Business Analytics
Fall 2019

Moodle, Course Calendar
Syllabus quick links: Objectives, Structure, Textbook, Technology, Grading Criteria, Policies

 

Course Information

Days & Times: In-class: Not applicable for this semester.
Online: The course starts on Monday, August 26. There are no meeting times. This course is asynchronous.
Location: In-class: Not applicable for this semester.
Online: There is no location. You can work from anywhere that is convenient to you.
Credits: 3 hours
Prerequisites: None
Instructor: Dr. Rick Jerz
Contact Information: Email:Rick@rjerz.com or richard-jerz@uiowa.edu
Phone: (563) 447-0180 (voice mail)
Office Hours: I can always be reached by email or from discussion posts.

MBA Program Goals

The administrative home of this course is the Tippie MBA Program, which governs academic matters relating to the course. The Tippie MBA program has learning goals that drive decisions about curriculum and assignments within courses. These goals are: 1) grow human capital through attaining relevant business knowledge and skills; 2) generate integrative solutions to business problems that impact organizations 3) develop global business perspectives; 4) understand and demonstrate the importance of acting with integrity and social responsibility and 5) demonstrate the ability to be effective team members and leaders in a complex and diverse world.

The primary emphases on this course are goal #1, the attainment of relevant business knowledge and skills; goal #2, to integrate these skills and knowledge to solve business problems that impact organizations; and goal #5, to be an effective team member by adding a quantitative, and objective component to team decisions. Goal # 3, that quantitative analysis has global impact, and goal #4, that quantitative analysis is an objective methodology that supports integrity and social responsibility, are both present in this course.

Catalog Description

Introduction to analytical techniques for making business decisions; utilizing Excel to apply descriptive and predictive analytical tools to solve practical business problems using real-world data; dealing with uncertainty in decision making; formal probability concepts and statistical methods for describing variability (decision trees, random variables, hypothesis testing); application of techniques (linear regression, Monte Carlo simulation, linear optimization) to model, explain, and predict for operational, tactical, and strategic decisions.

Course Objectives

This course introduces techniques of quantitative modeling, statistical analysis, and structured decision making that are useful for professionals and managers. A unifying element of the course is the use of Microsoft Excel to perform various kinds of analysis in a spreadsheet environment. The primary objectives of the course are:

  1. Categorize data to construct appropriate tables and charts, and interpret data using Excel.
  2. Investigate decision alternatives in the face of uncertainty. To use decision tree diagrams.
  3. Define probability for an event and calculate probabilities and outcomes using rules of addition, multiplication, and counting.
  4. Distinguish different kinds of probability distributions. To calculate probabilities of events using Excel.
  5. Calculate probabilities and p-values to evaluate hypotheses about sample data to support decisions using Excel.
  6. Calculate relationships between two or more sets of data using regression analysis in Excel.
  7. Determine the best decision using optimization techniques and models in Excel.
  8. Use simulation modeling techniques in Excel to evaluate uncertain business environments.

You will see these objectives, and their number (as CO1, CO2, etc.) referenced in each weekly module and in the Course Calendar.

Course Structure

This course is 11-weeks, and depending upon the semester, offered in both in-class as a hybrid format, and online sessions. The course content and assignments are the same. The only difference is that in-class students are in a physical classroom. This syllabus serves both formats.

In this course, I use my Learning Management System (LMS) called Moodle, instead of the university's ICON LMS. Moodle, an industry-leading open-source LMS, offers features not yet available in ICON. Moodle supports my quality standards. I do have a link in ICON to Moodle, for the convenience of students who might be in Moodle, but you can get to Moodle without going through the university website. There is no cost for Moodle.

One week before each weekly module (a module is a collection of topics,) as shown on the Course Calendar web page, I turn on that module, notifying you by email that it is available. You will see it in Moodle. By turning on a module one week early, and then making its due date one week after a module is covered, my method provides you about two weeks to do every assignment, except for exams.

Each weekly module in Moodle begins with a Resources and Assignments web page, that provides a somewhat step-by-step listing of what you need to do. On this web page, you will also have access to many support materials, such as my PowerPoints, supplemental readings (when appropriate,) my Excel models, and most importantly, my lecture videos. My lecture videos, a significant component of this course that you will quickly come to appreciate, are broken down into "conceptual understanding" and "Excel problem-solving" episodes. Following the link to Resources and Assignments, on Moodle, you access assignments and self-assessments.

