Difference Between Descriptive and Inferential Statistics

Aryugyan November 6, 2025

Statistics is broadly divided into two main categories: Descriptive Statistics and Inferential Statistics. Both are used to analyze data, but their purpose and usage are different.

1. Descriptive Statistics

Meaning

Descriptive Statistics refers to organizing, summarizing, and presenting data in a meaningful way.
It describes the characteristics of the collected dataset without making any general conclusions beyond the data.

Purpose

To explain what the data shows.

Common Operations

Calculating averages
Creating frequency tables
Generating graphs (e.g., histograms, bar charts, pie charts)

Common Tools

Measure Type	Techniques
Central Tendency	Mean, Median, Mode
Variability	Range, Variance, Standard Deviation

2. Inferential Statistics

Meaning

Inferential Statistics involves using data from a sample to make predictions or generalizations about a larger population.

Purpose

To draw conclusions, test hypotheses, and make decisions based on data.

Common Operations

Hypothesis testing
Confidence intervals
Correlation & regression analysis

Goal

To infer characteristics of a population based on a sample.

✅ Example to Understand

Suppose a university has 10,000 students (population).
You collect the height of only 100 students (sample).

Type	What You Do	What It Means
Descriptive Statistics	Calculate the average height of these 100 students	You are just describing the sample data.
Inferential Statistics	Use that sample’s average to estimate the average height of all 10,000 students	You are making a prediction about the full population.

🟢 In Short

Feature	Descriptive Statistics	Inferential Statistics
Purpose	Describe sample data	Make predictions about population
Based On	Only the observed data	Sample → Population
Techniques	Mean, Median, Mode, Graphs	Hypothesis Tests, Confidence Intervals, Regression
Output	Summary of data	Conclusion or Decision