Present a set of secondary data from a reliable source, in table form, pertaining to the environmental issue of waste disposal in Canada. The data should show what could go wrong if nothing is done to counter the environmental issue of waste disposal. The data must be appropriate for modeling with one of the types of functions: polynomial of degree 3 or higher; exponential; logarithmic or trigonometric. A spreadsheet (Excel, Google Sheets etc.) could be used to create the table and would facilitate graphing the data. Include the APA reference for the data set.

Present a scatter plot of the data including appropriate titles, scales and units, created with the graphing technology of your choice.

Present an algebraic model that fits the data. The model can feature one of the functions mentioned above or could be a combination or composite of two of those functions. The choice of model should be based on visual inspection of data trends observed and does not need to be supported by statistical analysis. Include an explanation of how the algebraic model was determined, including justification for the choice of parent function (or combined or composite function) and any transformations used to model the data, restrictions on the domain of your function and a description, including justification, of potential limitations of the algebraic model as it applies to correlation with the data and the 'real world' context.

Present a graph of the algebraic model, including appropriate titles, scales, units, and restrictions on the domain, created with graphing technology, and superimposed on the scatter plot.

Perform at least one calculation using the algebraic model to make a prediction, or for emphasis of what could happen if nothing is done about the environmental issue.

Note:

Five data points is not a lot to create a reasonable model. The data should show what could go wrong if nothing is done. Pick ONE set of data and ONE model.

It is important that you explain, with evidence, WHY you selected this parent function to model your data set. Also, it is necessary to explain HOW/WHY you chose the parameters in the equation.

Consider the domain and limitations - can this model be used to make reasonable predictions indefinitely?