IQR outlier detection

Outliers are certain points in the data set which deviate from the general trends in the dataset. There are several ways to detect outliers. In this problem, we will use the median absolute deviation method to find outliers. According to this method:

1. Find the Inter-quartile range [Q3 - Q1]
2. Upper range is computed as Q3 + 1.5*IQR
3. Lower range is computed as Q1 - 1.5*IQR
4. Values that have high values than upper range are suspected to be outliers.
5. Values that have low values than lower range are suspected to be outliers.

Complete the function that identifies the outliers and return them by applying the function on the input list.

Input Format

Number of testcases
N space separated integers as an input for each testcase

Output Format

Space separated integers but there isn't any space after the last element.
only outliers are printed

Example Input

2
1 1 2
10 10 6 9 4 5 7 1 8 929 100

Example Output

1 929 100

Note:

• The code for taking input is already taken care of.
• Make sure to print the outliers in the function itself in the required format.