For in-class students, watch my posted lecture videos before class and begin the readings. In class, I will briefly review what I covered in my lecture videos, and then we will work through more problems and exercises to "reinforce" your learning, and I will address your questions. Typically the day of class, I post information about what we will be doing that evening. Because my videos are an essential instructional component and take your time to watch before class, our classes will end about an hour early to "compensate" you for this time. Within a day after class, I will provide you a "reinforcement video" that reviews what we did in class. This method will allow us to use our time together productively, give us ample time to address questions in class, and maximize your learning. Classroom sessions are recorded and placed into the ICON course, but quite honestly, most students prefer watching my reinforcement videos because they are edited, shorter, and clearer. A break of about 10 minutes will be provided at the mid-point of class.

For online students, you should watch my lecture videos and do the readings, then attempt the assignments. Then, about a day after the module date, as shown on the Course Calendar web page, I make a "reinforcement" video and a reinforcement web page available to you. This "reinforcement" is exactly what I do in the physical classroom; it reviews what we have just learned and provides more problem-solving examples. You should watch these videos and follow along with my instruction. This online course does not use weekly webinars because this course is asynchronous.

Every weekly module, near the bottom of each module in Moodle, has a discussion forum for students to post questions, or provide comments or observations. Posting in these forums is optional and meant to be helpful to all students, and everyone will see these questions, comments, and observations.

I have carefully designed my videos to improve your study time. I deliver these videos asynchronously, meaning that you do not have to be behind your computer at any specified time to hear my lectures. You can study when you are most productive! These videos are provided in "mp4" format and can be played directly from most browsers, they can be download to your computer or smartphone, and they are available as podcasts. See my "Videos, Podcasts, iTunes" webpage for more information about the variety of ways to watch my videos. I think that you will enjoy my lecture videos, typically 15 to 25 minutes long.

Through my use of a variety of electronic technologies and a very organized easy-to-use LMS, Moodle, you will see that I am very dedicated to making your learning productive and efficient.  You can be successful in this course if you study the materials, watch the videos (often more than once), do all assignments on time, and ask questions whenever something is not understood.

The "Course Calendar" web page shows the topics and their dates for this course.

This course is in English and times are CST.

About a week before the class begins, I will send you a "Welcome" email that provides details and course access information, including how to access Moodle and a small pre-course assignment.  I send this email to your email addresses on record with the Registrar, so watch for this email and remember that you may need to check your “junk” mailbox.

Required Textbook

"Statistical Techniques in Business & Economics," 17th Ed., Douglas A. Lind, William G. Marchal, and Samuel A. Wathen, McGraw Hill Irwin, 2018. ISBN 978-1259666360. This textbook can be purchased from the UIowa Bookstore. The 13th, 14th, 15th, or 16th editions are permitted but must be purchased elsewhere. Note: no special DVDs or software keys are required, just the textbook.

I recommend getting the version that best suits your budget and reading style. This textbook is a good reference textbook, and it also provides many solved problems.

See FAQ - How to keep the textbook cost affordable. Earlier editions of this textbook are often priced under $20.

Supplemental Readings. I will provide several supplemental readings for a few of the topics, when needed.

Course Technology

This course assumes that the student has some basic computer skills and understands how to use products such as email, browsers, word processing, and spreadsheets. There may be times where you will need help from Information Technology Services (ITS,) which is the university's computer support department.

Computer and Internet: A PC or Macintosh computer is required along with Internet access, upload and download speeds of at least 2 Mbps. I do want to point out that this course designed for either PCs or Macs, but "officially," since this course is in the Business Analytics department, the department has this policy stating that students should have a PC. In this policy, Mac users will see alternatives, free and low cost, for running PC-based software on the Mac. (I own a Mac, and use VMWare when I need a PC.)

For in-class sections, many past students have found it extremely helpful to bring laptops to class, especially for following along with the Excel techniques demonstrated in class. The classroom has wireless Internet.

For online sections, students are expected to have their own computer or use a university lab computer.

