Question

8. Describe the differences between developing and developed flow.

9. Describe problems where Minitab could be used effectively.

10. Discuss what type of problems where Python, Matlab, and Maple could be used effectively.

Answer 1

Answer 8. This tabular structure presented below has been associated with the valid presentation of differences between developing flow and developed flow.

Developing Flow	Developed Flow
Basic use of flow-based programming is done within this feature of operations.	Advanced use of flow-based programming is done within this feature of operations.
Developing flow is functionally not complete at any point of consideration and eventually reaches there.	Developed flow is functionally complete at the time of running as well as at the time of execution.
Developing flow eventually reaches the developed flow stage of operations with every application bound to the complete logic	Developed flow does not have to reach a certain consideration as it is already logically complete
Easier to process with segmented analysis and further approach	Harder to process with complex functionality and required completeness

Answer 9. The points mentioned below associate with the consideration of Minitab and its problem-solving capabilities:

1. Problems related to trends and understanding their applications through trend analysis can be done through Minitab

2. Issues that occur with improper visualization of data and its statistical changes implemented can be solved using Minitab

3. The issues related to statistical needs for the systems can be effectively solved with the help of Minitab applications

4. A requirement of management principles upon data and results and problems relating such requirements can be solved

Answer 10. The type of problems where Python, Matlab, and Maple could be used effectively has been determined here:

1. Python: Compared with other programming languages like C++ and Java on an object-oriented level of operation, Python provides additional help in solving large calculations and data analysis problems using its core programming structure. The consideration of data analysis library exclusively present for Python helps import huge data from other databases and even excel-sheets

2. Matlab: Matlab could be used to effectively implement information processing for problems related to image files as the source of data. Advanced image processing is possible through the Matlab environment. Another benefit is that problems related to fuzzy logic can be visually implemented within the Matlab modules and effectively worked upon to be solved with the application

3. Maple: Maple helps the users associate with solving problems based on symbols and numeric. It provides required computation with arbitrary precision. Advanced mathematic problems can also be solved with an effective approach using Maple. The consideration of complex numerical and interval related arithmetic can be effectively processed through Maple operations