The complexity of the linear search algorithm is C) O(n).

Here's why:

1. A linear search algorithm works by sequentially checking each element in a list until it finds a match.

2. In the worst-case scenario, the algorithm would have to check every single element in the list.

3. Therefore, the time complexity of a linear search algorithm is proportional to the number of elements in the list, which is represented as O(n) in Big O notation.

4. Big O notation is used in computer science to describe the performance or complexity of an algorithm. O(1) represents an algorithm that always executes in the same time, regardless of the size of the input data set. O(n) represents an algorithm whose performance will grow linearly and in direct proportion to the size of the input data set.

5. So, the answer is C) O(n).

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The complexity of the linear search algorithm is C) O(n).

Here's why:

1. A linear search algorithm works by sequentially checking each element in a list until it finds a match.

2. In the worst-case scenario, the algorithm would have to check every single element in the list.

3. Therefore, the time complexity of a linear search algorithm is proportional to the number of elements in the list, which is represented as O(n) in Big O notation.

4. Big O notation is used in computer science to describe the performance or complexity of an algorithm. O(1) represents an algorithm that always executes in the same time, regardless of the size of the input data set. O(n) represents an algorithm whose performance will grow linearly and in direct proportion to the size of the input data set.

5. So, the answer is C) O(n).

Knowee AI · Accepted Answer

The complexity of the linear search algorithm is C) O(n).

Here's why:

1. A linear search algorithm works by sequentially checking each element in a list until it finds a match.

2. In the worst-case scenario, the algorithm would have to check every single element in the list.

3. Therefore, the time complexity of a linear search algorithm is proportional to the number of elements in the list, which is represented as O(n) in Big O notation.

4. Big O notation is used in computer science to describe the performance or complexity of an algorithm. O(1) represents an algorithm that always executes in the same time, regardless of the size of the input data set. O(n) represents an algorithm whose performance will grow linearly and in direct proportion to the size of the input data set.

5. So, the answer is C) O(n).

The complexity of linear search algorithm is*1 pointA) O(n2)B) O(log n)C) O(n)D) O(n log n)

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