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15.  Creating a normal distribution and displaying in graph (using Numpy + Matplotlib) - Display the scores of
              students in a graph and check if it is a normal distribution? What is the mean, median and mode of this data?

          Ans.  import numpy as np

              import matplotlib.pyplot as plt
              scores = np.array([75, 82, 88, 92, 68, 78, 85, 90, 95, 98])

              # Calculate mean and standard deviation
              mean_score = np.mean(scores)

              std_dev = np.std(scores)
              # Create a histogram of the scores with a normal distribution curve

              plt.figure(figsize=(10, 6))
              plt.hist(scores, bins=5, density=True, alpha=0.6, color='blue', label='Histogram')

              plt.title('Student Scores Distribution')
              plt.xlabel('Score')

              plt.ylabel('Density')
              plt.grid(True)

              # Create the normal distribution curve
              x_range = np.linspace(min(scores), max(scores), 100)

              normal_distribution = (1 / (std_dev * np.sqrt(2 * np.pi))) * np.exp(-((x_range
              - mean_score)**2) / (2 * std_dev**2))
              plt.plot(x_range, normal_distribution, color='red', label='Normal Distribution')

              plt.legend()
              plt.show()
              Output:
































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