title: Statistical Operation over set of data to detect change in a value
body: <p>I have a set of dummy data e.g. 100 points that I wish to do the following:</p>
  
  <ol>
  <li>Use some statistical operation</li>
  <li>use the result of the Step 1 and create a hash e.g. sha-256 or md-5</li>
  </ol>
  
  <p>Then I want to change more than one data points within the set and perform the same steps above.</p>
  
  <p><strong>Point to Prove</strong>:</p>
  
  <blockquote>
    <p>I wish to leverage statistics of the given set as a <em>key</em> to perform a cryptographic hash for the set. If the set values are changed, I assume the statistical operation will provide a different value and in turn provide a different hash. If hashes don't match the sets are not the same.</p>
  </blockquote>
  
  <p>By using mean of the set, will it be enough to detect changes to a set, even if the values changed are extremely small?</p>
  
  <p>What other operation should I look into to perform step 1  of the query?</p>
  
  <h2>Code Idea</h2>
  
  <pre><code>import hashlib
  # get Set
  # Perform Step 1
  h1 = hashlib.sha256()
  h1.update(b'value from step1')
  
  # change values within set
  # perform Step 1
  h2 = hashlib.sha256()
  h2.update(b'new value from step2')
  
  # check if h1 == h2
  h1 
  </code></pre>