Mathematics_For_DataScience

Maths Study for DS, ML, and NLP A Weekly Plan for MATHS Study

• Week 1: DESCRIPTIVE STATISTICS
  • GOALS: Understand and apply the basics of basic summary used to describe datasets
• Measure of Central Tendency
  • mean
  • median
  • mode
• Measure of Dispersion
  • Range
  • Variance
  • Standard Deviation
  • Quantile(75th percentile - 25th percentile)

Ouliers

- 🧪 What Are Outliers?

• Outliers are unusually high or low values in your dataset that differ significantly from most other values.

• Example:

• In this list of ages:

  • [22, 24, 25, 26, 150] — the 150 is clearly an outlier.

📉 How Outliers Affect Measures (with Examples)

1. Mean – ✅ Affected by outliers

• The mean (average) increases or decreases significantly if there's an outlier.

• 📌 Example:

• Ages:

• [25, 26, 27, 28, 29] → Mean = 27

• [25, 26, 27, 28, 100] → Mean = 41.2 ← Big change due to one outlier

b Insight: Mean is not robust to outliers. It can give a misleading picture.

2. Median – ✅ Not affected much

• The median is the middle value, so it’s stable even with outliers.

• 📌 Example:

• [25, 26, 27, 28, 100] → Median = 27

• Same median as before!

3. Mode – ✅ Not affected

• It’s just the most frequent value, so outliers don’t matter here.

4. Standard Deviation & Variance – ✅ Strongly affected

• These measure spread of data.

• Outliers make the spread appear wider than it actually is.