria & System
Grading Criteria Homework assignments 40% Mid-term examination 30% Final examination 30%
Notices:
Your examinations have similar format as the Sample Exams, consisting of two parts:
- The application part contains a few problems similar to your homework. The weekly homework problems are from a specific section of the book therefore, it is easy to know what formula or procedure to use. However, in real life, as in the test you have to know what procedure is the right one to use.
- The conceptual part contains a few questions that come from your weekly readings assignments. These questions test how careful and reflective your readings have been by coming up with correct, exclusive, and inclusive answers.
- Homework: Assignments (100 points) will be collected randomly and graded. Your homework assignment consists of two parts:
Homework Due Date: Meeting deadlines and even sending me material before deadlines are very important, since you will be engaging in group learning activities where time is crucial. So you should make every effort to complete your work on time. Therefore, late homework submissions carry no credit at all.
- Reading the lecture notes, Readings and problem solving from your textbook (90 points).
- Compute Implementation using the E-labs, Excel, or SPSS, etc., since without a statistical computer package one cannot perform any realistic statistical data analysis (10 points).
You do not have to type your homework assignments; you may save some times in spending more on learning than typing. In this case please, please hand-in your eligible homework on time.
- Computer assignments: The computer-assisted learning assignments provide you a "hands-on" experience which will enhance your understanding of the concepts and techniques covered in this course.
As you used to do experiments in physics labs to learn physics, computer-assisted learning enables you to use any online interactive tools available on the Internet to perform experiments. The purpose is the same, i.e., to understand statistical concepts using JavaScript e-labs which, are entertaining and educating.
The appearance of computer software, JavaScript Applets, Statistical Demonstrations Applets, and Online Computation are the most important events in the process of teaching and learning concepts in model-based statistical decision making courses. These tools allow you to construct numerical examples to understand the concepts, and to find their significance for yourself.
Unfortunately, most classroom courses are not learning environment. The way the instructors attempt to help their students acquire skills and knowledge has absolutely nothing to do with the way students actually learn. Many instructors rely on lectures and tests, and memorization. All too often, they rely on "telling." No one remembers much that's taught by telling, and what's told doesn't translate into usable skills. Certainly, we learn by doing, failing, and practicing until we do it right. The computer assisted learning serves this purpose.
What and How to Hand-in My Computer Assignment? For the computer assignment I do recommend in checking your hand computation homework, and checking some of the numerical examples from your textbook. As part of your homework assignment you don not have to hand in the printout of the computer assisted learning, however, you must include within your handing homework a paragraph entitled "Computer Implementation" describing your (positive or negative) experience.
- Web Sites Review: Think about these questions as you review the assigned Websites:
- What does the Website provide?
- How do you benefit from online material?
- What are some of the distinguishing characteristics of the Website?
- How is learning facilitated using the Web as an educational tool?
In general there are at least five criteria for an intersting and useful Web site:
- Accuracy: Accuracy covers who is the author and can you contact him or her, the reviewer should ask why this document was written. What is the purpose?
- Authority: The reviewer should verify who published the site as well as was the publisher separate from the webmaster.
- Objectivity: The evaluator should determine what are the goals and objectives of the site. Is the information marketing related or is it for informational purposes. This material is reviewed within the objectivity criteria.
- Currency and Coverage: Currency should be determined by the date of the last review. Has the material been updated recently or is the material old.
- Packaging: Are the images and text pleasing to the eye? Is the contact organized in a logical sequence? Is all of the information cited appropriately?
Your external Web sites reviews allow you to understand the same concepts covered in your textbook and the lecture notes from different perspectives. To maximize the outcome of your learning-to-learn process efforts, visit the Web site The Impact of the Internet on Learning & Teaching.
Grading System 90-100 80-89 70-79 65-69 60-64 O.W. A B + B C + C F
Instructions for Homework Assignment
Many students find it helpful to learn statistics. I strongly suggest to view them a few times.
Since you are allowed ONLY to use your own Pre-Prepared Summary-Sheets for Exam. Read carefully the Summary-Sheets for the Exam on this page, while preparing one for the test.
You will also need a scientific calculator, and a blue book (available at the Bookstore).
When taking your exam, present your work in detail. This will allow me to give partial credit.
