# What are the 7 types of data?

There are seven types of data: categorical, ordinal, interval, ratio, numerical, textual, and geographical.

Categorical data is data that cannot be measured on a numerical scale and is instead classified into distinct groups. This type of data is often used to categorize people into groups such as “male” and “female”.

Ordinal data is categorical data that can be ordered from least to greatest. Examples of ordinal data include “low,” “medium,” and “high” or “poor,” “average,” and “excellent” ratings.

Interval data is numerical data that can be measured on a scale, such as temperature. Interval data can be ordered and can be used to compare one unit to another.

Ratio data is scaled data with a fixed point of origin, meaning that the zero point always represents the absence of the characteristic being measured. Examples of ratio data include height, weight, and time.

Numerical data is any data that can be represented in the form of numbers. This includes any type of data that can be quantified, such as numerical scores or measurements.

Textual data is data that is represented in the form of words or phrases. Examples of textual data include comments, articles, and tweets.

Geographical data is data that is associated with a physical location or address. This type of data is often used to map locations and generate location-based data visualizations.

## How many main types of data are there?

There are four main types of data: numerical, categorical, ordinal, and text data. Numerical data, also known as quantitative data, is data that can be counted, measured, and compared numerically. Examples of numerical data include temperatures, ages, sizes, heights, weights, and distances.

Categorical data, also known as qualitative data, is data placed into a category or label. Categorical data can encompass any type of data that does not have a numerical value. Examples of categorical data include gender, marital status, color, religion, and animals.

Ordinal data is data that is placed into an order. Ordinal data can be ordinal in nature, meaning that is placed in a rank or order, or numerical in nature, meaning that is has a numerical value. Examples of ordinal data include rankings or ratings (e.g.

from 1-10), scales (e.g., from 1-5), and time (e.g., sunrise to sunset). Text data is any type of data that is represented using words or sentences. Text data is usually unstructured, meaning that it is not organized in any specific structure.

Examples of text data include comments, articles, blog posts, emails, articles, and reviews.

## What data types explain with example?

Data types refer to a classification of data that indicates how the data should be handled, stored and manipulated.

Data types can be split into two main categories: Primitive Data Types and Composite Data Types. Primitive data types are basic types which form the base of all programming. Common primitive data types include integers (34, -5, 0, etc.

), floating-point numbers (2.71828, -3.14159, etc. ), characters (x, z, Y, etc. ), strings (“Hello world! “, “Hello! “, etc. ), and Boolean values (true, false, etc. ).

Composite data types are the collection of primitive data types. Common composite data types include tuples (an ordered collection of objects), lists (an ordered collection of objects, often of mixed types), dictionaries (an unordered collection of key-value pairs), sets (an unordered collection of unique objects), dataframes (for relational data types, like in a database), and objects (that contain properties/methods).

For example, a data frame might look something like this:

Name Age Gender Mailing List Member

John 34 M Yes

Mary 29 F No

Joe 25 M Yes

In this example, the data types for each column are indicated. Name is a string, Age is an integer, Gender is a character, and Mailing List Member is a boolean value.

## What are the two 2 qualitative data collection techniques?

The two qualitative data collection techniques are interviews and focus groups. Interviews consist of a researcher gathering information on a specific topic through an in-depth conversation with an individual or a small group of individuals.

This type of data collection provides insight into the values, beliefs, and experiences of those involved in the study. Focus groups consist of researchers bringing together a small group of individuals to discuss a particular topic.

This type of data collection allows for a researcher to hear varied perspectives on the same topic from different people, as well as to observe the dynamic between group members.