\( ( \int _ { - \infty } ^ { + \infty } e ^ { - x ^ { 2 } } d x ) ^ { 2 \cdot \frac { 1 } { 2 } } \)
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The Deep Dive
Did you know that the integral \( \int _{ - \infty }^{ + \infty } e^{-x^2} \, dx \) equals \( \sqrt{\pi} \)? This integral is a classic example in probability and statistics and is often used to derive properties of the normal distribution. The beauty of this integral lies in its symmetry and connection to Gaussian functions. Now, if we square the result, \( ( \sqrt{\pi} )^2 \), we end up with \( \pi \). This transformation is useful in many areas, including quantum mechanics and statistical mechanics, where the Gaussian distribution plays a pivotal role in model behaviors and phenomena. How cool is that?
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