The exams are not in any particular format so expect both standard numerical problem solving and conceptual type questions. The exams will test your understanding of the material covered in this course. The main purpose of taking the examinations is to find out how reflective your mind is in answering a set of questions correctly. The objective is to maximize the number of correct solutions, subject to a limited time constraint (a 2-hours session). Samples of past exams are available on this Web site for inspection.
To prepare yourself for exams, review all topics, homework assignment and lecture notes.
To master what you are learning I recommend in prepare a summary sheet of the main topics you have learned in any given week.
The process of making your own summary-sheet is the idea of contemplating the topics you have learned. By definition of esthetics, the longer you contemplate on what you have learned the more beautiful the subject mater becomes. Beauty and contemplation is distinguished from other mental manifestations; contemplation is the result of the perfect apprehension of relations and topics.
Use the following Guide to Prepare Your Summary Sheets:
The above process helps to crystallize your mind to be reflective and responsive to questions posed about topics you've learned in this course and reinforces the topics in your mind.
I Am Confused: How to know when to apply what formulas and calculations in word problems. You or some of your classmates may have following honest concern and difficulty: "..The muddiest points still remaining are how to know when to apply what formulas and calculations in word problems.."
You are not alone on this. You have an honest concern and a difficulty to overcome. Since you are learning little-by-little every week, it is very natural desire to see the wholeness and manifoldness of topics. Therefore, it is natural to feel confused because of accumulation of different topics. However we must cross over to the other side of confusion where by thinking clearly and distinctively you will feel comfortable. As an Italian proverb says "He who knows nothing doubts nothing."As you know by now, the ingredient components of what you should master are:
- A set of Technical Keywords and Phrases. There are confusions on statistical terminologies, mostly because of historical miss-naming them. For example, ki-square (ki-sqre, Chi-square), is not the square of anything, its name implies Chi-square (read, ki-square). ki does not exist in statistics.
- A Collection of Problem-Solving Methodologies. There are different formula, and conditions under which each statistical procedure is applicable. For example, there are many Z's defined at z value, z test, z transformation, and z score. One must be careful to know which one to use for a given application. For test of hypotheses and estimations with confidence, I suggest in make a short list of them for yourself, similar to the one at Selection of a Statistical Table
- The above two items are for some useful ends for Business statistical-based courses, as well as statistical managerial interpretations of the word problems, for decision making under uncertainty. You may ask: 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.
E-Labs and Computational Tools
The Value of Performing Experiment: If the learning environment is focused on background information, knowledge of terms and new concepts, the learner is likely to learn that basic information successfully. However, this basic knowledge may not be sufficient to enable the learner to carry out successfully the on-the-job tasks that require more than basic knowledge. Thus, the probalility of making real errors in the business environment is high. On the other hand, if the learning environment allows the learner to experience and learn from failures within a variety of situations similar to what they would experience in the "real world" of their job, the probalility of having similar failures in their business environment is low. This is the realm of simulations-a safe place to fail.
The appearance of statistical software is one of the most important events in the process of decision making under uncertainty. Statistical software systems are used to construct examples, to understand the existing concepts, and to find new statistical properties. On the other hand, new developments in the process of decision making under uncertainty often motivate developments of new approaches and revision of the existing software systems. Statistical software systems rely on a cooperation of statisticians, and software developers.
Beside the statistical software, Java Applets, Online statistical computation, and the use of a scientific calculator is required for the course. A Scientific Calculator is the one, which has capability to give you, say, the result of square root of 5. Any calculator that goes beyond the 4 operations is fine for this course. These calculators allow you to perform simple calculations you need in this course, for example, enabling you to take square root, to raise e to the power of say, 0.36. and so on. These types of calculators are called general Scientific Calculators. There are also more specific and advanced calculators for mathematical computations in other areas such as Finance, Accounting, Civil Engineering, and even Statistics. The last one, for example, computes mean, variance, skewness, and kurtosis of a sample by simply entering all data one-by-one and then pressing any of the mean, variance, skewness, and kurtosis keys.
Without a computer one cannot perform any realistic statistical data analysis. Students who are signing up for the course are expected to know the basics of Excel, and other popular Spreadsheet.
As a starting point, you need visiting the Excel Web site created for this course. If you are challenged by or unfamiliar with Excel, you may seek tutorial help from the Academic Resource Center at 410-837-5385, E-mail.
