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DATA

NEXUS

In statistics, **data** refers to information collected for analysis. There are different types of data, which are categorized based on their nature and how they can be measured or classified. Understanding these types is essential for selecting the appropriate analysis method.

**Qualitative data** refers to non-numerical information that describes categories or characteristics. This type of data is typically grouped into categories.

**Example**: Eye colour, type of car, or gender.

**Quantitative data** refers to numerical information that can be measured or counted. It deals with quantities and can be expressed in numbers.

Quantitative data can be divided into two types: discrete and continuous data.

Discrete data can only take specific, separate values (often counts).

**Example**: Number of students in a class, number of cars in a car park.

Discrete data can be represented as:

\[x = \{0, 1, 2, 3, \dots\}\]

Continuous data can take any value within a given range (often measurements).

**Example**: Height, weight, time.

Continuous data can be represented as an interval:

\[x \in [0, \infty)\]

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