Course Software: This course requires the following application software: Excel (2010, 2011, 2013/2016/2019/365). It is recommended to have Excel 365 since most of my videos will be using this version of Excel. UIowa students are eligible to get MS Office 365 for free from Microsoft.

Browser requirements: You will need a modern browser that is up to date (Internet Explorer 11, Edge, Firefox, Safari, Chrome X, or equivalent.)

Acrobat, iTunes (or other feed aggregator, such as Podcast Republic) Video Player, and Screen Capture:

The latest version of Adobe Acrobat Reader must be installed on your computer to access course materials posted as PDFs. 

The posted videos play within most browsers, and they can also be downloaded and played with Windows Media Player or the QuickTime player, or you can use a more powerful video player such as VLC (PC or Mac) or the Elmedia player (Mac.) The videos are standard mp4 videos.

iTunes or a different "feed aggregator," such as Podcast Republic (for Androids), is optional but provides another alternative method to access videos.

I also recommend knowing how to do "screen captures," for those times when you want to show me a problem that you are having with your computer or software. See my FAQ webpage for help with screen capture software.

University Computer Lab Computers: Students can use the University labs' computers, which meet these course requirements, and are available for those students who are on-campus. Students can also use the public computers that are available in the building.

Mobile Devices: Most of this course's materials are designed to be easily viewed from most modern tablets, smartphones, and multimedia players. Mobile devices are handy for playing videos and accessing course materials "on the go." Moodle appears just fine from most smartphone's browsers, and there is an optional Moodle Mobile App, if desired. (I always work from my smartphone's browser.)

Clickers: For in-class sections, clickers will be used to improve participation. You do not need to purchase clickers. Clickers will be provided at no cost.

Pre-Course Assignment: A pre-course assignment (see Course Calendar) has been provided to make sure that all of these course requirements are working well before the start of the semester, and to introduce you to the course and to Moodle. This pre-course assignment is also explained in the "Course Introduction" video.

Need Technical or University Support? Any questions about the course materials and Moodle should be directed to the professor.  The professor’s FAQ webpage might sometimes help. Questions about The University of Iowa specific items, such as your UIowa email, UIowa computers, etc., should be directed to ITS, its-helpdesk@uiowa.edu, 319-384-HELP (4357). General university academic support and resources are found on the university's Helping Students Find their Way web page.

Accessibility: You will find this course designed with accessibility in mind, including students with our without special needs. Here is additional information about accessibility of products that might be used in this course.
- Moodle's Accessibility Statement
- iTunes (Apple's) Accessibility Values
- Microsoft Office Accessibility
- TreePlan: TreePlan is a VBA add-in for Microsoft Excel and uses accessibility features provided by Microsoft's standards.
- Tableau Accessibility

Grading Criteria

Students will be assessed based on their performance in the following items:

Weekly Self-Assessments and Assignments: 50%
First Exam: 25%
Second Exam: 25%

Your Moodle gradebook will show you both points and percentages for every graded item.

Final grades will be awarded based on the following ranges:

>= 99: A+ 94 - 99: A 90 - 94: A-
87 - 90: B+ 83 - 87: B 80 - 83: B-
77 - 80: C+ 73 - 77: C 70 - 73: C-
67 - 70: D+ 63 - 67: D 60 - 63: D-
below 60: F    

The MBA Committee recommends that approximately half the grades be in the "A" category, and approximately half in the "B" category. The C, D, and F grades are used as needed. However, this course has an exception and uses an absolute grading scale.

Attendance & Participation: For in-class sections, I highly recommend attending the first night to understand the course and its hybrid nature and flexibility. After the first night, students can decide if they want to be in class or work electronically. For online sections, this course is asynchronous and does not have "attendance."

Timing for Assignments: All assignments have due dates (Tuesdays), that show in Moodle's "Calendar" and in Moodle's "Upcoming Events." When the due date expires, the assignment is over. I encourage you to begin assignments early. Also, I try my hardest to help everyone who seeks my help prior to due dates, and usually in less than two days, but the probability of getting my help goes down dramatically as the due date approaches (i.e., if you ask me a question two hours before an assignment is due, I may not respond.)