This section is a part of the JavaScript E-labs learning tools for decision making. The following is a classification of statistical JavaScript by their application areas: MENU
The Main Web Sites I Recommend
The following main statistical web sites and the lecture notes, together with your textbook contain all the materials you need to learn statistics. Make sure to visit these sites at least once a week to learn more on the related topics covered in this course. Some other useful and specialized web sites are linked to your Weekly Topics pages.
General main statistical Web sites:
- Animated Statistical Demonstrations
- Bulletin Board Libraries
- Business Problem Solving
- Epidemiology and Biostatistics
- Financial and Economic Links
- How to Study Statistics
- Intro. to Stat.
- Java Applets
- Java Applets for Visualization of Statistical Concepts
- Lecture summaries
- Merlot
- Online Lecture Outlines
- Online statistical computation
- Online Statists Texts and Courses
- Probability
- Statistical Education Resource Kit
- Statistical Programs
- Statistical Training on the Web
- Statistics Education-I
- Statistics Education-II
- Statistics on the Web
- Statistics, Statistical Computing, and Mathematics
- st@tserv
- SurfStat
- Using Excel
- Virtual Library
- WebEc
- World Lecture Hall
- Yahoo:Statistics
Web Sites Containing Statistical Keywords & Phrases:The following Web site collection provide a wide range of keywords & phrases. Visit these sites weekly to learn the language of statisticians.
Statistical Demos:
Statistical Computation and Tables:
The following Web sites provide statistical computations and tables such ad critical values useful in statistical testing and construction of confidence intervals. The results are identical to those given in your textbook. However, in most cases they are more extensive (therefore more accurate).
- Web Pages that Perform Statistical Calculations
- Normal Probability Calculation
- Calculate Mean, Standard Deviation
- Creating a Histogram
- Probability Calculator
- StatCalc
- Statstical Calculators
- SurfStat statistical tables
Your Fellow Students' Opinion and Advice
The following is a collection of comments on the value of the course from last semester's students. I am sure you will benefit from their experience and their precious advice for your success upon taking this course. As you can see, the most frequently mentioned recommendation is to keep up with the work and complete all assignment prior to coming to class.
- Dear Dr. Arsham,
I want to thank you for all the knowledge that you transmit to the class I really enjoy your class and all your comments about the need of Stats in everything because as you have said "everything is business" probably some of us already knew that but many of them did not and I think that you turn on the light on their heads which is very valuable for the students and for UB community.
- Dear Dean McCarthy,
As an engineer pursuing my MBA, I found Dr. Arsham's course on Business Statistics to be the most useful course I've taken to date at UB in Bridging the gap between the technical world and that of the managerial. Dr. Arsham is able to bring numbers and statistics alive and give them meaning. As An instructor he is both disciplined and understanding of student needs.
While he is uncompromising in his method of teaching and rigorous in his treatment of the material, he is also most forgiving as I grew as a student under his tutelage.
In past courses I have never had difficulties with mathematics such as calculus or differential equations, but statistics and probability courses have always vexed me. For the first time in my life, Dr. Arsham has enabled me to grasp the elusive meaning and mechanics of statistical analysis. Indeed, I've even purchased and began reading one of the books from his "recommended reading list" in order to continue my growth in this subject area. At this point I can honestly say that a well-founded knowledge of basic statistics may be the most important class a business student should consider taking. I HIGHLY recommend his course to any serious student who really wants to know how to analyze and understand statistics.Sincerely,
"signed"
Senior Consultant
Booz Allen and Hamilton
- Dr. Arsham is very knowledgeable on the subject and is able to provide real world examples. His lectures are thought provoking and simplistic enough to engage your work. My suggestion to the following classes is to keep up with the reading and pay attention to the lectures. The text, the lectures, and the lecture notes, provide all the information that you will need for the homework and the exams. If you keep up with the homework, the reading, and attend class, the class is very passable. If not, you will be in for a long semester. Good luck to you as you embark on the adventure of learning a new language.
- OPRE 504 is a well-rounded class with opportunities to learn from the Web sites the lectures, book and lecture notes. The lectures were particularly helpful as Dr. Arsham spoke a lot about the concepts that are important, why they are important, and what they mean. Dr. Arsham also takes the time to review the highlights throughout the course, as well. It was helpful to have this conceptual information to see how the pieces fit together. The course information Web site was very useful- to check your homework, to use E-labs to complete assignments, for reading about special topics, and to use practice questions and practice exams. The external Web sites reviews were fun too, who knew there was so much information available about statistics? Some of them were really fun with neat graphics.
