AM4 MICROSOFT EXCEL: BASIC SKILLS FOR EFFICIENCY AND MODELING

Sunday, October 24, 2010: 9:00 AM
Huron Room (Sheraton Centre Toronto Hotel)
Course Type: Half Day
Course Level: Beginner

Format Requirements: This is a “hands-on” course. Participants will work through structured examples using their own computers. Data sets and files needed for the course will be available for download prior to the conference.

Background: Microsoft Excel has become the tool of choice for quantitative analysis in MBA programs because of its power, flexibility, ease of use, transparency, and widespread availability. However, it has not been fully exploited by the decision analysis community. Many decision problems can be analyzed in Excel. Excel can be used to organize and model input parameters, build small or large models, analyze and graphically display results, and perform sensitivity analysis. Excel is a ubiquitous platform for developing simple or complicated models. Additionally, several common decision analysis software tools integrate with Excel. Improved proficiency with Excel can save time for almost anyone. This is the first of two courses on Excel modeling. In this course we introduce basic Excel tools and functions to enable participants to gain comfort with the program and the start building useful models.

Description and Objectives: Course Description and Objectives:

The goals of this short course are to:

1. Introduce common keyboard shortcuts, functions, and graphing options that will improve efficiency.
2. Present advanced functions that will enable participants to analyze large datasets, build decision-analytic and Markov models in Excel.
3. Conduct deterministic sensitivity analysis in Excel.

Participants will acquire the following skills from this short course:

1. General principles of building good Excel models.
2. Using simple functions to calculate the sum, product, minimum, maximum, median, average and weighted average of a set of values. Finding built-in functions for other tasks.
3. Absolute vs. relative referencing.
4. Database sorting and database lookup functions including lookup, vlookup, hlookup, index, offset and match.
5. Matrix multiplication in a spreadsheet.
6. Constructing decision trees and Markov models in Excel.
7. Conducting one-way, two-way and threshold sensitivity analysis in Excel using Data Tables and Goalseek.
Course Director:
Gregory S. Zaric, PhD
Course Faculty:
Lauren E. Cipriano, BSc, BA, PhD Candidate , Eva Enns, MS, PhD Candidate and David W. Hutton, PhD