Detect Outliers

A medium Python interview practice problem on DataDriven. Write the Python and run it against test cases, with instant feedback.

Domain
Python
Difficulty
medium
Seniority
L4

Problem

Given a list of numbers and multiplier k, compute the mean. Return the sorted list of indices where the value exceeds k * mean.

Most values are normal. Some are suspicious.

Example 1

Input:

values = [10,12,11,50,9,13,45], k = 2

Output:

[3,6]

Example 2

Input:

values = [1,1,1,1], k = 2

Output:

[]

Worked solution and explanation

Why this problem exists in real interviews

Flagging values that deviate from the mean by a threshold factor is a basic statistical filtering operation used in monitoring pipelines. It tests two-pass processing: compute the mean first, then filter.

Break down the requirements

Step 1: Compute the mean of the list

Sum all values and divide by the count. This requires a first pass through the data.

Step 2: Find indices where the value exceeds k times the mean

In a second pass, compare each value against k * mean and collect indices that exceed it.

The solution

Two-pass mean computation and threshold filter
def detect_outliers(values, k):
    total = 0
    for v in values:
        total += v
    mean = total / len(values)
    threshold = k * mean
    result = []
    for i in range(len(values)):
        if values[i] > threshold:
            result.append(i)
    return result

Common follow-up questions