An Analysis of the Integration of Decision-Making Modeling with Statistical/Quantitative Background for Master's Level Analytical Courses

Abstract

The purpose of this thesis is to integrate statistical/quantitative background material with Master's level analytical courses. This thesis first identifies the requirements for management education in terms of AACSB and NASPAA standards. Then, based on a comparative analysis of the country's top master's of business administration (MBA) programs and Naval Postgraduate School's current Systems Management curricula, and a survey conducted among SM faculty members, it integrates the decision-making modeling with statistical/quantitative background material for master's level analytical courses. The structure of the MS in Management at NPS, while satisfying the requirements of both AACSB and NASPAA is similar to the top management schools' MBA programs in the United States. However, top management schools' statistical/quantitative course sequence generally has four courses, providing more statistic al/quantitative background material than those three of NPS. Additionally, the contents of these three courses are not offered in adequate depth and some topics are duplicated. The new sequence and the contents of these courses are proposed based on a survey conducted among SM faculty members.

Open PDF

Document Details

Document Type
Technical Report
Publication Date
Jun 01, 2000
Accession Number
ADA380828

Entities

People

  • Kadir Ozyurek
  • Murat Ozdemir

Organizations

  • Naval Postgraduate School

Tags

Communities of Interest

  • Human Systems

DTIC Thesaurus Topics

  • Business Administration
  • Commerce
  • Computational Science
  • Computer Programs
  • Data Analysis
  • Data Mining
  • Data Science
  • Information Science
  • Integer Programming
  • Management Personnel
  • Operating Systems
  • Operations Management
  • Organizational Structure
  • Regression Analysis
  • Students
  • Surveys
  • Systems Management

Readers

  • Aerospace Research.
  • Agent-Based Social Robotics and Mobile-Assisted Learning in Virtual Environments.
  • STEM Education