## What type of data is blood pressure?

Continuous data are numerical data that can theoretically be measured in infinitely small units. For example, blood pressure is usually measured to the nearest 2mm Hg, but could be measured with much greater resolution of difference. The interval measurement scale is intended for continuous data.

**Which are suitable for quantitative data?**

Histograms (similar to bar graphs) are used for quantitative data. Line graphs are used for quantitative data. Scatter graphs are used for quantitative data.

### What type of variable is eye Colour?

Eye color is another example of a nominal variable because there is no order among blue, brown or green eyes.

**What can quantitative data be used for?**

Quantitative data are used when a researcher is trying to quantify a problem, or address the “what” or “how many” aspects of a research question. It is data that can either be counted or compared on a numeric scale. Statistical analysis software, such as SPSS, is often used to analyze quantitative data.

## Is eye color qualitative or quantitative?

An important distinction between variables is between qualitative variables and quantitative variables. Qualitative variables are those that express a qualitative attribute such as hair color, eye color, religion, favorite movie, gender, and so on. The values of a qualitative variable do not imply a numerical ordering.

**What is the difference between quantitative and qualitative data?**

What’s the difference between qualitative and quantitative research? Quantitative data is information about quantities, and therefore numbers, and qualitative data is descriptive, and regards phenomenon which can be observed but not measured, such as language.

### What is an example of a quantitative research?

An example of quantitative research is the survey conducted to understand the amount of time a doctor takes to tend to a patient when the patient walks into the hospital.

**What is the definition of quantitative reasoning?**

By one definition, quantitative reasoning (QR) is the application of basic mathematics skills, such as algebra, to the analysis and interpretation of real-world quantitative information in the context of a discipline or an interdisciplinary problem to draw conclusions that are relevant to students in their daily lives.