Objective: Demonstrate your understanding of basic and complex data types in Python and apply algorithm design techniques to solve problems.

Tasks:

Data Types and Structures:

Define basic data types $($int$,$ float, str$,$ bool$)$ and complex data types $($list$,$ tuple, set, dictionary$)$ in Python and R$.$

Provide examples for each type and explain a scenario where a complex data type would be preferable over a basic data type.

Algorithm Design:

Choose one algorithm design technique $($recursion$,$ divide and conquer, dynamic programming, greedy algorithms$).$

Write a Python and R function that uses the chosen technique to solve a specific problem $($e$.$g$.,$ Fibonacci sequence, merge sort$).$

Analyze the time and space complexity of your solution.

Performance Analysis:

Compare your algorithm's performance with another algorithm designed to solve the same problem.

Use asymptotic notation to express the complexities and discuss the efficiency.

Conclusion:

Please submit your application and findings exclusively in a Word Document format.