Using Python

Numerical methods are implementations of mathematical algorithms, but constructed with special consideration for accuracy of solutions and computational run-time. The order in which we implement floating point arithmetic for any numerical method will effect the accuracy of the final computed value. For this reason, extra thought must be placed on our basic mathematical operations. In this problem, you are asked to add-up the values in a large array called data. How should you do this to achieve the most accurate final sum? Return your summation as a floating point variable named data_sum. The values and size of data will vary in length, so make sure your code is written in a generic fashion to handle this aspect. The setup code gives the following variable: Name data Type 1D numpy array Description contains data to be summed Your code snippet should define the following variable: Name data_sum Type float Description sum of data with minimum error Note: data can contain negative numbers as well