How can I use NumPy for advanced statistics?

How can I use NumPy for advanced statistics?

You can use NumPy for various advanced statistical operations like calculating mean, median, standard deviation, and more. What specific statistical analysis are you interested in?

I want to perform regression analysis using NumPy.

For regression analysis, you can use NumPy's polyfit function to fit a polynomial to your data. Would you like a code example?

Yes, please provide a code example for linear regression.

Sure! Here's a simple example:

import numpy as np

# Sample data
x = np.array([1, 2, 3, 4, 5])
y = np.array([2, 3, 5, 7, 11])

# Perform linear regression
coefficients = np.polyfit(x, y, 1)

print('Slope:', coefficients[0], 'Intercept:', coefficients[1])

This will give you the slope and intercept for the best fit line.

How can I visualize the regression line?

You can use Matplotlib to visualize the regression line. Here's how you can do it:

import matplotlib.pyplot as plt

# Generate points for the regression line
regression_line = coefficients[0] * x + coefficients[1]

# Plotting
plt.scatter(x, y, color='blue', label='Data points')
plt.plot(x, regression_line, color='red', label='Regression line')
plt.legend()
plt.show()