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Let's hypothesize that the mean tip percentage in the population is 1 7 % . Use sample _ mean, standard _ error, and the hypothesized

Let's hypothesize that the mean tip percentage in the population is 17%. Use sample_mean, standard_error, and the hypothesized value to calculate the t-statistic. Then use scipy.stats's norm.cdf function to calculate the p-value. Finally, decide whether you reject or fail to reject the hypothesis. Store your answers in the variables t_stat, p_val, and reject_or_not. The variable reject_or_not should either be the string 'reject' or the string 'fail to reject'. Remember to look at the units of the variable tip_percentage (in the output of taxi.head() above) in order to set the hypothesized value correctly. my code is wrong: import numpy as np
import pandas as pd
from scipy.stats import norm
taxi = pd.read_csv('assets/taxi.csv')
tip_percentages = taxi['tip_percentage']
hypothesized_mean =0.17
sample_mean = np.mean(tip_percentages)
sample_size = len(tip_percentages)
sample_var = np.var(tip_percentages, ddof=1)
standard_error = np.sqrt(sample_var / sample_size)
t_stat =(sample_mean - hypothesized_mean)/ standard_error
p_val =2* norm.cdf(-np.abs(t_stat))
alpha =0.05 # Significance level
reject_or_not = 'reject' if p_val < alpha else 'fail to reject'
print(f"t-statistic: {t_stat}")
print(f"p-value: {p_val}")
print(f"Decision: {reject_or_not}") error code: You have failed this test due to an error. The traceback has been removed because it may contain hidden tests. This is the exception that was thrown:
AssertionError: Problem 2.1:Your answer for t_stat does not match the official answer.

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