Fall Semester Module B

Fall Semester Module B

Advanced Decision Models

Professor: Amy Puelz, Clinical Professor
http://www.smu.edu/Cox/Departments/FacultyDirectory/PuelzAmy

Textbook: Practical Management Science, Fourth edition by Winston and Albright.

Software: Excel and Palisade’s Decision Tool Suite software.

Contents: Goal Programming, Non-linear Model, Non-Smooth Model, VBA in Excel, stochastic optimization and Logistic Regression models.

Tips: This is the advanced version of the Decision Model in Module A. Goal programming may be the most difficult part in this course. Follow every step that the Professor presents in class and you will have no problem in success in the course.

Applied Predictive Analytics II

Professor: Michael Braun, Associate Professor

http://www.smu.edu/Cox/Departments/FacultyDirectory/BraunMichael

Textbook: No required.

Software: R.

Contents: Construct probability models of customer activity, and estimate model parameters using the method of maximum likelihood; Choose among model specifications, using quantitative and qualitative criteria; Apply Bayesian methods for inference, classification and forecasting; Model integrated customer purchase and retention processes, and how to use those models to estimate expected customer lifetime value.

Tips: This may be the most difficult course I have taken in this program so far. Each class has a lot of contents to cover and master. The theory part is on probability models and Bayesian methods. The context is marketing related, such as new product adoption, sales forecasts and customer lifetime value.  The application is R based and it involves a lot of programming work. The homework is also difficult and it usually go a little beyond class materials. The professor wants you to discover something by yourself in homework. Anyway, this is a hard course but very state-of-the-art. There is no textbook, but you rely on the Slides and several recently published academic articles.

Database Design for Business Applications

Professor: Stewart Rogers, Adjunct Professor

http://www.smu.edu/Cox/Departments/FacultyDirectory/RogersStewart

Textbook: Concepts of Database Management, 8^th Edition, Philip Pratt and Mary Last.

Software: Access and Excel.

Contents: Fundamentals of relational database design, Data Management (Table design, Input and Output, Client/Server, Administration Issues), How to talk to IT intelligently (Database Jargon, current capabilities), Excel Data Capabilities (Data Functions, Table Manipulation, In Memory DB’s).

Tips: It is an introduction level course for database. It is not hard and the concept is the basic for advanced database course. You will learn basic SQL, which is very useful.

Revenue Management

Professor: John Semple, Charles Wyly Professor of MIS

http://www.smu.edu/Cox/Departments/FacultyDirectory/SempleJohn

Textbook: Pricing and Revenue Optimization, by Robert L Phillips.

Software: Excel.

Contents: optimal pricing model, Little Woods’ two class model, n-class dynamic model, network capacity control, choice model, overbooking management.

Tips: This class is mainly a modelling class. You will use Excel to build up those models. The homework is very interesting and challenging at the same time. So you will learn both in class and in doing homework.

Fall Semester Module A

Fall Semester Module A

Applied Predictive Analytics I
Professor: Richard Briesch, Professor of Marketing, Corrigan Research Professor, Research Fellow, National Center for Arts Research. http://www.smu.edu/Cox/Departments/FacultyDirectory/BrieschRichard
Textbook: Econometric Analysis (7th Edition) by Greene; The Little SAS Book: A Primer, Fifth Edition by Delwiche and Slaughter.
Software: SAS.
Contents: Endogeneity/Simultaneous Equations, Sample Selection Correction/Tobit, Information Criteria/Model selection, Likelihoods.
Tips: This is a basically Econometrics class with SAS application. You’d better to be familiar with basic SAS coding skills, because the Professor won’t go through every detail in SAS coding, especially the basic data manipulation skills. For the theory part, the textbook is too heavy and mathematical for the class contents. So just use it as a reference book.

Business Metrics
Professor: Jacquelyn Thomas, Associate Professor of Marketing, Frank and Susan Dunlevy Faculty Fellow
http://www.smu.edu/Cox/Departments/FacultyDirectory/ThomasJacquelyn
Textbook: Marketing Metrics, Paul Farris, Neil Bendle, Philip Pfeifer, and David Reibstein
Software: Excel
Contents: Through the use of problem sets and business cases, the course focuses on the calculation of financial, marketing and operational metrics and demonstrate contexts in which managers would rely upon such metrics for decision-making.
Tips: You have to remember a lot of calculations for different kind of metrics. It is not that hard, but keep to the slides and the book.

