title: Why does scipy.norm.pdf sometimes give PDF > 1? How to correct it?
body: <p>Given mean and variance of a Gaussian (normal) random variable, I would like to compute its probability density function (PDF). </p>
  
  <p><a href="https://i.stack.imgur.com/XwgLg.gif" rel="noreferrer"><img src="https://i.stack.imgur.com/XwgLg.gif" alt="enter image description here"></a></p>
  
  <p>I referred this post: <a href="https://stackoverflow.com/questions/12412895/calculate-probability-in-normal-distribution-given-mean-std-in-python">Calculate probability in normal distribution given mean, std in Python</a>,</p>
  
  <p>Also the scipy docs: <a href="http://docs.scipy.org/doc/scipy/reference/generated/scipy.stats.norm.html#scipy.stats.norm" rel="noreferrer">scipy.stats.norm</a></p>
  
  <p>But when I plot a PDF of a curve, the probability exceeds 1! Refer to this minimum working example:</p>
  
  <pre class="lang-python prettyprint-override"><code>import numpy as np
  import scipy.stats as stats
  
  x = np.linspace(0.3, 1.75, 1000)
  plt.plot(x, stats.norm.pdf(x, 1.075, 0.2))
  plt.show()
  </code></pre>
  
  
  
  <p>This is what I get:</p>
  
  <p><a href="https://i.stack.imgur.com/8H2Oi.png" rel="noreferrer"><img src="https://i.stack.imgur.com/8H2Oi.png" alt="Gaussian PDF Curve"></a></p>
  
  <p>How is it even possible to have 200% probability to get the mean, 1.075? Am I misinterpreting anything here? Is there any way to correct this?</p>