WGU Foundations-of-Computer-Science Exam With Confidence Using Practice Dumps

A function definition in Python specifies a function name and a list of parameters. Here, def linear_search(customersList, search_value): defines a function named linear_search that requirestwo argumentswhen called: a list (or sequence) of customer items and the value being searched for. A correct call must therefore supply both arguments in the same order: linear_search(customersList, search_value). Option B is correct because it calls the function properly and then prints the returned result.

Textbooks describe linear search as scanning the list from the beginning to the end, comparing each element to search_value until a match is found or the list ends. The function typically returns an index (e.g., position of the match) or a Boolean, or possibly -1/None if not found. Wrapping the call in print(...) is a standard way to display the returned value for testing or demonstration.

Option A is incorrect because it calls a different function name, not linear_search. Option C is incorrect because linear_search() would attempt to call the function with zero arguments, which would raise a TypeError, and then it tries to call the result as if it were another function. Option D uses a different function name (search_linear) and also contains a spelling mismatch compared to the given definition.

In Python and NumPy, indexing iszero-based, meaning the first element of a 1D sequence is at index 0, the second element is at index 1, and so on. A NumPy array behaves like a sequence for basic indexing, so numpy_array[1] returns the element stored at position 1 in the array. This is a fundamental concept taught in introductory programming and scientific computing: indexing selects a single element, while slicing selects a range.

For example, if numpy_array = np.array([5, 8, 13]), then numpy_array[0] is 5, numpy_array[1] is 8, and numpy_array[2] is 13. The expression numpy_array[1] therefore evaluates to thesecond element(8 in this example). This does not display the entire array (that would happen with print(numpy_array)), and it does not produce an error unless the array is too short. An error such as IndexError occurs only if index 1 is out of bounds, for example when the array has length 1 and you try to access numpy_array[1].

Textbooks emphasize careful reasoning about indices because off-by-one errors are common. In data analysis, correct indexing is crucial for extracting the right observations, features, or time steps from numerical datasets.

In Python, the standard way to display output to the console is the built-in function print(). When a program performs calculations—such as arithmetic expressions, function results, or computed statistics—print() can be used to show those results to the user. For example, print(2 + 3) displays 5, and print(total / count) displays the computed average. Textbooks introduce print() early because it supports interactive learning, debugging, and communicating program behavior.

print() can display one or multiple items separated by commas, automatically converting them to string form. It also supports formatting via f-strings (e.g., print(f"Sum = {s}")) and optional parameters like sep and end to control output formatting. This makes it versatile for reporting calculated values, intermediate steps in algorithms, and final program outputs.

The other options are not standard Python built-ins for output. compute(), result(), and solve() are not universally defined commands in Python; they might exist as user-defined functions or in specific libraries, but they are not the general command taught in textbooks for displaying results. Python follows a clear separation: expressions compute values; print() displays them.

Therefore, the correct answer is print(), as it is the primary mechanism for producing human-readable output from calculations in typical Python programs and coursework.