- Given the often-complex subject matter, which for those who are unable to analyze and interpret statistical methods and concepts, Professor Arsham did an admirable job of motivating me to succeed. He took the time to excite the class into believing that business statistics, in its purest form, can be used in most everyday activities. After taking this class with Professor Arsham, I feel better prepared to utilize what he taught me in other classes in my pursued of my MBA. Thank you Professor Arsham.
- I had a great opportunity learning about Business Statistics for decision-making subject with this course. Before taking course I have little knowledge about statistics which most of them I could not even remember. I love studying with the numbers and the course was based on the numbers. That is another subject I like about the course. The exams' style makes students not to memorize, instead make them to understand and learn. In my personal view understanding and learning are much better than memorizing. Because memorizing is short-term whereas understanding is long term. To tell the truth about the course web site although it is complicated it gives all the information that I need. I did not even buy the book, but study lecture notes and course notes on the web. So that it was very helpful for me. Also I learned several useful web sites because of the links in the course web site.
- As an engineer pursuing my MBA, I found Dr. Arsham's course on Business Statistics to be the most useful course I've taken to date at UB in bridging the gap between the technical world and that of the managerial. Dr. Arsham is able to bring numbers and statistics alive and give them meaning. As an instructor he is both disciplined and understanding of student needs. While he is uncompromising in his method of teaching and rigorous in his treatment of the material, he is also most forgiving as I grew as a student under his tutelage. In past courses I have never had difficulties with mathematics such as calculus or differential equations, but statistics and probability courses have always vexed me. For the first time in my life, Dr. Arsham has enabled me to grasp the elusive meaning and mechanics of statistical analysis. Indeed, I've even purchased and began reading one of the books from his "recommended reading list" in order to continue my growth in this subject area. At this point I can honestly say that a well-founded knowledge of basic statistics may be the most important class a business student should consider taking. I HIGHLY recommend his course to any serious student who really wants to know how to analyze and understand statistics.
Homework Assignments to Do Before
Each Class Meeting and Sample TestsPlease read and follow the Instructions on your homework assignment. Thank you.
We will follow the following sequence (Not a weekly-schedule) of topics.
Introduction: In this diverse world of ours, no two things are exactly the same. A statistician is interested in both the differences and the similarities, i.e. both patterns and departures.
Exploratory analysis of data makes use of numerical and graphical techniques to study patterns and departures from patterns. The widely used descriptive statistical techniques are: Stem & Leaf, Box Plot, Frequency Distribution, Empirical Cumulative Distribution, Histograms; and Scatter-diagram.
The actuarial tables published by insurance companies reflect their statistical analysis of the average life expectancy of men and women at any age. From these numbers, the insurance companies then calculate the appropriate premiums for a particular individual to purchase a given amount of insurance.
In examining distributions of data, you should be able to detect important characteristics, such as shape, location, variability, and unusual values. From careful observations of patterns in data, you can generate conjectures about relationships among variables. The notion of how one variable may be associated with another permeates almost all of statistics, from simple comparisons of proportions through linear regression. The difference between association and causation must accompany this conceptual development.
Data must be collected according to a well-developed plan if valid information on a conjecture is to be obtained. The plan must identify important variables related to the conjecture and specify how they are to be measured. From the data collection plan, a model can be formulated from which inferences can be drawn.
Objectives: What is statistics and what can it do? The main objective of this unit is to orient you to the subject of Business Statistics. When you have successfully completed this unit, you will know what to expect from this course and you will have an overview of the topics involved in the weeks to come. In the course you will learn to use statistical techniques to investigate business situations, and you will gain a good understanding of statistical ideas and thinking.
Read Ch (1-2), there's nothing much in Ch (1-2) to challenge you. It is an attempt to orient you to the subject of Business Statistics.
Read the Lecture Notes' Chapter 1.
