norm.pdf python

# import required libraries
from scipy.stats import norm
import numpy as np
import matplotlib.pyplot as plt
import seaborn as sb
 
# Creating the distribution
data = np.arange(1,10,0.01)
pdf = norm.pdf(data , loc = 5.3 , scale = 1 )
 
#Visualizing the distribution
 
sb.set_style('whitegrid')
sb.lineplot(data, pdf , color = 'black')
plt.xlabel('Heights')
plt.ylabel('Probability Density')

3.9
10
Egoiste 100 points

                                    #calculating the probability or the area under curve to the left of this z value
import scipy.stats as stats
stats.norm.pdf(x, loc=mean, scale=std_dev)




# The probability (area) to the right is calculated as (1 - probability to the left)
import scipy.stats as stats
1 - stats.norm.pdf(x, loc=mean, scale=std_dev)

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