Update src/content/docs/apm/apm-ui-pages/monitoring/transactions-page…

…-find-specific-performance-problems.mdx

Co-authored-by: alexa <81787716+akristen@users.noreply.github.com>

src/content/docs/apm/apm-ui-pages/monitoring/transactions-page-find-specific-performance-problems.mdx

@@ -48,7 +48,7 @@ The <DoNotTranslate>**Transactions**</DoNotTranslate> page also may include link
 
 ## Wall-clock time [#wall_clock_time]
 
-Wall-clock time measures "real-time elapsed" during a specific transaction. For example, let's say you're an engineer responsible for managing the checkout experience on an e-commerce site. You would like to understand how long it takes for a customer to add an item to their cart. The transaction took 15 seconds to complete but one minute in the real world or on the "wall clock" for the customer. This discrepancy in time could be because the function had to wait for network calls or other inputs and outputs, and that waiting time isn't considered in the system's transaction time. New Relic uses wall-clock time for all the transactions and then sums that value across all of the transactions.
+Wall-clock time measures "real-time elapsed" during a specific transaction. For example, let's say you're an engineer responsible for managing the checkout experience on an ecommerce site. You'd like to understand how long it takes for a customer to add an item to their cart. The transaction took 15 seconds to complete but one minute in the real world or on the "wall clock" for the customer. This discrepancy in time could be because the function had to wait for network calls or other inputs and outputs, and that waiting time isn't considered in the system's transaction time. New Relic uses wall-clock time for all the transactions and then sums that value across all of the transactions.
 
 In the above example, imagine that when a customer adds an item to their cart, the host has to make two requests to complete this work. One of these functions might take 3 seconds to complete, and the other takes 2 seconds, but because they occur simultaneously, the customer only had to wait 3 seconds. Because of this parallel work, you may see percentages over 100. For example, 100% would indicate that the execution time across all selected transactions equals the time expended when recording wall-clock time.