# MBA 511 Quantitative Methods - PowerPoint

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```					MBA 511: Quantitative Methods

June 29, 2009
Introductions

   Dr. Steve Mahar
    Office: CIS Building - 2021
    Phone (office): 962-3676
    Phone (home): 228-0562
    Email: mahars@uncw.edu
Today’s Class

   Introduction
   Syllabus highlights

   Descriptive Statistics & Data Analysis
Syllabus Highlights

   Books:
   Course Packet (and Jumpstart modules posted online)
   Harnett and Horrell
   Spreadsheet Modeling and Applications: Essentials of
Practical Management Science; 1st edition (w/software)
   Winston and Albright

   4 (group) homework assignments (50%)
   1 final exam (50%)
   3 hours to complete
   In class, Monday August 3
Syllabus: Miscellaneous

   Class files will be posted on my website

   http://www.csb.uncw.edu/people/mahars/mon/index.htm
Course Objectives

   To expose you to the use of analytical techniques and
tools in managerial decision-making

   To provide a broad understanding of how these tools
are used in various business areas

   To give you the skills to solve complex problems using
analytical techniques and tools on spreadsheets
Course Structure

Quantitative Methods

Descriptive Statistics
Harnett: Chapters 1,2,3
& Data Analysis

Forecasting           Harnett: Chapters 7,8

Simulation
Albright: Chapters 2,9

Optimization           Albright: Chapter 3
(Linear Programming)
Populations and Samples
Population of interest   (e.g., customers at Rampage Yachts, NC temperatures in June…)

Outlier: Sample value that’s not part
of our population of interest

Sample: Subset of the population
(dataset)

We want to make decisions about the population based
on the information from the sample
Discrim Dataset

   Female employees of a leading Detroit bank
have complained that male employees have
been given preferential salary treatment.

   You’ve been asked to summarize the
discrimination question
Discrim Dataset

http://www.csb.uncw.edu/people/mahars/mon/index.htm
dummy variable

Discrim Dataset

   Ratio data?
   Variable has a natural zero (meaningful to take ratios)
   Ordinal data?
   Outcomes of a variable express ranked order
   Categorical data?
   Variable is sorted into categories according to characteristics
Lab Problems

   Your assignment during this lab session is to:
   Work through as many of the following problems as
possible (in module 2 & 3 handouts):
 2.1, 2.2, 2.4-2.7

 3.1, 3.3, 3.7a, 3.11
Envelope Game
Expected Value and Variability

   Expected value of X

E[X] =   X  P( X )
i            i

   Standard deviation of X

sX =      X         E[ X ]  P( X i )
2
i
For Next Time

   Finish reading chapters 1 & 2 (Harnett)
   and finish working the lab problems
Additional Info from the 1st Class

   You can use your existing five/six member
teams for the HW assignments

   Expected return at the start of Deal or No Deal
   \$131,478
Risk?

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