Types of Data – Qualitative vs. Quantitative 📊

🎯 Learning Objectives

By the end of this lesson, you will be able to:
✔ Define qualitative and quantitative data
✔ Identify the key differences between them
✔ Recognize examples of each type in a medical context

1️⃣ Introduction

In medical research and clinical practice, data is everywhere—patient records, lab reports, clinical trials. To analyze data correctly, we must first understand what type of data we are dealing with.

Data can be broadly classified into two main types:
✅ Qualitative (Categorical)
✅ Quantitative (Numerical)

2️⃣ Qualitative Data (Categorical Data)

Qualitative data describes qualities, categories, or characteristics—things that cannot be measured numerically in a meaningful way.

✔ Key Features

• Represents categories or labels
• No true numeric value (cannot add, subtract, average)
• Answers questions like: “What type?” or “Which category?”

✔ Examples in Medicine

• Blood group: A, B, AB, O
• Gender: Male, Female
• Type of disease: Diabetes, Hypertension, Asthma

3️⃣ Quantitative Data (Numerical Data)

Quantitative data deals with numbers and measurements—values that can be counted or measured.

✔ Key Features

• Represents numerical values
• Can be used for mathematical calculations (mean, median, etc.)
• Answers questions like: “How much?” or “How many?”

✔ Examples in Medicine

• Age: 25 years
• Blood pressure: 120/80 mmHg
• Heart rate: 78 beats per minute
• Serum glucose level: 95 mg/dL

4️⃣ Comparison Table

5️⃣ Quick Check: Test Your Understanding ✅

Q1: Which of the following is qualitative data?
a) BMI
b) Pulse rate
c) Blood group
d) Serum cholesterol

👉 Answer: c) Blood group

Q2: Age measured in years is an example of:
a) Qualitative data
b) Quantitative data
👉 Answer: b) Quantitative data

✨ Key Takeaways

• Qualitative data = Categories (no numeric meaning)
• Quantitative data = Numbers (can calculate averages)
• Understanding the type of data is the first step in choosing the right statistical test!