Course

Course Summary
Credit Type:
Course
ACE ID:
DAU-0336
Organization's ID:
BCE 2000V
Organization:
Defense Acquisition University
Location:
Online
Length:
8 days
Dates Offered:
Credit Recommendation & Competencies
Level Credits (SH) Subject
Upper-Division Baccalaureate 3 applied statistics
Description

Objective:

The objective of the BCE 2000V, Intermediate Cost Estimating course is to pick up from the fundamentals courses with an emphasis on the application of techniques, methodologies and analysis used in Department of Defense (DoD) cost estimating throughout the life cycle of a program. The course addresses a higher level of critical thinking used in cost estimating to support improved decision making and contribute to successful program outcomes. Computations in this course are done using spreadsheets and automated DoD cost estimating tools. Prior to registering for this course, individuals attending this course must have acquisition cost analyst experience serving in a program office, Program Executive Office (PEO), Service/Defense agency level, or supporting a program that reports to a Service Acquisition Executive (SAE). This course is designed for DoD professionals (with a minimum of six years of acquisition cost analyst experience prior to registration) with duties serving in one of the following areas: Program Office at the Service/Defense Agency level or supporting a program that reports to a Service Acquisition Executive.

Learning Outcomes:

  • Explain the activities involved with the various steps of the cost estimating process
  • Apply activities necessary for data collection
  • Describe and apply the activities performed during the Normalization Step of the cost estimating process
  • Describe the use of characteristics like shape, dispersion, and central tendency of a sample distribution
  • Apply advanced regression techniques to develop a Cost Estimating Relationship (CER)
  • Apply simple linear regression (SLR) analysis in developing cost estimating relationships
  • Create cost models that are easy to navigate, clear for others to understand, fast to update, and easy to summarize outputs
  • Apply the unit and cumulative average learning theories
  • Examine risk and uncertainty in a simulation model

General Topics:

  • Cost estimating process
  • Data collection
  • Data normalization
  • Data analysis
  • Regression
  • Model development
  • Learning Curve Theory
  • Cost, risk and uncertainty analysis
Instruction & Assessment

Instructional Strategies:

  • Audio Visual Materials
  • Case Studies
  • Classroom Exercise
  • Discussion
  • Learner Presentations
  • Lectures
  • Practical Exercises
  • Performance Rubrics (Checklists)

Methods of Assessment:

  • Case Studies
  • Performance Rubrics (Checklists)

Minimum Passing Score:

80%
Supplemental Materials