Syllabus

MGMT 462 Managerial Analytics

Online

Spring 2024: January 8, 2024 - April 26, 2024

Instructor:      James Miller

E-mail:             jmiller@dom.edu

Cell phone :    847-530-0550

Class Location : Online

For the links in this document to work, read this document from this location.

The first part of the Syllabus contains general information that applies to all courses in the Brennan School of business. You can find content specfic to this course here

• Everyone enrolled in this course can meet the course goals given appropriate opportunities for learning and for demonstrating learning.  For this reason, the learning and assessment activities are designed to meet a variety of learning needs and styles.  Many features of the current course were developed in response to student suggestions.
• Learning is deepest, most encompassing, and most successful when a variety of perspectives are contributed and discussed.  For this reason, all perspectives and insights are welcome and valued, as long as they are presented thoughtfully, respectfully, and with sensitivity to the perspectives and experiences of others.

Texts (required):  

1. Business Analytics 3rd Edition by James R. Evans and Publisher Pearson. Save up to 80% by choosing the eTextbook option for ISBN: 9780135231715, 013523171X. The print version of this textbook is ISBN: 9780135231678, 0135231671.

Students in past classes have reported that there is an inexpensive version of the above text book at

2. Computational and Inferential Thinking (no charge)

The Foundations of Data Science

By Ani Adhikari and John DeNero

The contents of this book are licensed for free consumption under the following license:
Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0).

The book is available at https://www.inferentialthinking.com/chapters/intro.html

The book is also available in PDF form in Canvas

We will use Microsoft Office software, especially Excel, and Access and the Anaconda distribution of Python.  We will also use Microsoft SQL Server which you should not attempt to install on your own machine. All software is available in the Dominican Tech Center. The easiest way to use all the software needed in this course is to connect to the Dominican Server acats2019.dom.edu. Instructions to do this will be given in the course. You can connect from home or from Dominican.

Note: Chromebook computers will not work for many assignments in this course. See this document for a list of assignments that will or may not work with Chromebooks.

Course Description: 

Firms can gain a competitive advantage by using data to make better decisions. Many different organizations, including businesses, governments, and non-profits, are now making significant investments in analytics. The objective of this course is to help you understand the field of analytics and be able to put analytics into a business / managerial environment. A secondary objective is to expose the student to basic concepts in Management Information Systems such as Database Management, Cloud Computing, and Big Data. The course will explore

1. How managers use analytics to formulate and solve business problems and to support managerial decision making.

2. The Role of Data to help you understand the basis of all analytics

3. Descriptive Analytics to help you understand what has happened

4. Predictive Analytics to help you understand trends and predict outcomes

5. Prescriptive Analytics to help you decide what action you should take

Cases and hands on exercises will be used.  Students will apply tools such as Microsoft Excel, Microsoft Access and SQL, and Python.  

Prerequisites:  (QUAN201 and MGMT301), and (CIS120 or exemption from CIS120)

Grading: (Percentages will be updated as soon as all assignments have been entered into Canvas)

Logistics:

You will need to use your Dominican e-mail address in this class. Please see the Computer Lab aides if you do not already have the required accounts. Use of Canvas is required.

All assignments are due at midnight Sunday night. If you have been "stuck" on an issue for more than 15 minutes, seek help. Please seek help form me.

If you have a reason why your assignment will be late, contact me before the due date. This is easy to do and it could save you the minimal late penalty. The late penalty is 1% per day if you don't ask for an extension ahead of time. So, for example, if your assignment is eight days late it will be mathematically impossible to get an "A" on that assignment.

Exam in Week 11:  The exam will cover all materials presented up to the exam date.  An emphasis will be placed on the class lectures, notes, handouts and the required reading.  If you must miss the exam, you must obtain approval before the exam date. The exam may be made up on a mutually agreeable schedule but make up dates generally are before the scheduled exam date.

Online work (Canvas): All work in this course will be submitted in Canvas (No paper!).

Schedule details: The schedule is subject to change. A detailed schedule by class week can be found in Canvas. A summary schedule appears later in this document.

Objectives: 

• Upon completion of this course, students should be able to:

• Use advanced features in Excel such as
  • Pivot Tables
  • Solver (linear programming)
  • Date and Text manipulation
• Use Python or other tools to analyze data and then draw conclusions from analysis.
• Analyze and explain the applicability of big data and data analytics within a particular business/managerial environment and explain the associated requirements and challenges.
• Assess the ethical, legal, and privacy issues associated with collection and use of data.
• Demonstrate and effective use and an understanding of the applicability of various systems and tools for managing data including relational databases, spreadsheets, and analytical engines.