Visit the following external Web sites:
After you did your reading assignment, and visiting the external Web sites, then write a 2-page essay entitled: "What is Business Statistics?" You essay should, among others, address the following questions:
Introduction: Decision makers make better decisions when they use all available information in an effective and meaningful way. The primary role of statistics is to provide decision makers with methods for obtaining and analyzing information to help make these decisions. Statistics is used to answer long-range planning questions, such as when and where to locate facilities to handle future sales.
One must understand conceptually the meanings of measures of locations of the central tendency, e. g. mean, median, and mode, and measures of variability, e. g., range, variance, standard deviation, and coefficient of variation.
The problem most decision makers must solve is how to deal with the uncertainty that is inherent in almost all aspects of their jobs. Raw data provide little, if any, information to the decision makers. Thus, they need a means of converting the raw data into useful information. In this lecture, we will concentrate on some of the frequently used methods of presenting and organizing data.
Objectives: When you successfully complete this unit, you will be able to cite examples to show the importance of data and statistical summary measures in business. You will be able to use alternative methods and measures to describe sets of data so that the phenomena they represent can be more easily understood. You will be able to enter data, use the Web-based statistical computation functions to obtain descriptive statistics, and interpret results. You will be able to identify the formula used by the Web-based computer to make calculations and perform simple calculations with those formulas on a hand held calculator using the raw (or original) individual values. You will also be expected to recognize when data transformations are needed before attempting to represent magnitudes with the standard measures of location and dispersion.
Read Ch (2-3). Read the Lecture Notes' Chapter 2 .
Visit the following external Web sites:
Do problems 2(2, 4, 14, 22), 3(2, 8, 20, 36, 60).
E-Labs and Computational Tools: Select those JavaScript from the collection under MENU that can be applied to the current topics and then perform some numerical experiment for deeper understanding of the concepts. For example, you may like checking your hand-computations for the homework problem(s), or checking the numerical examples from your textbook. Submit along with the rest of your homework, a short report entitle Computer Assignments describing your findings, no need to include any printout.
As a stating point, I suggest the following JavaScript:
Introduction: Probability theory provides a way to find and express our uncertainty in making decisions about a population from sample information. Please, see the Chart given in the first week lecture note for the relevancy of Probability to Statistics.
Any generalization and extension of the results obtained from a random sample to the population contains uncertainties. How do you measure uncertainty? The answer is: By Probability measure.
Objectives: When you successfully complete this unit, you will be acquainted with the notion of a random variable and the basic rules of probability. You will be familiar with the expected values (means and variances) of a random variable and the sum of random variables. You will be able to articulate the difference between a mean calculated with relative frequencies and probabilities. You will be able to calculate means and standard deviations. You will be able to make applications to business and economics as well as personal financial situations (and in your Finance courses).
Read Ch. 4, and Ch. 5 sections 5.1, 2, 3, 4. Read the Lecture Notes' Chapter 3 (sections 1-9).
Visit the following external Web sites:
Do Problems 4(4, 10, 30, 34, 44, 54), and 5(2, 8, 12, 22).
E-Labs and Computational Tools: Select those JavaScript from the collection under MENU that can be applied to the current topics and then perform some numerical experiment for deeper understanding of the concepts. For example, you may like checking your hand-computations for the homework problem(s), or checking the numerical examples from your textbook. Submit a short report of your findings. As a stating point, I suggest the following JavaScript:
Introduction: A Random Variable is a quantity resulting from a random experiment that, by chance, can assume different values, such as, number of defective light bulbs produced during a week. Also, we said a Discrete random Variable is a variable which can assume only integer values, such as, 7, 9, and so on. In other words, a discrete random variable cannot take fractions as value. Things such as people, cars, or defectives are things we can count and are discrete items. In this unit, we will discuss Binomial distribution which a widely used distribution for discrete random variables.
A Continuous random is a variable can take on any value over a given interval. Continuous variables are measured, not counted. Items such as height, weight and time are continuous and can take on fractional values. For example, a basketball player may be 6.954 feet tall.
There are many continuous probability distributions, such as, uniform distribution, normal distribution, the t-distribution, the chi-square distribution, and F-distribution. In this unit, we will concentrate on the uniform and normal distributions.
Objectives: When you successfully complete this unit, you will be able to articulate the difference between probabilities associated with discrete and continuous random variables. You will be able to identify the use of discrete distributions in real and hypothetical situations. You will be able to identify the correct use of specific continuous distributions in real and hypothetical situations. You will know the general properties of the normal and t-distributions, and be aware of the existence and possible use of other continuous distributions like the Chi-square and F. You will be able to use available Web-based tools to obtain probabilities from these distributions.
