Scaling

1. What is min-max scaling and how is it calculated?
2. Explain max-abs scaling and its primary use.
3. Describe what is meant by 'range adjustment' in the context of data scaling.
4. How does scaling preserve the relative distances between values?
5. Why is min-max scaling particularly suitable for datasets with known boundaries?

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Standardisation

1. Why is having a ‘zero mean’ important in data standardisation?
2. What does it mean for a dataset to have unit variance, and why is it desirable?
3. Describe z-score standardisation and how it is implemented.
4. How does standardisation affect the distribution of features in a dataset?
5. Discuss the considerations for standardising data that does not have inherent bounds.

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Normalisation

1. What does range normalisation involve and how does it differ from min-max scaling?
2. Explain vector normalisation and its typical applications.
3. How does normalisation impact the ratios and proportions within a dataset?
4. Why is normalisation important when dealing with data in varied units?