title: Apply t-test on many columns in a dataframe split by factor
body: <p>I have a dataframe with one factor column with two levels, and many numeric columns. I want to split the dataframe by the factor column and do t-test on the colunm pairs. </p>
  
  <p>Using the example dataset Puromycin I want the result to look something like this:</p>
  
  <pre><code>Variable    Treated Untreated   p-value    Test-statistic CI of difference**** 
  Conc        0.3450  0.2763          XXX     T           XX - XX
  Rate        141.58  110.7272        xxx     T           XX - XX
  </code></pre>
  
  <p>I think I am looking for a solution using PLYR that can an output the above results in a nice dataframe.</p>
  
  <p>(The Puromycin only contains two numeric variables, but the solution I am looking for would work on a dataframe with many numeric variables)</p>
  
  <p><em>UPDATE - I will try to clarify what i mean.</em></p>
  
  <p>I would like to go from data that look like this:</p>
  
  <pre><code>Grouping variable   var1    var2    var3    var4    var5
  1           3   5   7   3   7
  1           3   7   5   9   6
  1           5   2   6   7   6
  1           9   5   7   0   8
  1           2   4   5   7   8
  1           2   3   1   6   4
  2           4   2   7   6   5
  2           0   8   3   7   5
  2           1   2   3   5   9
  2           1   5   3   8   0
  2           2   6   9   0   7
  2           3   6   7   8   8
  2           10  6   3   8   0
  </code></pre>
  
  <p>To a result dataframe that look like this:</p>
  
  <pre><code>"Mean in group 1"   "Mean in group 2"  "P-value of difference" "N"
  
  var1            ##          ##          ##          ##      
  var2            ##          ##          ##          ##  
  var3            ##          ##          ##          ##  
  var4            ##          ##          ##          ##  
  var5            ##          ##          ##          ##
  </code></pre>
  
  <p>Maybe it is something with mapply I am looking for because i want to split up my dataframe into dataframe1 and dataframe2 by a two-level factor, and apply a function( t-test) to the first parts of dataframe1 and dataframe2, and then a t-test on the second parts of dataframe1 and dataframe2, and then a t-test to the third parts of dataframe1 and dataframe2, and so on on all the column-pairs generated by the split by factor.</p>