Read Chs. 5 and 6. Read the Lecture Notes' Chapter 3 (topics under section 10).
Do problems 5(26, 28), and 6(2, 4, 6, 8, 19, 36).
E-Labs and Computational Tools: Select those JavaScript from the collection under MENU that can be applied to the current topics and then perform some numerical experiment for deeper understanding of the concepts. For example, you may like checking your hand-computations for the homework problem(s), or checking the numerical examples from your textbook. Submit a short report of your findings. As a stating point, I suggest the following JavaScript:
Introduction: You may recall that there are several good reasons for taking a sample instead of conducting a census, for example, to save time, money, etc. Also, in the same lecture we said that if a for example, a marketing researcher is using data gathered on a group to reach conclusions about that same group only, the statistics are called descriptive statistics. For example, if I produce statistics to summarize my class's examination effort and use those statistics to reach conclusions about my class only, the statistics are descriptive. On the other hand, if a researcher collects data from a sample and uses the statistics generated to reach conclusions about the population from which the sample was taken, the statistics are inferential statistics. The data collected are being used to infer something about a large group.
In attempting to analysis the sample statistic, it is essential to know the distribution of the statistic. In this lecture, we are going to talk about the sample mean as the statistic. In order to compute and assign the probability of occurrence of a particular value of a sample mean, we must know the distribution of the sample means. In other words, how are sample means distributed? One way to examine the distribution possibilities is to take a population with a particular distribution; randomly select samples of given size, compute the sample means, and attempt to determine how the means are distributed.
Objectives: When you successfully complete this unit, you will be able to describe different methods of sampling and demonstrate how the Central Limit Theorem and sampling distributions are used for estimation in statistical analysis. You will be able to articulate what a sampling distribution is, and to explain the relationship between an estimator and the parameter being estimated. You will be expected to make statistical inferences and constructing confidence interval within practical business applications involving the estimation of mean and the variance s2 using the t (or z), and c2 (read, ki-square, it's not squared of anything, its name is Chi-square read, ki-square). There is no such thing as ki in statistics. I'm glad that you're overcoming all the confusions exist in learning statistics) distributions, respectively.
Read Ch. 7. and Ch. 8. Read the Lecture Notes' Chapters (4-5)
Visit the following external Web site:
Do problems 7(8, 12, 20), 8(4, 10, 16, 18, 40, 46, 54, 84).
E-Labs and Computational Tools: Select those JavaScript from the collection under MENU that can be applied to the current topics and then perform some numerical experiment for deeper understanding of the concepts. For example, you may like checking your hand-computations for the homework problem(s), or checking the numerical examples from your textbook. Submit a short report of your findings. As a stating point, I suggest the following JavaScript:
Introduction: In the previous unit, our discussion partly was on sampling from a population, we have known the population, and calculated the chance (exact or approximate) that, for example, the average of the sample would be in some range. That is, a probability calculation. We also learnt, how to construction of confidence intervals for population parameters (mean and variance), which is working backwards from a sample to population, or to infer something about the population, of course, subject to some uncertainty. This is one of the most important and fundamental problems statistics addresses: how to estimate and make inferences about a parameter of a population based on a random sample taken from the population, using a CORRECT statistic method.
Because the value the estimator takes depends on the sample, the estimator's value is random, and will not typically equal the value of the population parameter. We need to understand how the value of the estimator varies for different possible samples to be able to say how close or how far from the parameter value the estimator's value is likely to be. That's essentially what a C.I. is for.
Now we turn on to test of hypotheses (claims) about mean and variance of a population or concerning comparison of these parameters for two populations based on random samples.
We learn that there is a duality between the test of hypothesis and construction of confidence interval. That is, instead of performing a test for a claimed value for the population parameter, we may construct a confidence interval, and then see if the constructed confidence interval contained the claimed valued.
Objectives: When you successfully complete this unit, you will be able to use sample data to test claims and statements about population (and comparisons of two populations) parameters (mean and variance). You will be able to specify the null and alternative hypotheses, select and calculate a correct test statistics, and use p-values in decision making. You will also be able to do all
Read Chs. 10, 11, and Read the Lecture Notes' Chapters (6-7)
Visit the following Web site:
Do problems 10(4,10, 16, 22, 28), and 11(2, 8, 36, 42, 50, 64, 74, 78).
