Discrete vs. Continuous Variables 🔢

🎯 Learning Objectives

By the end of this lesson, you will be able to:
✔ Define discrete and continuous variables
✔ Differentiate between them based on characteristics
✔ Identify real-world medical examples
✔ Understand why this distinction matters in statistics

1️⃣ Introduction

In medical research and clinical practice, quantitative data can be further classified into two main types:
✅ Discrete variables
✅ Continuous variables

This classification helps in choosing the right statistical methods and data presentation formats.

2️⃣ Discrete Variables

Definition:

• Variables that take distinct, separate values (usually whole numbers).
• Cannot take fractions or decimals.
• Countable values.

✔ Key Features:

• Counted, not measured
• Gaps between values
• Often represent counts of events or objects

✔ Medical Examples:

• Number of hospital visits: 0, 1, 2, 3…
• Number of teeth extracted: 5, 6, 7
• Number of children in a family: 2, 3, 4

3️⃣ Continuous Variables

Definition:

• Variables that can take any value within a given range, including fractions and decimals.
• Measured with precision.

✔ Key Features:

• Measured, not counted
• Infinite possible values within an interval
• Can have decimal values

✔ Medical Examples:

• Height: 170.2 cm
• Weight: 68.5 kg
• Blood pressure: 120.5 mmHg
• Blood glucose level: 92.3 mg/dL

4️⃣ Comparison Table

5️⃣ Clinical Relevance

Why is this important?

• Graphical representation:
  • Discrete → Bar charts
  • Continuous → Histograms
• Statistical tests: Some tests require continuous data, others work with discrete data.

6️⃣ Quick Check: Test Your Understanding ✅

Q1: Which of the following is a discrete variable?
a) Body temperature
b) Number of surgeries
c) Serum cholesterol
d) Height

👉 Answer: b) Number of surgeries

Q2: Blood glucose level is an example of:
a) Discrete variable
b) Continuous variable

👉 Answer: b) Continuous variable

✨ Key Takeaways

• Discrete variables = Countable, whole numbers (e.g., number of patients)
• Continuous variables = Measurable, can take decimal values (e.g., weight, height)
• Correct classification ensures appropriate statistical analysis.