# Descriptive Statistics vs. Inferential Statistics: What's the Difference?

Edited by Aimie Carlson || By Harlon Moss || Updated on October 15, 2023
Descriptive statistics summarize and organize data, while inferential statistics make predictions or inferences about a population based on sample data.

## Key Differences

Descriptive statistics provide a summary of the main aspects of the data, offering a snapshot of its main characteristics. They are used to describe the basic features of data in a study, such as mean, median, mode, and range. Inferential statistics, on the other hand, use sample data to make inferences or predictions about a population or larger dataset.
Descriptive statistics are typically straightforward and simple to compute. They provide a foundation for understanding a dataset's distribution, central tendency, and spread. Inferential statistics take a step further by making predictions or decisions about a population based on the properties of a sample.
Descriptive statistics are most commonly used when the total set of data is available. They allow for clear and concise understanding of data by breaking it down into simpler summaries. Inferential statistics are used when one wants to draw conclusions about a larger group from a smaller sample set.
Descriptive statistics focus primarily on describing, presenting, and interpreting a given set of data in its entirety. Inferential statistics, conversely, focus on drawing conclusions, making predictions, and testing hypotheses about populations based on samples.

## Comparison Chart

### Purpose

Summarize and organize data
Make predictions or inferences based on sample data

Entire dataset
Sample data

### Main Techniques

Measures of central tendency, dispersion, etc.
Hypothesis testing, confidence intervals, etc.

### Outcome

Summary of data characteristics

### Dependency

Doesn't depend on probability theory
Relies heavily on probability theory

## Descriptive Statistics and Inferential Statistics Definitions

#### Descriptive Statistics

Methods that provide insight into specific characteristics of data.
By employing descriptive statistics, the researcher identified outliers in the dataset.

#### Inferential Statistics

Procedures that allow conclusions about larger datasets from samples.
Inferential statistics showed a likely increase in future market demand.

#### Descriptive Statistics

Techniques used to describe and summarize data.
She used descriptive statistics to provide a general overview of the test scores.

#### Inferential Statistics

Techniques to make predictions about a population based on sample data.
She used inferential statistics to estimate the average income of city residents.

#### Descriptive Statistics

The process of organizing data into meaningful patterns.
Using descriptive statistics, he found that sales peaked during summer months.

#### Inferential Statistics

Techniques to derive conclusions from data subject to random variation.
The study used inferential statistics to determine the correlation between variables.

#### Descriptive Statistics

Tools that help in determining the distribution and tendencies in datasets.
Descriptive statistics showed the majority of students scored above 70%.

#### Inferential Statistics

Tools that use probability to make generalizations.
Through inferential statistics, it was deduced that the treatment was effective for 90% of the population.

#### Descriptive Statistics

Quantitative summaries of features within a dataset.
The report began with descriptive statistics outlining the demographic breakdown.

#### Inferential Statistics

Methods used to test hypotheses and make estimations.
With inferential statistics, he concluded that the drug had a significant effect.

## FAQs

#### How do inferential statistics differ?

Inferential statistics make predictions or inferences about larger populations based on sample data.

#### What type of data do inferential statistics typically work with?

Inferential statistics work with sample data to draw conclusions about a larger population.

#### Can descriptive statistics provide predictions?

No, descriptive statistics only describe and summarize data without making predictions.

#### What's a common tool in descriptive statistics?

Measures of central tendency, like mean, median, and mode, are common in descriptive statistics.

#### What is the main purpose of descriptive statistics?

Descriptive statistics aim to summarize and organize data.

#### Can descriptive statistics be used on a sample?

Yes, descriptive statistics can be applied to both samples and entire datasets.

#### Are histograms used in descriptive statistics?

Yes, histograms are used in descriptive statistics to show data distributions.

#### Can inferential statistics confirm causal relationships?

While they can suggest relationships, inferential statistics can't confirm causality without controlled experiments.

#### Are bar charts a tool in descriptive statistics?

Yes, bar charts are a graphical method used in descriptive statistics to visualize data distribution.

#### What's an example of a descriptive statistic?

Calculating the average age of a group is an example of a descriptive statistic.

#### What's a common outcome of inferential statistics?

Common outcomes include hypothesis testing results, confidence intervals, and predictions.

#### Can inferential statistics determine the likelihood of an event?

Yes, inferential statistics often estimate probabilities or likelihoods of events.

#### How are descriptive statistics presented?

They can be presented numerically or graphically, like in tables or charts.

#### Are inferential statistics based on probability?

Yes, inferential statistics heavily rely on probability theory to make predictions and test hypotheses.

#### Do descriptive statistics involve complex calculations?

Typically, they involve straightforward calculations, like averages or percentages.

#### Which type of statistics provides more detailed data insight?

While descriptive statistics provide a basic data summary, inferential statistics delve deeper into data patterns and relationships.

#### What's a foundational concept in inferential statistics?

The concept of a "population" and a "sample" is foundational in inferential statistics.

#### Do inferential statistics require assumptions?

Often, yes. Inferential statistical tests usually have underlying assumptions that need to be met for valid results.

#### Do inferential statistics always guarantee accurate predictions?

No, predictions from inferential statistics come with a degree of uncertainty and are based on probabilities.

#### When are inferential statistics most commonly used?

Inferential statistics are used when one wants to generalize findings from a sample to a larger population.