MBA 503.01 – Data Analysis and Decision Making; …...This course is an introduction to data...
Transcript of MBA 503.01 – Data Analysis and Decision Making; …...This course is an introduction to data...
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MBA 503.01 – Data Analysis and Decision Making; Fall 2018
Mondays and Wednesdays: 10:00 AM – 11:20 AM; Harriman Hall Room 104
Professor Thomas R. Sexton; Office: Harriman Hall Room 317
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
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undue cost? If you understand the principles of random sampling, the types of nonrandom errors that
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:
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
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6. Understand the basic concepts of sampling and the nature of sampling distributions in business
decision making contexts
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
Textbook and Computer Software The textbook is Applied Statistics in Business and Economics, 5e, Doane and Seward, McGraw-Hill/Irwin.
You will also need Connect in this course. Connect 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. You MUST log in to Connect through
Blackboard.
When you come to class, please bring a computer that has Microsoft Excel installed. You can visit
http://it.stonybrook.edu/software/title/microsoft-office to receive Microsoft Office for free. We will use
Microsoft Excel and Statistix 10 for our statistical calculations.
Statistix is available on the Virtual SINC Site. Go to https://it.stonybrook.edu/services/virtual-sinc-site.
Click “Launch Virtual SINC Site”. You will need to log on with your NetID and password. You will need to
download the Citrix receiver the first time, unless you already have it installed on your computer. Click
on the “Virtual SINC Site Desktop” icon, click the Windows Start button in the lower left corner, open
the “Statistix” folder, and click on the “Statistix 10” icon. Do all of this before coming to our next class
meeting!
Class Attendance, Contributions, and Days in the Office Your attendance in every class (like every business meeting) is important! You cannot succeed in this
course if you miss class. More importantly, your contributions in every class (like in every business
meeting) are critical! Please ask questions and answer those for which you think you know the answer.
In some class meetings, I will randomly split the class into teams of 2-3 students. I will give each team an
assignment that uses the material of this course to address a business situation. Each team will have
time to devise a solution. I will randomly select one member of each team to present their team’s
solution and answer follow-up questions from me (your supervisor) and from other members of the
class (your co-workers). The response will be graded on a 3-point scale: 3=Perfect response; 2=Good
response; 1=Weak response; 0=Unusable response. These exercises will simulate a “Day in the Office.”
Your performance in these exercises will be part of your final grade.
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Class Schedule Class Day Date Chapter/Topic
1 Monday 27-Aug Introduction to the course
2 Wednesday 29-Aug 2. Data Collection Monday 3-Sep Labor Day
3 Wednesday 5-Sep 3. Describing Data Visually/4. Descriptive Statistics
4 Monday 10-Sep 5. Probability
5 Wednesday 12-Sep 5. Probability
6 Monday 17-Sep 5. Probability
7 Wednesday 19-Sep 5. Probability
8 Monday 24-Sep 6. Discrete Probability Distributions
9 Wednesday 26-Sep 6. Discrete Probability Distributions
10 Monday 1-Oct 6. Discrete Probability Distributions
11 Wednesday 3-Oct 7. Continuous Probability Distributions Monday 8-Oct Fall Break
12 Wednesday 10-Oct 7. Continuous Probability Distributions
13 Monday 15-Oct 7. Continuous Probability Distributions
14 Wednesday 17-Oct 8. Sampling Distributions and Estimation
15 Monday 22-Oct 8. Sampling Distributions and Estimation
16 Wednesday 24-Oct Midterm Exam
17 Monday 29-Oct 8. Sampling Distributions and Estimation
18 Wednesday 31-Oct 9. One-Sample Hypothesis Tests
19 Monday 5-Nov 9. One-Sample Hypothesis Tests
20 Wednesday 7-Nov 9. One-Sample Hypothesis Tests
21 Monday 12-Nov 10. Two-Sample Hypothesis Tests
22 Wednesday 14-Nov 10. Two-Sample Hypothesis Tests
23 Monday 19-Nov 10. Two-Sample Hypothesis Tests Wednesday 21-Nov Thanksgiving
24 Monday 26-Nov 12. Simple Regression
25 Wednesday 28-Nov 12. Simple Regression
26 Monday 3-Dec 12. Simple Regression
27 Wednesday 5-Dec 13. Multiple Regression
28 Monday 10-Dec 13. Multiple Regression
Monday 19-Dec
2:15 - 5:00 PM Final Exam
Examinations The exams will be given on the dates shown above. Both 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
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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 below. You will take the midterm exam during class time on the
indicated date. You do not need to come to class on this day. Log in to Connect at the beginning of class
and take the exam. The exam will time out at the end of class. You may use any resources you want
except other people during the exam.
EXAM CHAPTERS
Midterm Exam 2, 3, 4, 5, 6, 7
Final Exam 8, 9, 10 (including 15.1), 12,13
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, 70% for a C, and 60% for a D. 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!
Midterm Exam Grade 30%
Final Exam Grade 30%
Connect Assignments 20%
LearnSmart Assignments 10%
Days in the Office 10%
Blackboard Web Site You will use Blackboard to access your Connect assignments, receive announcements, distribute course
materials, and record grades. Access Blackboard at https://blackboard.stonybrook.edu/. For help, visit
http://it.stonybrook.edu/services/blackboard.
Stony Brook University Syllabus Statements Americans with Disabilities Act: If you have a physical, psychological, medical or learning disability that
may impact your course work, please contact Disability Support Services, ECC (Educational
Communications Center) Building, Room 128, (631) 632-6748. They will determine with you what
accommodations, if any, are necessary and appropriate. All information and documentation is
confidential. http://studentaffairs.stonybrook.edu/dss/index.shtml.
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.
Faculty are required to report any suspected instances of academic dishonesty to the Academic
Judiciary. For more comprehensive information on academic integrity, including categories of academic
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dishonesty please refer to the academic judiciary website at
http://www.stonybrook.edu/commcms/academic_integrity/index.html
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 University Community
Standards any disruptive behavior that interrupts their ability to teach, compromises the safety of the
learning environment, or inhibits students' ability to learn. Further information about most academic
matters can be found in the Undergraduate Bulletin, the Undergraduate Class Schedule, and the Faculty-
Employee Handbook. 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 web site: http://www.ehs.sunysb.edu and search Fire Safety and Evacuation and
Disabilities.
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.