Which statistical techniques are used to summarize and detail the characteristics of a dataset?

Descriptive statistics are the branch of statistics that provides methods for summarizing and detailing the characteristics of a dataset. This includes techniques such as calculating measures of central tendency (like mean, median, and mode), measures of variability (like range, variance, and standard deviation), and presenting data visually through graphs and charts. These tools allow researchers to convey the essential features of the data in a straightforward way, making it easier to understand and interpret the dataset.

In contrast, inferential statistics focus on making inferences or predictions about a population based on sample data, rather than merely summarizing the data itself. Experimental methods pertain to designing and conducting experiments to gather data, while convenience sampling involves selecting a sample that is easy to reach, which may not provide a representative view of the entire population. Thus, these alternatives do not directly address the summarization of dataset characteristics in the same way descriptive statistics do.