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PRIMARY AND SECONDARY DATA

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-  Starts with simple model development and build toward greater complexity.
-  Ability to invent or formulate an idea/concept.
-  Occurs in the beginning of a design activity.

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- Need to be correct
- Low levels of detail may result in lost of information and goals cannot be accomplished.
- High levels of detail require:
~ more time and effort
~ longer simulation runs

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Essential features:
1) Entity - is an object of interest in the system.
Example: Health Care
- Patients
- Visitors
2) Attribute - is a characteristic of all entities ( Unique entity to differ from one entity to another)
Example: Patient
- Type of illness
- Temperature
3) Resources - what entities compete for.
Example: Health Center
- Doctors
- Nurses
4) Activity - represents a time period of specified length.
Example: Health Center
- Surgery
- Checking temperature
5) State Variables - collection of variables necessary to describe the system at any time.
Example : Factory
- number of machine (busy, idle, down)
6) Event - An instantaneous occurrence that changes the state of the system.
Example: Health Care
- Arrival of a new patient
- Completion of service (i.e., examination)

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Process of establishing a reasonable model

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The process of gathering information related to our case study is called data collection, which can be obtained from various sources.

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We need to understand the objective of our case study and the problem we want to solve so that we can collect related and relevant data

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2. Operational Definitions & Procedure (How to Collect Data)

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2. Operational Definitions & Procedure (How to Collect Data)

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Plan an approach and method. We need to be very clear as to what we are measuring, how it is to be measured, duration of data collecting process and who is to measure it. Data collection can be done by:
Primary Data:

Interview

Observation

Survey/Questionnaire

Experiment

Secondary Data (a type of data that has already been published):

Online materials

Journals

Newspaper

Books

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Start collecting data

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Data analyzing is the process of evaluating data using analytical and logical reasoning to examine each component of the data provided.
There are generally two forms of data analysis: quantitative and qualitative.

1. The goal of quantitative analysis is to use numbers and statistics to describe your sample and to use these data to help explain any differences that may exist between your sample and the population.

2. The goal of qualitative analysis is to use words and stories to provide a narrative or picture of a situation or individuals.

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After being collected and processed, data need to be classified and organized to produce useful information. There are a wide variety of ways to summarize, organize, and present data.

For instance, we can organize our data in graphical form such as histogram, scatter plot, pie chart and more.

Data presented in time sequence can be organized chronologically.

Qualitative data can be classified by reviewing the entire data set so that themes or patterns begin to emerge. Assign letters, numbers or symbols to designate categories. Like responses on a particular topic can be grouped together.