When we describe and present the data we are telling a story or narrative. Quantitative stories are always about relationships. Numbers by themselves don’t mean anything unless they relate to something. They need to measure something meaningful.

You want your data to communicate with clarity. Your tables and charts ideally strike a balance on the complexity scale. Quantitative stories feature two types of data: quantitative and categorical. Your charts communicate quickly and with impact. How can you do these things? The first thing to do is to learn a bit more about data.

• Categorical Data / Qualitative Data (subjective or explanatory measures of qualities and characteristics)
• Quantitative Data (what, how many, and how often); Numeric

Quantitative values measure things and categories divide information into useful groups. Categorical items can be geographical, type, subtype, time, person, or something else. For example, Sales related to Time. Sales related to geographical regions. Expenses related to organizational structure. Market share related to companies. Quantitative data generally gives you the what, and qualitative data generally gives you the why.

Relationships

Quantitative stories always feature relationships. These relationships involve either:

1. Simple associations between quantities and categories – sales for each product, sales for each product category
2. More complex associations among multiple sets of quantitative values

Relationships Within Categories

According to Stephen Few, in his book Show Me The Numbers, on page 17, Categorical (qualitative) items can relate to one another in the following four ways:

• Nominal (discrete values with no intrinsic order; north south east west, street names, gender)
• Ordinal (the items have an order; small medium large; first second third; low average moderate high)
• Interval (items have a sequential series of numerical ranges that subdivide a larger range of quantitative values into smaller ranges; the difference between two values is meaningful; bins’ intervals are arranged in order; Jan Feb Mar)
• Hierarchical (multiple categories that are closely associated with each other; parent-to-child)

Relationships Between Quantities

What about relationships between quantities? Categorical items can relate to one another by virtue of the quantitative values associated with them. The quantitative values can be arranged to display the following relationships:

• Ranking. When you display the categorical items in order by value, either ascending or descending, you have ranked them.
• Ratio. A ratio compares two values by dividing one by the other.
• Correlation. A correlation compares two sets of paired values to determine whether increases in one corresponds to either increases or decreases in the other.

We have more information here on the post called Statistics.

We have more information here on a series called Data Analytics.

NOIR

Columns in a table or dataset are sometimes called attributes. These attributes are either qualitative or quantitative (numerical). NOIR stands for Nominal, Ordinal, Interval and Ratio. By the way, Noir is the French word for black.

Learn with YouTube

Here a basic YouTube on nominal, ordinal, interval and ratio called Nominal, Ordinal, Interval & Ratio Data: Simple Explanation With Examples.

The first post in this series is called An Introduction to Data.