What is Quantitative Data?

Definition: Quantitative data is any data that can be represented and measured numerically. For a variable to be quantitative it must have numerical values.

What Does Quantitative Data Mean?

Quantitative data is easier to measure and study than qualitative data since numeric values are easier to analyze. The advantages of quantitative data is that it can be objectively measured and presented and it explains the observed phenomena more accurately since numerical values are obtained through systematic process of observation and recording, not appreciations or opinions.

Quantitative data serves the statistical purpose of representing volumes, frequencies, number of appearances and values of the variables being observed. With quantitative data, objective trends can be identified to develop projections and statistical forecasting models.

In business, quantitative data is much more used than qualitative data since it is more reliable. This data is regularly employed in fields such as finance, marketing and production to study the company’s behavior and performance from different perspectives. The disadvantage of quantitative data is that some situations can’t be explained by numbers and therefore, the need for both quantitative and qualitative data to complement each other to increase the accuracy of any research project.

Example

The Finance Manager of a company called Sugar Tree Co. a company that produces sugar for retail and commercial clients is interested in finding out the current price trend of some of the most common raw materials the company employs for its manufacturing processes. The manager gathered a team of two of his best analysts to research historical prices from the last 10 years to understand how the market has behaved for each of the commodities he selected.

In order to fulfill this task, the analysts must gather the quantitative data (past and current prices) to develop some analytics. The manager asked for averages, seasonality and drivers for each of these commodities in order to get a better grasp of how the market looks like for each of them so he can develop some forecasting models for planning purposes.