Answer Big O Notation Exercises

Notes/Exercise/Questions/Exercise-01.md

@@ -6,4 +6,6 @@ function isLeapYear(year){
   return (year % 100 === 0) ? (year % 400 === 0) : (year % 4 === 0);
 }
 
-````
+````
+
+The time complexity for  `isLeapYear` is: `O(1)`. Regardless of the input the algorithm will still go through the same number of operations during operation.

Notes/Exercise/Questions/Exercise-02.md

@@ -11,4 +11,6 @@ const sumOfArray = (array) => {
   return sum;
 }
 
-```
+```
+
+The time complexity for  `sumOfArray` is: `O(n)`. The number of operations that will be used in the for loop will increase as the input increases.

Notes/Exercise/Questions/Exercise-04.md

@@ -1 +1,8 @@
-**Write a function that accepts an array of strings and return a new array that only contains the strings that start with the character 'd'. Use Big O Notation to describe the time complexity of the function.**
+**Write a function that accepts an array of strings and return a new array that only contains the strings that start with the character 'd'. Use Big O Notation to describe the time complexity of the function.**
+
+```js
+const returnString = (arr) => {
+        return arr.filter(string => string.toLowerCase().startsWith('d'));
+}
+```
+The above function will have a time complexity of `O(n)`. This is because the filteration operations will increase as the input increases.

Notes/Exercise/Questions/Exercise-05.md

@@ -11,4 +11,6 @@ const median (array) => {
   return array[middle];
 }
 
-```
+```
+
+The time complexity for  `median` is: `O(1)`. Regardless of the length of the input array accessing the middle elements will take constant time.