Final answer:
The array module is preferred over lists in Python for large numeric data sets due to its memory efficiency and performance advantages in arithmetic operations. It is also crucial to limit digits in calculations for practicality, understanding of significant figures, and when working with complex numbers like index numbers.
Step-by-step explanation:
The array module is a powerful tool in Python, particularly when dealing with a large quantity of numeric data values. It is often chosen over the built-in list data type when the data is homogeneous and numeric, mainly because it is more memory-efficient and can potentially provide better performance for numerical calculations. Since arrays are tightly packed with a single data type, they save memory compared to lists, which are more general-purpose and can store elements of different types. Furthermore, the array module can offer better performance with arithmetic operations due to its internal implementation and the ability to leverage more specialized processing techniques on the contained data.
When performing calculations or computations, it's essential to be concerned with the number of digits you're using. We often limit the number of digits to a manageable number like three for practical reasons such as readability, precision-needs, and because additional digits beyond a certain point may not be meaningful - showing an understanding of the concepts of accuracy, precision, and significant figures. This is critically important when calculating things like index numbers based on a basket of goods where the results can be complex and unwieldy if too many digits are included.