Java true or falsequestions!!!!!!!!!!!!!!!!!!!!!!!!!!!!

True/False (13) 1. Time complexity is typically more important than space complexity 2. An inverse relationship often exists between the time complexity and space complexity of an algorithm. 3. Reformulating an algorithm to run faster most likely has no effect on the space requirements. 4. You cannot compute the actual time requirement of an algorithm. 5. You cannot predict the behavior of an algorithm without implementing it and timing the code. 6. In algorithm analysis, the general behavior of the algorithm is more important than the exact count of operations. 7. An algorithm's basic operation is always the most frequent operation performed. 8. Ignoring operations that are not basic will not affect the final conclusion about algorithm speed. 9. For large values of n, the grown rate of n is smaller than n log n. 10. For large values of n, the growth rate of n! is larger than 2" 11. The behavior of a logarithmic function is the same regardless of its base. 12. You want the upper bound on f(n) to be a large as possible. 13. All of the operations for the fixed-size array-based bag ADT have the same Big-O time complexity as the linked-based bag ADT.