what is math modeling

What is Math Modeling?

it represents, analize, make predictions or provide insight into real-world phenomena.

it can help us answer big messy questions

It has 6 steps

Make assumptions

Defining variables

Getting a solution

Analysis and model assessment

Report results

Defining the problem

it is important because there are many ways to approach the question

it will reduce the amount of information you have to consider

They help you understand what and how your equations gonna work

defining the problem statement

A concise restatement of the problem will tell you what your model will measure or predict.

Focus and define subjective words

Explore with research and brainstorming

Brainstorm like you have access to any and all data

Assessing a team member to record every idea

Visual diagrams can be a powerful tool to help structure

Keep an open mind

tips to make assumptions

Assumptions come from brainstorming

Preliminary research will help you make assumptions

In the absence of relevant data, it's reasonable to make an assumption

Assumptions develop as you move through the modeling process

there are two kind of variables

Dependent variables (outputs)

they represent the information you seek

independent variables (inputs)

represent quantities you know

things to remember when defining variables

your problem statement will define the output

initial brainstorming should give clues to define your independent, dependent and fixed model parameter

keep track of units

You may need to do additional research or make new assumptions

sub models may be needed

is digging into your math toolbox to find the pieces that will get you an answer to your problem.

Building solutions

Use software tools or the math you already know

You might discover more than one ways to tackle a problem

Different methods can lead to different solutions

Analysis is critical in determining whether or not your model works

tips to make the work easy

It is just to explain the model

tips to writte the report

ask yourself some questions

Determine your model's sensitivity to parameters and assumptions

Consider potential improvements

Examine the outputs of your model

Leave enough time to analyze results

List the model's strengths and weaknesses

Does the model make sense?

Is the answer reasonable?

Does the model behave as expected?

Make sure to validate your model

Take good notes

Follow technical writting procedures

Justify all assumptions and cite all sources

Give yourself time to write and proofread your paper