title: How to generate a random normal distribution with specific standard deviation
body: <p>I have already used this function :</p>
  <pre><code>np.random.seed(40)
  np.random.normal(loc = 0, scale = 1, size = 10)
  </code></pre>
  <p>However, I'm assuming the values should be between 1 and -1 right?
  But I'm getting values that are larger than 1 and smaller than -1. How is that possible?</p>
  <p>I'm getting this array :</p>
  <pre><code>array([-0.6075477 , -0.12613641, -0.68460636,  0.92871475, -1.84440103,
         -0.46700242,  2.29249034,  0.48881005,  0.71026699,  1.05553444])
  </code></pre>
  <p>You can see there're values like 2.2924 and also -1.8 which is ranges outside the standard deviation</p>
  <h3>Possible solution</h3>
  <p>I have made this code, is this okay?</p>
  <pre><code>final_data = []
  count = 0
  a = 26 # standard deviation
  b = 157 # mean
  
  for i in range(2000):
      y = a*np.random.normal(0, 1, 1) + b # equation to multiply by the std and add the mean
      if y &lt;= upper and y &gt;= lower :
          final_data.append(y[0])
          count += 1
          if count &gt; 608:
              break;
  </code></pre>
  <p>Where upper and lower are the mean + std and mean - std.
  I have first generated a randomly distributed number and then put it in the equation. If the number is between the specific range, then I added it to the list</p>