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Identify the variables: The first step is to identify the variables that are involved in the problem. These variables can be physical quantities such as length, time, temperature, etc.

Choose a graph: Once the variables are identified, a graph should be chosen that best represents the relationship between them. The type of graph chosen will depend on the nature of the relationship, whether it is linear, exponential, logarithmic, etc.

Collect data: Data should be collected for the variables being studied. This data should be in the form of numerical values for each variable.

Plot the data: Once the data has been collected, it should be plotted on the graph. The x-axis represents the independent variable, while the y-axis represents the dependent variable.

Determine the equation: Once the data has been plotted on the graph, an equation that best fits the data points should be determined. This equation can be determined using regression analysis, which is a method for finding the line of best fit for the data.

Verify the equation: Once the equation has been determined, it should be verified by comparing it to other known data points or by using it to make predictions.

Use the equation: Once the equation has been verified, it can be used to make predictions about the behavior of the variables in the future. This can help in making decisions or in designing experiments to further study the problem.

Code the model in MATLAB: Finally, the mathematical model can be coded in MATLAB using the equation and the data collected for the variables. This will enable the model to be used for further analysis and simulation.