Scaling: Scaling refers to multiplying (or dividing) every value in a dataset by a constant factor. It's often used in linear transformations to change overall magnitudes while preserving patterns.
Translation: Translation involves adding (or subtracting) a constant term to every value in a dataset, effectively shifting the entire set of data points up or down on a graph.
Reflection: Reflection is a transformation that involves flipping or inverting the values in a dataset. For example, multiplying all values by -1 would reflect them across the x-axis.