Partial 325 Fix P2 - Updated vectvshash.png Added

pretext/AlgorithmAnalysis/HashTableAnalysis.ptx

@@ -173,7 +173,7 @@ for i in range(10000,1000001,20000):
             </code></program></statement>
         </task>
     </exploration>
-    <p><xref ref="fig-vectvshash-cpp"/> summarizes the results of running
+    <p><xref ref="fig-vectvshash2-cpp"/> summarizes the results of running
         <xref ref="expl-hashtable-analysis"/>. You can see that the hash table is consistently
         faster. For the smallest vector size of 10,000 elements a hash table is
         89.4 times faster than a vector. For the largest vector size of 990,000
@@ -186,16 +186,16 @@ for i in range(10000,1000001,20000):
         contains operation took 0.004 milliseconds and for the hash table size
         of 990,000 it also took 0.004 milliseconds.</p>
 
-    <figure xml:id="fig-vectvshash-cpp">
-        <caption>Comparing the <c>contains</c> operation for C++ vectors and Hash Tables</caption>
-            <image source="AlgorithmAnalysis/vectvshash.png" width="90%">
-                <description><p>The primary take away is that the graph for vectors shows an almost linear climb from
-                0 elements taking almost 0 time to 1,000,000 elements taking approximately 45 seconds. For hash
-                tables, the function is also linear, but shows almost 0 slope from 0 elements to 1,000,000 elements
-                in the hash table. This reflects the linear versus constant time growth of the two
-                functions.</p></description>
-            </image>
-    </figure>
+<figure xml:id="fig-vectvshash2-cpp">
+    <caption>Comparing the <c>contains</c> operation for C++ vectors and Hash Tables</caption>
+        <image source="AlgorithmAnalysis/vectvshash2.png" width="90%">
+            <description><p>The primary take away is that the graph for vectors shows an almost linear climb from
+            0 elements taking almost 0 time to 1,000,000 elements taking approximately 69 microseconds. For hash
+            tables, the function is also linear, but shows almost 0 slope from 0 elements to 1,000,000 elements
+            in the hash table, staying at approximately 2 to 3 nanoseconds throughout. This reflects the linear
+            versus constant time growth of the two functions.</p></description>
+        </image>
+</figure>
 
     <p>Since C++ is an evolving language, there are always changes going on
         behind the scenes. The latest information on the performance of C++