Executive Summary:
In the Pedigree Vs. Grit: Predicting Mutual Fund Manager Performance case, AMBTPMs
management team is faced with the challenge to appoint a new head in charge of its signature
funds
A
1
2
3
4
5
6
7
8
9
10
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12
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14
15
16
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20
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24
B
C
D
E
F
G
H
I
<=
<=
<=
Supply
150
167
188
Shipping Cost ALPHA
Cost per 1000 tires
Plant 1
Plant 2
Plant 3
Total Demand (thousands)
Ma
Descriptive statistics
Cost per attendee
count
17
mean
1,117.29
sample standard
445.52
sample variance 198,490.60
minimum
605
maximum
2468
range
1863
confidence inter
confidence inter
halfwidth
z
939
Microsoft Excel 14.1 Limits Report
Worksheet: [Cox MS Exam.xlsx]Stone Age Surfboards
Report Created: 3/16/2015 7:06:23 PM
Objective
Cell
Name
Value
$B$15 Units Graystone $ 
Variable
Cell
Name
Value
$
Decision Variables  TBD to determine drug value
Decision Variables
Code
Is Competitor a Breakthrough?
No
Yes
0
1
II
se
Ph
a
0
0
0
Cholesterol only approved
Obesity only approved
Both approved
Re
su
l
Case Analysis #1
Bryan Bradshaw
Ryan Cox
Keyan Peterson
Executive Summary
In our research and analysis of the Prudent Pensions and Macpherson cases, we were challenged
to optimize very different scena
1
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46
A
Formulation
B
C
D
E
F
G
H
I
J
K
Decisions:
x1 number of asset 1 to p
Optimization Problem Set
We approached problem 3.12 with a goal to minimize the initial investment into
assets 1,2, and 3 to meet the required flow. We used the objective function of
Z=x1+x2+x3, where
CHAPTER 5


Normal distribution: continuous distribution characterized by symmetric bellshaped curve & is
cornerstone of statistical theory
Binomial distribution: discrete distribution relevant whe
Simulation Problem Set
MBA 701
September 26, 2014
Problem 1
After running this simulation, the management of Emerald Nuts is able to decide on the best
production policy to move forward with. The obje
MBA 701: Linear Programming Case Report
9/3/14
Executive Summary
Prudent Financial Services and MacPherson Refrigeration are two companies that have been
presented with an objective that requires deci
Optimization Problem Set
MBA 701
9/12/14
3.12
When considering problem 3.12 it becomes clear that Maureen Laird is faced with a
minimization problem. She must minimize the investment while meeting the
CHAPTER 8:


Given an observed data set, we want to make inferences to some larger population
Inferences in this chapter are always based on an underlying probability model, which means
that some ty
CHAPTER 4:




Random variable: associates a numerical value with each possible outcome in a situation
involving uncertainty
o Ex: demands for products, time b/t arrivals to a supermarket, stock p
m=
s=
a.
b.
c.
d.
e.
f.
450 bags
80 bags
Direction
Highest
Lowest
Lowest
Highest
Highest
Middle
g. Lowest
h. Middle
i. Highest
The weekly demand for Baked Lays potato chips at a certain Subway
sandwic