What type of data is often used for statistical analysis and reporting?

Quantitative data is widely used for statistical analysis and reporting because it consists of numerical values that can be measured and analyzed mathematically. This type of data allows for the use of various statistical methods to identify patterns, correlations, and trends, thereby providing objective insights that can be used in decision-making processes. For instance, quantitative data can be collected through surveys, experiments, or observational studies, and can include metrics such as heights, weights, ages, or scores.

Statistical analysis often relies on the ability to perform calculations such as averages, percentages, and standard deviations—all of which require numeric input. This makes quantitative data particularly well-suited for producing clear and precise reports that may include charts, graphs, and tables to visually represent the findings, which further enhances understanding and communicability of the data. While qualitative, experiential, and descriptive data provide valuable insights, they are typically less suited for rigorous statistical analysis compared to quantitative data.