Self-Assessments (Concepts & Problems): Every week, you must complete self-assessments to see how well you understand the assigned readings, and more importantly, that you can solve business problems. These self-assessments are in Moodle, and they must be completed by the due date -- no exceptions. When you "submit" these self-assessments, they immediately graded. If you do not like your grade, you can redo your self-assessment unlimited times, and your highest grade is what counts. Since you can redo your homework, I encourage you to begin early and complete at least one attempt so that you hopefully will not end up with a zero. Questions about any of these self-assessment questions should be posted at the bottom of each module's forum, which other students or I can discuss, provide feedback, and respond.

Uploaded Assignments: There will be some topics where you will be expected to upload a file. I intend to grade these assignments and provide feedback within two days after their due dates.

Exams: There will be two exams, equally weighted and delivered electronically. You do not need to take these exams at the university testing center. Each exam will cover only the materials that we have covered in each half of the semester. These exams timed, 2-hours long, one attempt, but you will have a period of at least 24 hours (often more) to decide when to begin. Exams must be taken individually, and there will be severe consequences for those who do not follow this rule. The best way to make sure that you don't appear to be "cheating" is to make sure that no other student is in sight of you. Exams are open-book, open-notes, and you are encouraged to use Excel. Your exam grade will be posted immediately upon completion of the exam as the multiple-choice questions are self-grading. At my discretion, I can ask you to find an instructor or administrator from a university to proctor your exam.

Bonus Points: Occasionally, I provide bonus exercises, shown as "Bonus" in Moodle. Bonus exercises are always optional, and they are additional points within its own grade category. In the spirit of quality and continuous improvement, whenever you are the first student to identify an administrative error about any component of this course, you will receive one (1) bonus point. These bonus points can amount to up to 2% improvement to your overall grade.

Course Policies

Communications, Posting, and Email: I send an email each week when a topic is released, sent to the email address(s) you provided in the pre-course Student Survey. When you have a question, I prefer that you post your question in Moodle since your question, and my response often benefits other students. Moodle will email these posts to everyone using your Moodle profile's email address. However, if you have a more personal question, email it to me. I typically reply to posts and emails in less than two days. If you do not get a response from me within two days, try emailing me to both my private (Rick@rjerz.com) and university (Richard-Jerz@Uiowa.edu) email addressed, just in case your email is detected as spam.

Make Up Exams: Make up exams will only be given for extreme situations.

Late Work: Late work is not accepted.

Academic Integrity and Misconduct: It is my sincere hope that no student in this class submits work which is not his or her own. However, it seems prudent to clarify in advance the policy on cheating. If I determine that any assignment was not completed solely by the student whose identification number appears on the project, the student will receive a zero (0) for the assignment and may receive an "F" for the class. All incidents of cheating will be reported to the Associate Dean of the Tippie College of Business and the student may be placed on disciplinary probation for the remainder of his or her undergraduate work at the University of Iowa. In general, the decision of the Professor may be appealed to a Judicial Board, then to the appropriate Associate Dean. The Honor Code for the Tippie College of Business will determine the appropriate appeal process.

Classroom Etiquette (Netiquette): In emails, online discussions, assignments, and other interactions, a courteous tone, politeness, and professionalism tone is expected. Here are some tips on "Netiquette."

Rectifying Scores: During the semester, I will post all your scores in Moodle's gradebook for you to view. After you get your assignment or exam grade, you have a week to dispute your score. Beyond this period, I will not entertain any disputes.

Privacy Statements for software products that students might use in this course:
- The University of Iowa Online Privacy Statement
- The University of Iowa FERPA Guidelines. I keep your personal email addresses and phone numbers private. The data that Moodle collects is not shared with others as I honor FERPA guidelines.
- Moodle Data Privacy Statement: Moodle is a private Learning Management System. Keep your password private and do not share it with others. I am my Moodle's Privacy Officer.
- Microsoft Office Privacy Statement
- iTune (Apple's) Privacy Statement
- Tableau Privacy Statement

Collegiate Policy

Tippie Collegiate Policies and Guidelines

University Policies

Accommodations for Disabilities: UIowa Accommodations Policy.

Mental Health: UIowa Mental Health Policy.

Sexual Harassment: UIowa Sexual Harassment Policy.

Multicultural Holidays: UIowa Multicultural Holidays Policy.

Sustainability: UIowa Sustainability Policy.