The size of the data you are sorting really affects which sorting method to use. Here’s a simple breakdown of three different sorting techniques:

1. Insertion Sort: This method is great for small sets of data, like when you have less than 10 items. It’s easy to use and works quickly because it makes fewer comparisons. It can often sort these small lists in a time close to $O(n)$.

2. Merge Sort: This one is really good for larger groups of data. It works at a steady rate of $O(n \log n)$, which means it can handle big lists effectively. It’s a popular choice for sorting large amounts of data because it does well no matter how the data is arranged.

3. Quick Sort: This method is awesome for medium to large sets of data. On average, it also sorts at $O(n \log n)$. However, it can get slow, going up to $O(n^2)$, if the choices for dividing the data aren’t good. It works best when the data is big enough to be split up effectively.

In short, think about how big your data is and what it looks like when you pick the right sorting method!