hotfix

Author: hamdaankhalid

statistical-experiments-and-testing.md

@@ -161,7 +161,8 @@ This algorithm let's you explore and exploit by promoting better performering gr
   1. Generete a uniformly distributed random number between 0 and 1.
   2. If the number lies between 0 and epsilon, flip a fair coin and show A if heads, else show B.
   3. If the number is greater than epsilon, show whichever A or B sample group that has had the highest response rate to date.
-Epsiolon is the single parameter that governs this algorithm. If epsilon is 1, we end up with a standard simple A/B experiment. If epsilon is 0 we get a purely greedy algorithm.
+
+Epsilon is the single parameter that governs this algorithm. If epsilon is 1, we end up with a standard simple A/B experiment. If epsilon is 0 we get a purely greedy algorithm.
 A more sophisticated algorithm would use Thompson's sampling.
 Bandit algorithms can efficiently handle 3+ treatments and move toward optimal selection of the "best". For traditional statistical testing procedures, the complexity of decision making for 3+ treatments far outstrips that of the traditional A/B test, and the advantage of bandit algorithms is much greater.