|
|
|
|
| Spring 2010 |
|
| QTM7571 |
BUSINESS INTEL & APPLIED DATA MINING |
3.00 credits |
| |
QTM7571 Business Intelligence and Applied Data Mining
(formerly Applied Data Mining)
This course will examine the methods and challenges faced in extracting meaningful information from large databases and the growing number of applications for these techniques. Students will learn new techniques for data gathering and data analysis including neural nets, correlative webs, ruleset development using classification nodes, and cluster analysis . These analysis techniques will be used to understand how to turn the information into a knowledge base, to synthesize enormous amounts of data, and to identify new or surprising patterns which can't be found using classical statistical analysis. We will analyze databases from marketing, finance, accounting (auditing) as well as genomic and on-line clickstreams data and online surveys.
Instructional modes (e.g. lecture, laboratory, seminar, internship, film, etc.): The course will include hybrid delivery where some classes will take place online and others will be face-to-face. The course will utilize a hands-on approach to understanding the methods of data mining, as well as understanding its links to Statistics and Information Systems and its Applications in business, finance, economics, physical and social science. Lectures, case presentations, computer labs and guest speakers will be used. Students will learn Clementine, a widely used data mining software package.
Prerequisite: QTM7010 or QTM8400 or completion of the One Year, Two Year or Fast Track modules
|
| QTM8200 |
APPLIED DECISION MODELS |
2.00 credits |
| |
QTM 8200
Applied Decision Models
This is a core class for the Evening MBA Program only. Students must complete or have advanced standing credit or pass a waiver exam in QTM7010, Statistics, in order to take this class.
The focus of this class is on developing decision support models and using these tools to enhance decision making. It is an application-oriented introduction to the modeling techniques used to structure the way we think about managerial decision situations. Methodologies considered are decision analysis, simulation, optimization, and sensitivity analysis. Spreadsheet models are developed with applications to finance, operations management, logistics, and resource allocation.
Prerequisite: QTM7010
|
| QTM8400 |
DATA & DECISION MODELING |
4.00 credits |
| |
No Saturday Class Requirement
QTM8400
Data and Decision Modeling
4 Credits
This course is an introduction to basic quantitative tools that enable managers to analyze data and make informed decisions. Topics include descriptive analysis of survey data, introductory probability, decision analysis, sampling and sampling distributions, hypothesis testing, simple and multiple regression, simulation, and optimization. Case studies drawn from marketing, finance, and operations management, illustrate the use of these quantitative tools in applied context. The course requires use of spreadsheets and statistical, optimization, and simulation software.
This course is equivalent to QTM7010 - Statistics and QTM8200 - Applied Decision Models
Prerequisite: NONE
|
|
| Fall 2009 |
|
| MIS7580 |
INDEPENDENT RESEARCH |
3.00 credits |
| |
XXX7580
Independent Research
******Independent research is available for all academic divisions.Registration is manual for students through Graduate Programs and Student Affairs******
Independent Research provides an opportunity to conduct in-depth research in areas of a student's own specific interest. Students may undertake Independent Research for academic credit with the approval of a student-selected faculty advisor, the appropriate division chair, and Graduate Programs and Student Affairs. Please note that a student is responsible for recruiting a faculty advisor through the student's own initiative and obtain the advisor's prior consent/commitment before applying for an independent research project.
Authorization for such a project requires submission of a formal proposal written in accordance with standards set forth by the Graduate School. The research project normally carries 1.5 or 3 credits.
For more information and a proposal outline please visit: www.babson.edu/grad/gpsa
|
| QTM7575 |
FINANCIAL MODELING |
3.00 credits |
| |
QTM7575
Financial Modeling using Simulation and Optimization
The focus of this course is on developing spreadsheet models for a wide variety of financial concepts including, but not limited to portfolio optimization, option pricing, asset allocation, value at risk, asset prices, etc. Students will gain familiarity with the financial instruments through the construction of the models, and will gain greater insights by analyzing and solving the models. Simulation and optimization are used extensively to analyze the models. Particular attention is paid to modeling uncertainty via random variables and the mathematics of stochastic variables.
Prerequisites: QTM8400 or (QTM7010 and QTM7020) or completion of the One Year, Two Year or Fast Track modules
|
| QTM8400 |
DATA & DECISION MODELING |
4.00 credits |
| |
Saturday Meeting Date: December 5th
QTM8400
Data and Decision Modeling
4 Credits
This course is an introduction to basic quantitative tools that enable managers to analyze data and make informed decisions. Topics include descriptive analysis of survey data, introductory probability, decision analysis, sampling and sampling distributions, hypothesis testing, simple and multiple regression, simulation, and optimization. Case studies drawn from marketing, finance, and operations management, illustrate the use of these quantitative tools in applied context. The course requires use of spreadsheets and statistical, optimization, and simulation software.
