Definition
Model
A simplified representation of a system or phenomenon.
- Models helps us understand, analyze, and predict the behavior of real-world systems.
- Models can be physical, mathematical, or computational.
- In computer science, we often use computational models that rely on data representation and organization.
- Imagine you want to predict the growth of a population.
- Instead of tracking every individual, you can use a mathematical model that considers birth and death rates.
Data Representation in Models
Types of Data Representation
- Tabular Data: Data organised in rows and columns, like spreadsheets.
- Graphical Data: Visual representations such as charts and graphs.
- Mathematical Equations: Formulas that describe relationships between variables.
A spreadsheet showing sales data over time is a form of tabular data representation.
Choosing the Right Representation
- The choice of data representation depends on the purpose of the model and the type of data involved.
- Use tabular data for detailed records.
- Use graphical data to visualize trends.
- Use mathematical equations for precise relationships.
Data Organisation in Models
Why Organise Data?
- Efficiency: Organised data is easier to process and analyze.
- Clarity: It helps users understand the model.
- Scalability: Well-organised data can handle larger datasets.
Methods of Data Organization
- Arrays: Store data in a linear sequence.
- Lists: Flexible collections that can grow or shrink.
- Tables: Structured data with rows and columns.
A weather model might use an array to store temperature readings and a table to organize data by location and time.
Constructing a Simple Model
- Step 1: Define the Problem
- Start by identifying the system you want to model and the questions you want to answer.
