Descriptive data analysis aims to provide information about what?

Descriptive data analysis focuses on summarizing and interpreting data to give a clear overview of its main characteristics. This type of analysis typically reveals the frequency of specific occurrences, such as how often a certain event happens or how many times a particular item is sold within a certain period.

In the context of choices provided, the emphasis of descriptive analysis is on quantifying data—this could include metrics like averages, counts, and percentages that help to organize and describe the primary features of the data set clearly and concisely. By understanding the frequency of occurrences, businesses can identify patterns and trends in consumer behavior and responses, which can be essential for informed decision-making.

For example, if a real estate agency conducts descriptive analysis of property sales data, it can determine how many properties were sold in a specific month or which areas are most popular among buyers. This information is vital for strategizing future marketing efforts or pricing strategies.

The other choices propose different focuses, such as overall market trends over time or consumer feelings and motivations, which are elements of higher-level analysis, such as inferential statistics or qualitative research, rather than descriptive data analysis itself. Descriptive analysis does not delve into the underlying motivations or emotional responses of consumers; it simply captures and summarizes the patterns present