int mid = firstIndex + (lastIndex-firstIndex)/2 , will give you the mid of the array.

Table of Contents

## How do you find the median of an array in Java?

- public class MedianFinder {
- public static void main(String[] args) {
- int[] values = { 2, 3, 6, 12, 15, 34, 65, 78, 99 };
- double median = median(values);
- println(“Median is : ” + median);
- values = { 2, 3, 6, 12, 15, 34, 65, 78};
- median = median(values);

## How do you find the mid value in Java?

- public class MiddleDidgitNumberExample1.
- {
- //function that finds the mid-digit.
- static int middleDigitNumber(int mid_digit)
- {
- //determines the total number of digits or length of the given number.
- int total_digits = (int)Math.log10(mid_digit) + 1;
- //determines the middle digit.

## How do you find the median of time?

To find the median of an unsorted array, we can make a min-heap in O(nlogn) time for n elements, and then we can extract one by one n/2 elements to get the median. But this approach would take O(nlogn) time.

## How do you find the median?

Count how many numbers you have. If you have an odd number, divide by 2 and round up to get the position of the median number. If you have an even number, divide by 2. Go to the number in that position and average it with the number in the next higher position to get the median.

## How do you find the middle element of an arrayList?

So, presuming you want the “middle” element (i.e. item 3 in a list of 5 items — 2 items on either side), it’d be this: Object item = arrayList. get((arrayList. size()/2)+1);

## How do you find the middle of an array?

8 Answers. int mid = firstIndex + (lastIndex-firstIndex)/2 , will give you the mid of the array. In your original code, you were not checking whether the length of nums be even or odd.

## How do you find the middle number in an array?

- if(n%2==1)
- If the number of elements is odd then, the center-most element is the median.
- m=a[(n+1)/2-1];
- Else, the average of the two middle elements.
- m=(a[n/2-1]+a[n/2])/2;

## Can you find the median in linear time?

We have quickselect, an algorithm that can find the median in linear time given a sufficiently good pivot. … Combining the two, we have an algorithm to find the median (or the nth element of a list) in linear time!

## How do you find the median class?

For this, we must know how to find the median class of grouped data. To do so, we are required to find the cumulative frequencies first and then calculate the value of n/2. Now, the median class is the group where the cumulative Frequency has equal value to n/2.

## How do you find the median of a set of data?

- Arrange the data points from smallest to largest.
- If the number of data points is odd, the median is the middle data point in the list.
- If the number of data points is even, the median is the average of the two middle data points in the list.

## What is the easiest way to find the median?

To find the median, put all numbers into ascending order and work into the middle by crossing off numbers at each end. If there are a lot of items of data, add 1 to the number of items of data and then divide by 2 to find which item of data will be the median.

## What is the fastest way to find the median?

## How do you find the mean and median?

The mean (informally, the “average“) is found by adding all of the numbers together and dividing by the number of items in the set: 10 + 10 + 20 + 40 + 70 / 5 = 30. The median is found by ordering the set from lowest to highest and finding the exact middle. The median is just the middle number: 20.

## How do you find the middle element in a circular linked list?

Traverse linked list using two pointers. Move one pointer by one and the other pointers by two. When the fast pointer reaches the end slow pointer will reach the middle of the linked list.

## What is the time complexity for finding the middle node of a linked list?

The running time of finding the middle element this way with two pointers is O(n) because once we pass through the entire linked list of n elements, the slower pointer is at the middle node already.