The table below gives the frequency with which a sample of women drink tea and coffee (Arab, Lenore et al. "Gender differences in tea, coffee, and cognitive decline in the elderly: the Cardiovascular Health Study." Journal of Alzheimer's disease: JAD vol. 27,3 (2011): 553-66. doi:10.3233/JAD-2011-110431). Do women drink tea and coffee with the same frequency at the alpha = 0.01 significance level? Freq Tea Coffee 5/week 742 1148 Enter the data into an array. Calculate the chi-square statistic and p-value Write an if statement to determine if the null hypothesis that women drink tea and coffee with the same frequency is rejected or not.. Enter the data into an array. Calculate the chi-square statistic and p-value Write an if statement to determine if the null hypothesis that women drink tea and coffee with the same frequency is rejected or not. Ex: If the data for men is used, Freq Tea Coffee 5/ week 443 915 the output is: 3.776187E+02 1.903049E-80 The hypothesis that tea and coffee are drunk with the same frequency is rejected. LAB 7.6.1: LAB: Chi-square test ACTIVITY main.py 0/1 Load default template... 1 # Import the necessary modules 2 3 # Construct a contingency table 4 5 # Calculate the test statistic and p-value 6 chi2, p, df, ex = # Code for calculating test statistic and p-value 7 print (f' {chi2:.6E}') 8 print (f' (p:.6E}') 9 10 # Determine if null hypothesis is rejected or not 11 if # write appropriate if statement 12 print("The hypothesis that tea and coffee are drunk with the same frequency is rejected.") 13 else: 14 print("The hypothesis that tea and coffee are drunk with the same frequency is not rejected.")]