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Using regression is fine, but you need to justify why it is appropriate and relevant e.g. why should it be linear?

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Footnotes are helpful. Must have bibliography

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Reflection throughout - it narrates and drives your work while tying back to aim

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Presentation: has to be coherent, concise, and well organized.

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Use of mathematical notations, symbols, terminology and multiple forms of mathematical representation.

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Need to show understanding of the mathematics used and not just substitute numbers in a formulae. This can be achieved by reasoning and explaining the mathematics used.

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Personal Engagement, take an active part in the exploration.

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constant reflection throughout (must include meaningful reflections e.g. linking to the aim, comments, consideration of limits of this mathematical approach)

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Use tools such as equation editors and graphing software for consistent and accurate notations.

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Fix minor issues such as spelling, article errors adn refrences which arent properly referenced.

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Explain what the formula mean and show understanding

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add citations and avoid repetition

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Problems may occur if candidates try to connect other areas of study they haven't researched whether the maths would be accessible.

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Labelling axes accurately and having clear screenshots of graphs. Define key terms and variables.

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Make reflections throughout the IA. Make it constant and detailed. Also, make sure its relevant

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Provide more meaningful reflection and evaluate my work as a whole

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Do not connect maths to other areas of knowledge that you have not researched on

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Explain how the maths links to the exploration and demonstrate understanding

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Compare real life examples with the mathematical theory

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conduct surveys and experiments, collect own data

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Do not just let technology do the work for you without showing understanding and justifying your choice of model.

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Collecting own data is much better than just saying "I have been interested in this because.." and think creatively