MBA 503.02 – Data Analysis and Decision Making; Fall 2017...MBA PROGRAM LEARNING OBJECTIVE MBA 503...
Transcript of MBA 503.02 – Data Analysis and Decision Making; Fall 2017...MBA PROGRAM LEARNING OBJECTIVE MBA 503...
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MBA 503.02 – Data Analysis and Decision Making; Fall 2017
Mondays and Wednesdays: 10:00 AM – 11:20 AM; Harriman Hall Room 104
Professor Thomas R. Sexton; Office: Harriman Hall Room 317
E-Mail: [email protected] ; Telephone: (631) 632-7181
Office Hours: Mondays and Wednesdays 11:30 AM – 12:30 PM
Course Description This course is an introduction to data analysis and decision making in business. We will motivate each
topic with managerial applications, and we will analyze actual data sets using modern statistical
software. Topics include data collection, summarization, and presentation; probability and probability
distributions; confidence intervals; hypothesis testing; and regression analysis.
Goals of the Course In your career, you will often face situations in which a clear understanding of statistical thinking and
decision-making methodology will be essential. I have designed the course to:
1. Introduce the basic concepts and methods of statistics and decision making,
2. Demonstrate the applications of statistics and analytical decision making in business,
3. Enable you to perform statistical and decision analyses using appropriate software, and
4. Help you to become a wise consumer of statistical and decision analyses performed by
others.
Why Business Students Need Business Statistics Let’s say that you’re interested in finance. Then you know that investment strategy is all about return
and risk. How will a portfolio fare in an uncertain world? Why do well-informed investors include funds
that perform well in certain circumstances and others that perform poorly under the same
circumstances? How can you measure the volatility of a stock relative to the market? If you understand
uncertainty, expected value, variance, regression analysis, and correlation, then you have a strong
competitive advantage over those who do not.
Let’s say that you’re interested in marketing. Then you know that successful marketers have a good
understanding of the markets they target. How do they obtain such knowledge? How do marketers
design surveys and other data collection devices that will give them a clear and unbiased look at their
markets? What traps must they avoid so as not to make serious mistakes? How many people must they
survey, and how must they select those people, to obtain the precision that they need without incurring
undue cost? If you understand the principles of random sampling, the types of nonrandom errors that
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can destroy a data set, and some simple ways to judge the size of the sampling error present in any data
set, then you have a strong competitive advantage over those who do not.
Let’s say that you’re interested in operations. Then you know that keeping a business running smoothly
requires that you keep in touch with current operations. How do you know when a production line is
producing too many defective items and needs adjustment, repair, or recalibration? How can you tell
which suppliers are the most dependable links in your supply chain? What inventory levels should you
maintain to keep customers happy and costs low? Will a proposed new computer information system
speed customer orders or will it simply be a large expense with little positive impact on the company’s
bottom line? If you understand the principles of sampling distributions, estimation, confidence intervals,
and hypothesis testing, then you have a strong competitive advantage over those who do not.
Whether you are interested in human resource management, information systems management, health
care management, or any other business discipline, you will need to understand how to deal with
problems like these. Whether you work in energy, transportation, retailing, business-to-business, real
estate, or any other industry, you will find yourself making decisions in an uncertain environment in
which your ability to analyze data (and understand analyses performed by others) will be a key to your
success. That’s why business students need a course like this.
College of Business Learning Objectives This course contributes to the College of Business Learning Objectives in the following way:
MBA PROGRAM
LEARNING OBJECTIVE MBA 503 ACTIVITY
Critical Thinking,
Problem Solving, and
Decision Making
In this course, you will learn how to think critically about business problems
and how to apply standard statistical and decision analytical methods to
solving business problems and to improving business decision making.
Course Learning Objectives When you have successfully completed this course, you will be able to:
1. Recognize the many types and sources of business-related data
2. Recognize the many acceptable and unacceptable ways to collect data to support business
decision making
3. Summarize data using summary statistics and statistical charts to support business decision
making
4. Understand the major importance of variability in business decision making
5. Understand and be able to use basic probability concepts and probability distributions to solve
problems related to business
6. Understand the basic concepts of sampling and the nature of sampling distributions in business
decision making contexts
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7. Compute and interpret confidence intervals for percentages and means and apply them in
business decision making contexts
8. Compute and interpret one- and two-sample hypothesis tests for percentages and means and
apply them in business decision making contexts
9. Construct and interpret univariate and multivariate regression models and apply them in
business decision making contexts
I will assess your learning by your performance on assignments and exams.
Textbook and Computer Software The textbook is Applied Statistics in Business and Economics, 5e, Doane and Seward, McGraw-Hill/Irwin.
The textbook available through the bookstore is packaged with ConnectPlus, which includes Connect
and access to the online textbook. If you decide to purchase the textbook elsewhere, then I highly
recommend that you also purchase ConnectPlus. You will need Connect in this course.
