on Understand the following function and the concept of "bootstrapping": def bs_med(original, name, copies): """
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*Python
Understand the following function and the concept of "bootstrapping":
def bs_med(original, name, copies):
"""
Return array of bootstrapped medians from samples"""
original = table with the original sample
name = name of column with variable
copies = samples from bootstrap
"""
single_column = original.select(name)
meds = make_array()
for i in np.arange(copies):
bs_sample = single_column.sample()
resample_med = percentile(50, bs_sample.column(0))
meds = np.append(meds,resample_med)
return meds
QUESTION: How can the bs_med function be used to find the p-value for a given set of data?
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- I keep on getting error for the following python code. Please help me resolve this error asap. # SYSC 2100 Winter 2023 Lab 11/Asst 2 import randomimport timefrom sort import bubble_sort, selection_sort, insertion_sort, heapsort __author__ = ''__student_number__ = ''__Version__ = '9.0.2' # Your profiling functions can have as many parameters as you want.# The return type of each function is up to you. def generate_random_list(length: int): return [random.randint(i, 1000) for i in range(length)] def profile_sort_algorithm(sort_function, test_lengths, repetitions): results = [] for n in test_lengths: timings = [] for i in range(repetitions): data = generate_random_list(n) start_time = time.perf_counter() sort_function(data) end_time = time.perf_counter() timings.append(end_time - start_time) average_time = sum(timings) / len(timings) results.append((n, average_time))…Create two Arrays A with 10 unsorted integer elements and B with 10 unsorted floatelements. Find the largest element in A and B and then sum both of them calling afunction SumAB() by reference. Sort A and B and then call another function StichAB()to merge B with A. Be careful about memory leakage.The goal is to rewrite the function, below, such that passes in a different list of parameters, particularly eliminating the need to pass low and high for each recursive call to binary_search. defbinary_search(nums,low,high,item): mid=(low+high)//2iflow>high:returnFalse #The item doesn't exist in the list!elifnums[mid]==item:returnTrue# The item exists in the list!elifitem<nums[mid]:returnbinary_search(nums,low,mid-1,item)else:returnbinary_search(nums,mid+1,high,item) The new function should be prototyped below. The number of changes between the given version, and the one requested is not significant. defbinary_search(nums,item):pass# Remove this and fill in with your code Tip: If you consider that high and low are used to create a smaller version of our problem to be processed recursively, the version requested will do the same thing, just through a different, more Pythonic technique.
