AI Basics with AK

Season 03 - Introduction to Statistics

Arun Koundinya Parasa

Episode 03

Descriptive Statistics — Mean, Median, Mode, Range, Variance, Standard Deviation

Agenda

• What are Descriptive Statistics?
• Understanding Mean, Median, Mode
• Exploring Range, Variance, and Standard Deviation

What are Descriptive Statistics?

Descriptive statistics summarize and describe the main features of a dataset.

• They give us a snapshot of the data.
• Help us understand distribution and spread.
• Are the foundation for all data analysis. 🧠 Think of them as the storytellers of your data. ✨

Measures of Central Tendency

Mean

• The average value.

• Sum of all values divided by count.

• Sensitive to outliers.

Median

• The middle value in ordered data.

• Not affected by extreme values.

• Splits data into two halves.

Mode

• The most frequently occurring value.

• Can be more than one mode.

• Useful for categorical data. ## Measures of Spread (Variability)

Range

• Difference between max and min.

• Simplest measure of spread.

• Doesn’t capture distribution well.

Variance & Standard Deviation

• Variance: average squared deviation from mean.

• Standard Deviation: square root of variance.

• Both measure how data spreads around the mean.

Interactive Example Dataset & Visualizations

Mean, Median & Mode Concept

Mean

graph TD
  A[Add All Numbers] --> B[Count How Many Numbers]
  B --> C[Divide Total by How Many]
  C --> D[That's the Mean!]

Median

graph TD
  A[Put Numbers in Order] --> B[Find the Middle One]
  B --> C[That's the Median!]

Mode

graph TD
  A[Look at All Numbers] --> B[Find the Number That Shows Up the Most]
  B --> C[That's the Mode!]

Visualizing Range

Highlighting minimum and maximum scores to demonstrate range.

Range Concept

graph TD
  A[Look at All Numbers] --> B[Find the Smallest Number]
  A --> C[Find the Biggest Number]
  B --> D[Subtract Smallest from Biggest]
  C --> D
  D --> E[That's the Range!]

Visualizing Variance and Standard Deviation

Variance & Standard Deviation Concept

graph TD
    B[Calculate Mean] --> C[For Each Data Point:<br>Deviation = Data Point - Mean]
    C --> D[Square Each Deviation]
    D --> E[Average of Squared Deviations = <br> Variance]
    E --> F[Square Root of Variance = <br> Standard Deviation]

Why Variance and Std Dev Matter?

• They tell us if data points are close or spread out.

• Smaller std dev → data tightly clustered.

• Larger std dev → data more spread, more variability.

• Crucial for risk assessment, quality control, and AI model evaluation.

Summary

• Mean, median, and mode are ways to find the “center” of data.

• Range, variance, and standard deviation describe data spread.

• These basics are building blocks for deeper statistics and AI.

Thank You

Thank you for joining this episode on Descriptive Statistics.