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Understanding the types of statistical data is crucial for analysis. Discrete data is countable and finite, like the number of students in a class. Continuous data, such as temperature, can take any value within a range and requires precise measurement. Grouped data organizes continuous data into intervals, simplifying interpretation. This overview covers how to distinguish these data types and their best graphical representations, including bar charts for discrete data and histograms for continuous data.

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## Discrete Data

### Definition

Discrete data consists of countable items, such as the number of students in a class

### Examples

Number of leaves on a tree

The number of leaves on a tree is an example of discrete data

Number of cars in a parking lot

The number of cars in a parking lot is an example of discrete data

### Representation

Discrete data is typically represented graphically by bar charts or pie charts

## Continuous Data

### Definition

Continuous data includes measurements that can take on any value within a continuum, like the temperature on a thermometer

### Examples

Distance

Distance is an example of continuous data

Time

Time is an example of continuous data

Temperature

Temperature is an example of continuous data

### Representation

Continuous data is best visualized using line graphs, histograms, or scatter plots

## Grouped Data

### Definition

Grouped data is continuous data that has been organized into categories, or intervals, to simplify analysis and interpretation

### Examples

Age groups

Age groups are an example of grouped data

Weight categories

Weight categories are an example of grouped data

### Representation

Grouped data is typically represented graphically by histograms or frequency polygons

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