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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

Thomas.Sexton@StonyBrook.edu

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.