title: Normalize/scale data set
body: <p>I have the following data set:</p>
  
  <pre><code>dat&lt;-as.data.frame(rbind(10,8,2,7,10,10,1,10,14,9,2,6,10,8,10,8,10,10,7,11,10))
  colnames(dat)&lt;-"Score"
  print(dat)
  Score
  10
  8
  2
  7
  10
  10
  1
  10
  14
  9
  2
  6
  10
  8
  10
  8
  10
  10
  7
  11
  10
  </code></pre>
  
  <p>these are the test scores which students obtained, <strong>a student could get a maximum of 15 or a minimum of 0 in this test</strong> (by the way, nobody got the max or the min), <strong>however the lowest score obtained in this test was 1 and the highest was 14</strong>.</p>
  
  <p>Now, I want to normalize/scale this data to the scale of 0 to 20. 
  How to achieve this in excel? or in R?
  My final goal is to normalize the scores in this test to the above scale and to compare them with another set of data for which the max and min is 5 and 0 respectively. 
  How to compare these two different scaled data sets correctly against each other?</p>
  
  <p>What I tried:
  I went through many stuff on the internet, and came up with this:</p>
  
  <p><a href="https://i.stack.imgur.com/rdikv.png" rel="nofollow noreferrer"><img src="https://i.stack.imgur.com/rdikv.png" alt="enter image description here"></a></p>
  
  <p>which I got it from the <a href="https://en.wikipedia.org/wiki/Normalization_%28statistics%29" rel="nofollow noreferrer">wikipedia.</a>
  Is this method reliable?</p>