Data Science

Mean, Median, and Mode - Measures of Central Tendency

Arun Murali

Tags: data-science; statistics; descriptive-statistics

🟪 1-Minute Summary

Mean (average), median (middle value), and mode (most frequent) are the three ways to describe where the “center” of your data lies. Mean is sensitive to outliers, median is robust to them, and mode works for categorical data. In interviews, you’ll be asked when to use each.

🟦 Core Notes (Must-Know)

Mean (Average)

[Content to be filled in]

Median (Middle Value)

[Content to be filled in]

Mode (Most Frequent)

[Content to be filled in]

When to Use Each

[Content to be filled in]

🟨 Interview Triggers (What Interviewers Actually Test)

Common Interview Questions

  1. “Your dataset has extreme outliers. Which measure of central tendency should you use?”

    • [Answer: Median]

  2. “When is mode more useful than mean or median?”

    • [Answer framework to be filled in]

🟥 Common Mistakes (Traps to Avoid)

Mistake 1: Always using mean by default

[Content to be filled in]

🟩 Mini Example (Quick Application)

Scenario

[Example with salary data to be filled in]

Solution

import numpy as np
import pandas as pd

# Example to be filled in

🔗 Related Topics

Navigation: