Model blog 9

Ode to modeling
by james

Models, Models
How do I love thee?
I just cannot see
The more I search, the more I fall so deeply
for your methodology

This love I speak of it can't be erotic
I am married, and plus loving you that way would just be illogic
No! we are much deeper you and I,
down to the core,
problems we simplify.

Sometimes I wonder if you'd love me back.
But it is then that I think about blogging instead of hitting the sack.
It seems that I often lie awake pondering what to type.
until I scan the Google top ten list on business models in honolulu or some other foreign land
on which I may write.

I can not say we will last,
for there is but one day more,
that I should live search this class
or knock on Jeeves' door.

The greater question is this:
Will you hold me together
like staples or sutures
when I must design a system
way out in the distant future.

The End


eh-hem, and now to fulfill the requirement of this assignment:

Data to be put into this model:

love, affection, endearment.

Bayesian Decision Theory Blog 8

While surfing the interweb I came across this "normative approach" to decision making.

The Bayesian theory is pretty basic and is as follows:

1. Define a set of available actions
2. Define a set possible outcome of acts
3. Define a conditional probability distribution specifying the probability of each outcome given each available act.
4. Define a preference order ranking the possible outcomes distributions according to the desirability

The formulation of these definitions is really nothing more than a series of weighted averages that, in essence provide the user with the best decision possible.

This theory leaves presumes quite a bit. It presumes that there must be a defined amount of decision variable. In reality, there is not always a 0 to 100 percent probability of a course of action occurring. Sometimes the course of action is dependent upon other variable and are not up to chance.

Models are imperative to the decision making process, but oversimplification can be dangerous.

Blog Number 7 - Linear Programming

Much of Operations Management involves problem solving abilities. One way to solve problems is by using Excel's Linear Programming to minimize cost or maximize profits.

It is relatively simple to input the data then run the program. The majority of the problems occur when it is time to call on the limiting criteria.

It is very important to first model the criteria before typing it in manuscript form to Excel.

One important factor contributing to a decision model's success is the thought process behind its formulation and how well the manager uses the marketing-mix variables to formulate the model. It's important to focus on the actual problem at hand and then formulate the model with the variables directly related to the problem. Otherwise, implementation errors are inevitable.

Case in point, the problems with linear programming do not lie in the technology, for there will always be an algorithm for every query. However, if the formulation is off even a little bit, the result could be malicious.