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

Descriptive statistics are the techniques specifically designed to summarize and describe the main features of a dataset. This includes measures of central tendency, such as mean, median, and mode, as well as measures of variability, such as range, variance, and standard deviation. By providing a simple summary and visualization of the data, descriptive statistics help researchers understand the basic patterns that exist within their datasets, making it easier to gain insights and communicate findings.

In contrast, inferential statistics involve making predictions or inferences about a population based on a sample of data. Predictive analytics focuses on using statistical techniques to predict future outcomes based on historical data, while data mining refers to the process of discovering patterns and knowledge from large amounts of data. Each of these methods serves distinct purposes and is used in different contexts, which is why they do not fit the specific role of summarizing and describing characteristics of datasets as effectively as descriptive statistics do.