title: Projecting revenue using information on percentile?
body: <p>Suppose I have 2 datasets: splitA (the control group) and another dataset, splitB (the treatment group in which a feature was implemented). Both datasets have the following columns:</p>
  
  <p>username,
  session, 
  revenue</p>
  
  <p>It was determined for the previous year that August was in the 70th-percentile for revenue. How do I use this information to project the change in annual revenue after implementing the feature?</p>
  
  <p>My calculations thus far:</p>
  
  <p>August was the 70th percentile for revenue last year, so</p>
  
  <pre><code>total_revenue_A_aug = np.sum(splitA_df.revenue)
  std_a = np.std(splitA_df.revenue)
  </code></pre>
  
  <p>Follows standard normal distribution X = mu + z*sigma...</p>
  
  <pre><code>mean_A = total_revenue_A_aug - 0.5244*std_a
  </code></pre>
  
  <p>Am I on the right track?</p>