Which data type would likely involve the use of surveys with numerical responses?

Quantitative data is characterized by numerical responses that can be measured and analyzed statistically. Surveys that yield quantitative data often contain scaled questions or items, where respondents can provide answers that are inherently numerical, such as ratings on a scale of 1 to 10 or the number of times they visit a healthcare provider in a month.

This type of data is essential in various fields, including healthcare research, because it allows researchers to perform statistical analyses, identify trends, and make data-driven decisions. Quantitative data can be subjected to various statistical tests and can be used to establish correlations, means, medians, and other numerical measures that provide a clear picture of the data being studied.

In contrast, qualitative data involves non-numerical responses that capture opinions, experiences, and feelings, which would not be suitable for surveys focused on numerical outcomes. Ordinal data, while it involves ordered categories, still does not directly imply numerical measurement that can be analyzed in the same way as quantitative data. Categorical data refers to variables that can be divided into different categories but do not possess a numerical context. Therefore, the most fitting choice for the data type involving surveys with numerical responses is indeed quantitative data.