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Given the following text problem statement, write Python code to implement the functionality described below in problem statement
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Problem:
I have an array of experimental values and a probability density function that supposedly describes their distribution:
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Python Code:
import numpy as np
import scipy as sp
from scipy import integrate,stats
def bekkers(x, a, m, d):
    p = a*np.exp((-1*(x**(1/3) - m)**2)/(2*d**2))*x**(-2/3)
    return(p)
range_start = 1
range_end = 10
estimated_a, estimated_m, estimated_d = 1,1,1
sample_data = [1.5,1.6,1.8,2.1,2.2,3.3,4,6,8,9]
def bekkers_cdf(x,a,m,d,range_start,range_end):
    values = []
    for value in x:
        integral = integrate.quad(lambda k: bekkers(k,a,m,d),range_start,value)[0]
        normalized = integral/integrate.quad(lambda k: bekkers(k,a,m,d),range_start,range_end)[0]
        values.append(normalized)
    return np.array(values)
    
s, p_value = stats.kstest(sample_data, lambda x: bekkers_cdf(x, estimated_a, estimated_m, estimated_d, range_start,range_end))
if p_value >= 0.05:
    result = False
else:
    result = True
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