Ashford 5: - Week 4 - Discussion 1
For this discussion, you will assess the use of various support decision tools:
1.) Simulation models
2.) Information control
3.) Processes
4.) Paradigm models
5.) R
The Management Science Process consists of 1) understanding the problem, 2) building a
representative model, 3) solving the mathematical model and, lastly, 4) monitoring/communicating
the outcome. Dis
Understanding the Problem:
Problem definition is likely the most important step of the Management Science process, and
should be looked at in detail. I say that this is a vital step because it is ess
The simplest time series forecasting model is one in which the mean value of the item being
examined is assumed to be relatively constant or stationary overtime. (Lawrence, Pasternack,
2002, Pg. 390)
Frank Hurley has two options for his crop and wants
to maximum profits. With the multiple data I found it
easier to break each option into two separate
scenarios based on total profit and then summari
PERT a technique that treats activity completion times, as random variables, can be used
to determine the likelihood that a project will be completed within a certain time period.
(Lawrence, Pasternac
Management science process is applied in all areas of the business. I use them daily on
budgeting, procurement analysis such as lead times, vendor management, order points
and more. I have seen the pr
A decision tree is a chronological representation of the decision process. The root of the tree is
a note that corresponds to the present time. (Lawrence, Pasternack, 2002, Pg. 349)
A Scenario example
Queuing theory is the study of waiting lines, or queues. (Lawrence, Pasternack, 2002,
Pg. 502
Chapter 9.1 gives a detailed explanation of the queuing theory in regards to retail lines. In
summary line
MVC ENTERPRISES PRODUCTION ANALYSIS
Marvin Phelps
BUS 461 Decision Modeling & Analysis
Dr. Vucetic
October 26, 2015
MVC Enterprises Production Analysis:
To: MVC Enterprises
From: Marvin Phelps Student
Running head: WIND POWER
Network Design for Wind Power Farms
Janice L. Ali
INF220: IS Principles
Instructor: Dr. Pamela Harris
September 21, 2015
1
WIND POWER
2
Network Design for Wind Power Farms
All
Running head: INFORMATION SYSTEMS
1
Information Systems within United Parcel Service
Janice L. Ali
INF220: IS Principles
Instructor: Dr. Pamela Harris
September 07, 2015
INFORMATION SYSTEMS
2
Informat
Example of when you might want to take a cluster random sample instead of a simple
random sample?
To answer this, I first need to see the difference in each.
Cluster random sample is where there are d
PROBABILITY
Coke/Pepsi Dummie
0.5
0.45
0.32
0.28
0.61
0.38
0.24
0.1
0.8
0.52
0.21
Coke
Pepsi
Confidence Interval at 95%
Half Length at 2%
Probability
0
0
Random Data A6-A15 and b5,b6
1
0
1.96
0.02
1
M
You have been assigned to determine whether more people prefer Coke or Pepsi. Assume that roughly half the pop
P = 0.5
z-multiple 1.959964
B = .02
n = sample size
n = (sqrt(z-multiple/B) * p(1-p)
n =
Venture Limited Investment Decision
Sure thing = P1
Less Risky = P2
More Risky = P3
Sure Thing (P1)
Outcome
Less Risky (P2)
Outcomes
Probability
More Risky (P3)
Outcomes
Probability
Venture Decision
B
Probability, p1 =succeed in developing the microprocessor in time.
Probability, p2 =if exceed changes company will win the 1 million Olympic contract.
Probability, p3 = they do not succeed; there is a
A Simulation develops a model to evaluate a system numerically over some time period of
interest. Its purpose is to estimate characteristics for the system, which can then be used to select
the best p
As with any project it is best to know the requirements before setting up the plan. The
instructors Guidance details a GREAT model which is a good basis of required information
before commencing.
Goal
Do the students scores for the two exams tend to go together, so that those who do poorly
on the midterm tend to do poorly on the final, and those who do well on the midterm tend
to do well on the fin
According to our text (Albright and Winston, 2017), the seven-step modeling process is
as follows: Define the problem, Collect and summarize data, Develop a model, Verify the model,
Select one or more
Number of defective items in a random sample of 15 items
X
P(X)
# of defectives
0
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
SUM
Probability
0.2059
0.3432
0.2669
0.1285
0.0428
0.0105
0.0019
0.0003
0.0000
0.0
BUS 461
Week 2 Assignment
Uncertainty
Read Case 6.3: Electronic Timing System for Olympics on pages 275-276 of the textbook.
For this assignment, you will assess and use the correct support tool to de
BUS 461 Wk 2 Assignment Writing a Business Report Memo -Ashford
Just Click on Below Link To Download This Course
https:/sellfy.com/p/i5c3/
Complete Problem 7 in Chapter 3 in the text. Develop a two to