We will use Microsoft Excel for most of our statistical calculations. If you wish, you may download and
install an Excel add-in called Megastat at no charge from:
HTTP://HIGHERED.MHEDUCATION.COM/SITES/0070000237/STUDENT_VIEW0/MEGASTAT_TUTORIALS.HTML. You can
visit HTTP://IT.STONYBROOK.EDU/SOFTWARE/TITLE/MICROSOFT-OFFICE to receive Microsoft Office for free.
Connect Plus Connect Plus is an online system in which you will complete your assignments and take exams. Please
review the PowerPoint presentation entitled “Connect-Blackboard-FDOC_2011” in the Documents
section of our Blackboard web site.
Class Attendance and Participation Your attendance and your participation in every class are important! You cannot succeed in this course
if you miss class. I will take attendance in some class meetings, and I will monitor your participation in
class discussions. This means that you should always ask questions when you are unclear on something,
and you should offer answers or helpful comments when appropriate.
When we meet, we will focus on activities, demonstrations, and discussions designed to enhance your
learning of the course material. I will not discuss every topic in detail – I expect you to read each chapter
before we discuss it – I will focus on the more challenging aspects of the topic in class.
Please see the web link “Why Do I Have to be On Time?” in the Documents section of our Blackboard
web site.
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Blackboard Web Site The Blackboard web site for this course will serve many important functions. You will use Blackboard to
access your Connect assignments. I will use Blackboard to make announcements, distribute course
materials, and record grades. You can access Blackboard at HTTPS://BLACKBOARD.STONYBROOK.EDU/. For
help, visit HTTP://IT.STONYBROOK.EDU/SERVICES/BLACKBOARD. You can also call 631-632-9602 or e-mail
Class Schedule Here is our daily class schedule:
Class Day Date Chapter/Topic
1 Monday 28-Aug-17 Introduction to the course
2 Wednesday 30-Aug-17 2. Data Collection
Monday 4-Sep-17 Labor Day (No Class)
3 Wednesday 6-Sep-17 3. Describing Data Visually
4 Monday 11-Sep-17 4. Descriptive Statistics
5 Wednesday 13-Sep-17 5. Probability
6 Monday 18-Sep-17 5. Probability
7 Wednesday 20-Sep-17 5. Probability
8 Monday 25-Sep-17 6. Discrete Probability Distributions
9 Wednesday 27-Sep-17 6. Discrete Probability Distributions
10 Monday 2-Oct-17 6. Discrete Probability Distributions
11 Wednesday 4-Oct-17 6. Discrete Probability Distributions
12 Monday 9-Oct-17 7. Continuous Probability Distributions
13 Wednesday 11-Oct-17 Connect Exam #1
14 Monday 16-Oct-17 7. Continuous Probability Distributions
15 Wednesday 18-Oct-17 8. Sampling Distributions and Estimation
16 Monday 23-Oct-17 8. Sampling Distributions and Estimation
17 Wednesday 25-Oct-17 8. Sampling Distributions and Estimation
18 Monday 30-Oct-17 9. One-Sample Hypothesis Tests
19 Wednesday 1-Nov-17 9. One-Sample Hypothesis Tests
20 Monday 6-Nov-17 10. Two-Sample Hypothesis Tests
21 Wednesday 8-Nov-17 10. Two-Sample Hypothesis Tests
22 Monday 13-Nov-17 Connect Exam #2
23 Wednesday 15-Nov-17 10. Two-Sample Hypothesis Tests
24 Monday 20-Nov-17 12. Simple Regression
Wednesday 22-Nov-17 Thanksgiving Break (No Class)
25 Monday 27-Nov-17 12. Simple Regression
26 Wednesday 29-Nov-17 12. Simple Regression
27 Monday 4-Dec-17 13. Multiple Regression
28 Wednesday 6-Dec-17 13. Multiple Regression
Tuesday
19-Dec-17 2:15 PM - 5:00 PM
Final Exam on Connect
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Examinations The exams will be given on the dates shown above. All three exams will be given online using Connect. I
will not give make-up exams without (a) advanced notice that you will miss the exam, and (b) written
documentation explaining the reason for your absence. I will judge the adequacy of the reason and the
appropriateness of a make-up exam. I reserve the right to format the make-up exam as an oral exam.
The exams cover the material shown here:
EXAM CHAPTERS
Connect Exam 1 2, 3, 4, 5, 6
Connect Exam 2 7, 8, 9
Final Exam 10, 12,13
You will take the Connect Exams during class time on the indicated dates. You do not need to come to
class on those days. Log in to Connect at the beginning of class and take the exam. The exam will time
out at precisely the end of class. You may use any resources you want except other people during the
exam.