Introduction to Business Process Analytics
Professor: Ulrike Schultze, Associate Professor 2012-2013 Dunlevy
http://www.smu.edu/Cox/Departments/FacultyDirectory/SchultzeUlrike
Textbook: No required.
Software: No.
Contents: In this class, students will learn the conceptual frameworks, tools and skills needed to develop a blueprint for analytics. This entails successfully analyzing the high-level requirements for business analytics, prioritizing and outlining solutions, proposing business process improvements to generate the requisite data, and making the business case.
Tips: This is a totally case-based class, without any programming skills requirement. But the course load will be very heavy and you have to read a lot of case before class and discuss in class. The conceptual framework is very important. Participation means a lot in this course.

Decision Models
Professor: Amy Puelz, Clinical Professor
http://www.smu.edu/Cox/Departments/FacultyDirectory/PuelzAmy
Textbook: Practical Management Science, Fourth edition by Winston and Albright.
Software: Excel and Palisade’s Decision Tool Suite software.
Contents: linear, integer, binary and nonlinear optimization models in Excel; decision trees for business decisions given uncertainty, simulation models for business decision given uncertainty.
Tips: It basically teaches operation research models with Excel applications. The Professor keeps a perfect pace of presenting how to build decision models in Excel at class. You will learn the most in class. Follow every examples in class and finish the corresponding homework, and you will get a good result.

The "Managing Your Career" Course

Over the course of our first semester, everyone in the program was enrolled in a course called "Managing Your Career". In this course, we got to hear great career and job search advice from both Hettie Tabor, our program director and Scott Hensley, who is in charge of the Cox career center. They gave great interview tips and let us ask tons of questions about everything job-related. In addition, we also had presentations from 2 different companies every week. A lot of these companies had either hired students from the program the year before or expressed an interest in the students in the current program. This was a great chance to network, and it also let us see some of the options for careers after graduation.

Some of the companies that came were:

• State Farm
• Accenture
• Texas Health Resources
• Google
• PwC
• Hitachi
• American Airlines

SMU has a really great alumni network, which can really be helpful in the job search.

Summer Bootcamps

Since the MSBA program mostly focuses on quantitative analysis skills and students come from a variety of academic backgrounds, SMU provides a series of required Summer Bootcamps for students to refresh basic statistics and programming skills. In 2015, the Summer Bootcamps were held in August and lasted for 3 weeks. It consists of 3 parts: Statistics Bootcamp, R Bootcamp and Excel Bootcamp.

Statistics Bootcamp

Professor: Richard Briesch, Professor of Marketing, Corrigan Research Professor, Research Fellow, National Center for Arts Research.

http://www.smu.edu/Cox/Departments/FacultyDirectory/BrieschRichard

Textbook: None required.

Software: Excel.

Contents: The first half of this course is devoted to learning about basic probability distributions, estimation, and hypothesis testing; the second half is devoted to simple and multiple regression analysis and model building and diagnoses.

Tips: It is altogether 6 classes for this statistics bootcamp. The professor cannot teach every detail on statistics in such a short amount of time, so it is better for students to have a good sense of statistics beforehand. The PPT slides are very concise in contents so that you may need to search for more detailed explanations in your college textbooks or on the internet. The professor will present each statistics concept using examples in Excel, so that you should have basic Excel skills.  The professor may teach very fast for some time, so you should feel free to ask questions in class and review class contents carefully after class by yourself. Remember, this is just a statistics bootcamp, not a semester-long, mathematics-based statistics course. 

R Bootcamp

Professor: Young Park.

Textbook: None required.

Software: R.

Contents: There are 3 classes for this R Bootcamp. It covers basic R syntax, such as Vectors, Matrices, Data Frames, Arrays, Vector and Matrix Operations, Random Sampling and Subscripting, Function, Loops, Reading and Writing Data, Data Manipulation by dplyr, Conversion by tidyr, and Creating Graphics by ggplot2.

Tips: If R is a totally new programming language for you, just keep practicing. The more you practice, the more you will learn by yourself. Do not just copy and paste, try to write those codes by yourself.

Excel Bootcamp

Professor: Stewart Rogers, Adjunct Professor.

http://www.smu.edu/Cox/Departments/FacultyDirectory/RogersStewart

Textbook: None required.

Software: Excel.

Contents: It is only 1 class for this Intermediate/Advanced Excel session. It covers Excel Basics (functions, help, and formula), Managing Data (importing, sorting, filtering, summarizing, pivot tables), Financial Modeling, and Custom Applications with Excel (OLAP, Data Mart).

Tips: Excel is the basis for every business analysis task, so make sure you master it well. You will need the Analysis ToolPack and the Solver ToolPak installed on your computer before class. Sometimes, the Professor presents some Excel operations very quickly, so be sure to follow him, otherwise you will be lost.