What Type of Data Is Most Commonly Used for a Statistical Table?


Larry Thompson

Statistics play a crucial role in various fields, ranging from scientific research to business analysis. Statistical tables are an effective way to summarize and present data in a concise and organized manner.

But what type of data is most commonly used for a statistical table? In this article, we will explore the different types of data that are frequently used in statistical tables.

Categorical Data:
Categorical data, also known as qualitative or nominal data, consists of categories or groups. This type of data cannot be measured on a numerical scale but can be classified into distinct categories. Examples of categorical data include gender (male/female), color (red/blue/green), and marital status (single/married/divorced).

Numerical Data:
Numerical data, also known as quantitative or continuous data, consists of numerical values that can be measured on a specific scale. This type of data allows for mathematical operations such as addition, subtraction, and averaging. Numerical data can further be divided into two subcategories:

1. Discrete Data:

Discrete data consists of whole numbers or values that are counted and are not infinitely divisible. Examples include the number of siblings someone has, the number of cars sold in a month, or the number of items in stock.

2. Continuous Data:

Continuous data consists of values that can take any real number within a given range.

These values are usually obtained through measurements and can be infinitely divided into smaller units. Examples include height, weight, temperature, and time.

Ordinal Data:
Ordinal data is a type of categorical data where the categories have an inherent order or ranking. While it may seem similar to numerical data at first glance, ordinal variables do not possess equal intervals between their values. Examples include educational attainment levels (elementary school/middle school/high school/college), customer satisfaction ratings (very dissatisfied/dissatisfied/neutral/satisfied/very satisfied), and star ratings (1 star/2 stars/3 stars/4 stars/5 stars).

Time-Series Data:
Time-series data is a type of numerical data that is collected and recorded over a specific period at regular intervals. This data is used to analyze trends, patterns, and changes over time. Examples include monthly sales figures, stock market prices, and weather data recorded daily.


In statistical tables, various types of data are commonly used to present information in a structured manner. Categorical data provides insights into different categories or groups, while numerical data allows for mathematical operations.

Discrete and continuous data further differentiate between whole numbers and infinitely divisible values. Ordinal data introduces an order or ranking among categories, while time-series data focuses on recording values over regular intervals.

By understanding the different types of data commonly used in statistical tables, you can effectively analyze and interpret the information presented. Remember to choose the appropriate type of table for your specific dataset to ensure clear communication and accurate representation of your findings.

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