Grading System The following table shows the grading allocation for the course. You will need a 90% course average to
receive a final grade of A, 80% for a B, and 70% for a C. Of course, I will also use plus and minus final
letter grades. I do not “curve” grades – potentially everyone in the class can receive an A. You will be
graded based on your performance, not that of anyone else in the class!
Lowest Exam Grade 22%
Middle Exam Grade 25%
Highest Exam Grade 28%
LearnSmart Assignments 10%
Connect Assignments 15%
Stony Brook University Syllabus Statements Disability Support Services (DSS) Statement: If you have a physical, psychological, medical, or learning
disability that may impact your course work, please contact Disability Support Services, 128 ECC
Building, (631) 632-6748, or [email protected]. They will determine with you what accommodations
are necessary and appropriate. All information and documentation is confidential.
Students who require assistance during emergency evacuation are encouraged to discuss their needs
with their professors and Disability Support Services. For procedures and information go to the following
website: HTTPS://EHS.STONYBROOK.EDU/PROGRAMS/FIRE-SAFETY/EMERGENCY-EVACUATION/EVACUATION-GUIDE-
PEOPLE-PHYSICAL-DISABILITIES and search Fire Safety and Evacuation and Disabilities.
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Academic Integrity: Each student must pursue his or her academic goals honestly and be personally
accountable for all submitted work. Representing another person's work as your own is always wrong.
Any suspected instance of academic dishonesty will be reported to the Academic Judiciary. For more
comprehensive information on academic integrity, including categories of academic dishonesty, please
refer to the academic judiciary website at WWW.STONYBROOK.EDU/ACADEMICINTEGRITY.
Critical Incident Management: Stony Brook University expects students to respect the rights, privileges,
and property of other people. Faculty are required to report to the Office of Judicial Affairs any
disruptive behavior that interrupts their ability to teach, compromises the safety of the learning
environment, or inhibits students' ability to learn. Faculty in the HSC Schools and the School of Medicine
are required to follow their school-specific procedures.
The College of Business Statement Regarding Academic Dishonesty The College of Business regards any act of academic dishonesty as a major violation punishable by
severe penalties, including dismissal from the University. University policy requires that instructors and
GAs report all suspected cases of academic dishonesty to the appropriate Academic Judiciary
Committee, which is empowered to take strong action against violators, including expulsion from the
University. Please note that there is a link to the Academic Judiciary web site on the Blackboard home
page.
Under no circumstances will the College of Business permit cheating of any kind. Many activities
constitute academic dishonesty. The following list is not inclusive, only suggestive:
On Examinations: ▪ Referring in any way to the examination paper of another student.
▪ Use of materials (notes, books, etc.) not explicitly permitted by the instructor.
▪ The exchange of any information concerning the examination with any other person after the
examination has begun.
On Papers: ▪ The submission in whole or part of the work of another person as if it were your own.
▪ The citation of the work of others without proper reference and credit.
If you have any questions about the honesty of an action, please consult with any faculty member for
clarification. We will not construe such consultation as evidence that you have committed any violation
or are even contemplating it. We will not accept failure to understand the rules as an excuse.
If you are considering any act of academic dishonesty, the College of Business advises you in the
strongest possible terms to abstain. The consequences associated with academic dishonesty are
substantial enough literally to ruin your career. DON’T DO IT.
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What is Plagiarism? There is nothing wrong with using the words or thoughts of others or getting help. Indeed, it is good to
do so as long as you explicitly acknowledge your debt. It is plagiarism when you pass off the work of
others as though it were your own:
▪ Copying without quotation marks or paraphrasing without acknowledgment from the writing of
someone else.
▪ Using someone else’s facts or ideas without acknowledgment.
▪ Submitting work in one course that you submitted for credit in another course without the
permission of both instructors.
You can strengthen your paper by using material by others – as long as you acknowledge your use, and
as long as you use that material as a building block for your own thinking rather than a substitute for it.
When you use published words, data, or thoughts, you must footnote your use. (See any handbook or
dictionary for footnote formats.) When you use the words or ideas of friends or classmates, you should
thank them in an endnote (e.g., “I am grateful to my friend so-and-so for the argument in the third
paragraph.”) If friends just give you reactions but no suggestions, you need not acknowledge that help in
print (though it is gracious to do so).
The academic and business worlds depend on people using the work of others for their own work.
Dishonesty destroys the possibility of working together as colleagues. Faculty and researchers do not
advance knowledge by passing off the work of others as their own. Students do not learn by copying
what they should think out on their own. Therefore, the University insists that instructors report every
case of plagiarism to the Academic Judiciary Committee, which keeps records of all cases. The
recommended penalty for plagiarism is failure for the course and possible expulsion from the
University.
Unintentional plagiarism is still plagiarism. You cannot plead ignorance. Therefore, if you have any
questions about the proper acknowledgment of help, be sure to ask your instructor.