This course is equivalent to QTM7010 - Statistics and QTM8200 - Applied Decision Models
Prerequisite: NONE
|
|
| Summer II 2009 |
|
| MIS7580 |
INDEPENDENT RESEARCH |
3.00 credits |
| |
XXX7580
Independent Research
******Independent research is available for all academic divisions.Registration is manual for students through Graduate Programs and Student Affairs******
Independent Research provides an opportunity to conduct in-depth research in areas of a student's own specific interest. Students may undertake Independent Research for academic credit with the approval of a student-selected faculty advisor, the appropriate division chair, and Graduate Programs and Student Affairs. Please note that a student is responsible for recruiting a faculty advisor through the student's own initiative and obtain the advisor's prior consent/commitment before applying for an independent research project.
Authorization for such a project requires submission of a formal proposal written in accordance with standards set forth by the Graduate School. The research project normally carries 1.5 or 3 credits.
For more information and a proposal outline please visit: www.babson.edu/grad/gpsa
|
| QTM7580 |
INDEPENDENT RESEARCH |
3.00 credits |
| |
XXX7580
Independent Research
******Independent research is available for all academic divisions.Registration is manual for students through Graduate Programs and Student Affairs******
Independent Research provides an opportunity to conduct in-depth research in areas of a student's own specific interest. Students may undertake Independent Research for academic credit with the approval of a student-selected faculty advisor, the appropriate division chair, and Graduate Programs and Student Affairs. Please note that a student is responsible for recruiting a faculty advisor through the student's own initiative and obtain the advisor's prior consent/commitment before applying for an independent research project.
Authorization for such a project requires submission of a formal proposal written in accordance with standards set forth by the Graduate School. The research project normally carries 1.5 or 3 credits.
For more information and a proposal outline please visit: www.babson.edu/grad/gpsa
|
|
| Summer I 2009 |
|
| QTM8400 |
DATA & DECISION MODELING |
4.00 credits |
| |
Saturday Meeting Date(s) There will be no Saturday Meeting Date for this course.
QTM8400
Data and Decision Modeling
4 Credits
This course is an introduction to basic quantitative tools that enable managers to analyze data and make informed decisions. Topics include descriptive analysis of survey data, introductory probability, decision analysis, sampling and sampling distributions, hypothesis testing, simple and multiple regression, simulation, and optimization. Case studies drawn from marketing, finance, and operations management, illustrate the use of these quantitative tools in applied context. The course requires use of spreadsheets and statistical, optimization, and simulation software.
This course is equivalent to QTM7010 - Statistics and QTM8200 - Applied Decision Models
Prerequisite: NONE
|
| QTM9501 |
BUSINESS FORECASTING |
1.50 credits |
| |
Meeting Dates and Times: Friday May 29th (8:30 - 3:30), Saturday May 30th (8:30 - 3:30), and Friday June 12 (8:30 - 12:30)
SUMMER I 2009
QTM9501: BUSINESS FORECASTING
Credits: 1.5
Registering for QTM9501: Registration for Intensive Electives will take place through online course registration. Students will be notified of the Summer 2009 registration dates via their Babson email account. The last day to add this course is Friday, May 22nd (4:30PM deadline). Please see the drop deadline below. If a space becomes available in the course after the regular Summer I 2009 add/drop deadline (Wednesday, May 20th) but before the course specific add deadline, students must email intensiveelectives@babson.edu to register for it. These emails will be processed on a first-come-first-serve basis. We will not retain emails for future consideration.
Professor: Norean Sharpe
Time Conflicts: Students are responsible to check the meeting dates for all Intensive Electives. If a student is registered for Intensive Electives that have conflicting dates and times, the Registrar's Office will drop one of the these courses.
Intensive Electives Limit: The maximum number of Intensive Electives a student may take while at Babson is 4. It is the student's responsibility to adhere to this policy. If the student exceeds this limit, we will drop that student from an Intensive Elective of our choosing.
Meeting Room: TBA
Dropping QTM9501: If online add/drop is closed, students can email intensiveelectives@babson.edu to drop this course. Students can drop this course so long as an email is sent to intensiveelectives@babson.edu before the end of the day (11:59PM) of the first class meeting. Students must email from their Babson email account.
Capacity: 36
Overview: If you have taken ECN7520, Economic & Financial Forecasting, you cannot take this course.
This course will introduce elementary time series models and discuss advanced forecasting methods in the context of real business data and decision-making situations. The objectives of the course are to provide experience in using time series data (e.g., sales, profits, stock prices, economic indicators, industry sector indicators) to explain the impact of various internal and external factors and predict future trends; to provide a framework for comparing alternative forecasting models for validity, accuracy, and feasibility; to enhance an appreciation for the limitations of forecasting models; to provide exposure and experience in using statistical software to develop forecasting models; and to develop skills at communicating statistical concepts, methods, results, and inferences effectively in a managerial context. Teamwork and professional presentation of analysis and recommendations will be required during this course.
Prerequisite: QTM8400 or (QTM7010 and QTM7020 or QTM7010 and QTM8200) or completion of the One Year, Two Year or Fast Track modules
*THERE IS PRE-WORK FOR THIS COURSE*
|
|
|