E-Labs and Computational Tools: Select those JavaScript from the collection under MENU that can be applied to the current topics and then perform some numerical experiment for deeper understanding of the concepts. For example, you may like checking your hand-computations for the homework problem(s), or checking the numerical examples from your textbook. Submit a short report of your findings. As a stating point, I suggest the following JavaScript:
Your preparation is a very important undertaking in terms of integrating what you have learned each week in order to see the whole picture and inter-connectivity of the topics.
To prepare yourself for the actual test, you are advised to review all the topics we have covered, to review past homework assignment, and then prepare your own few pages of a summary sheet. The process of producing a summary sheet, helps you to crystallize your mind to be reflective and responsive to any question posed to you about the topics you've learned in this course, it also helps you to reinforce the wholeness of the topics in your mind.
Click here to read a conceptual summary-sheet prepared by one of your classmates. If you think you have prepared a better one, kindly send it to me via an attached email. Thank you.
Here is A Why List (Word.Doc) containing a set of good questions, asked during our class meetings.
A good source for practice questions is the Web site Practice Questions, sections: Descriptive Statistics, Probability, Distributions, Making Inferences, and the Hypothesis Testings.
Exercise Your Knowledge on this Sample of Past Midterm Tests:
Introduction: Analysis of Variance or ANOVA is a technique for comparing several populations’ means. We have already learned how to use the t-test (or z-test, for large samples) for test of hypothesis with respect to equality of means in two populations. Therefore, ANOVA is an extension of t-test for testing the equality of means in more than two populations. The conditions under which this test can be applied are as follows: Populations must has normal distributions, and Variations in the populations must be equal
In ANOVA we partition the total variation into two components: variation within each population, and variation between the populations. Under the above conditions, if these two components are the same magnitude, then there is no reason to reject that these populations are, in fact the same. That is, there are all normally distributed, having same mean and same variance.
Objectives: When you successfully complete this unit, you will be able to use sample data to test claims and statements about the means of several populations. You will learn the necessary conditions under which such a test would be valid.
Read Ch. 14 (sections 1-4). and Read the Lecture Notes' Chapters (8).
Visit the following external Web site:
Do problems 14(1, 2, 10).
E-Labs and Computational Tools: Select those JavaScript from the collection under MENU that can be applied to the current topics and then perform some numerical experiment for deeper understanding of the concepts. For example, you may like checking your hand-computations for the homework problem(s), or checking the numerical examples from your textbook. Submit a short report of your findings. As a stating point, I suggest the following JavaScript:
Introduction: The statistics such as Covariance, Correlation, and Regression indicate mathematical linear relationship between two or more variables within the same population.
Objectives: This unit covers the statistical modeling of situations in which a response variable depends on one or several explanatory variables. When you successfully complete this unit, you will be able to identify situations in which there may be a linear relationship between a dependent variable y and an independent variable x. With paired data on y and x, you will be expected to use the method of least squares with the Web-based tools and Excel to estimate the linear relationship between these two variables; y values will then be predicted, and hypotheses about the slope or intercept will then be tested within this framework. You will be expected to interpret coefficients and other statistics produced by these computational tools.
Read Ch. 12. and Read the Lecture Notes' Chapter 10.
Do problems 12(8, 20, 29, 42, 54, 66).
E-Labs and Computational Tools: Select those JavaScript from the collection under MENU that can be applied to the current topics and then perform some numerical experiment for deeper understanding of the concepts. For example, you may like checking your hand-computations for the homework problem(s), or checking the numerical examples from your textbook. Submit a short report of your findings. As a stating point, I suggest the following JavaScript:
Click here to read a conceptual summary-sheet prepared by one of your classmates , and Statistics Summary-sheet Formulas (PDF) (print to enlarge) by another. If you think you have prepared a better one, kindly send it to me via an attached email. Thank you.
Review all your past assignments. For practice questions visit the Web site Practice Questions, ALL sections including ANOVA, and Regression Analysis.
Exercise Your Knowledge on this Sample of Past Final Tests:
Here is A Why List (Word.Doc) containing a set of good questions, asked during our class meetings.