What kind of information is typically provided by descriptive statistics?

Descriptive statistics are fundamental tools in data analysis that summarize and provide insights into the main features of a dataset. These include measures such as means (averages), medians, modes, ranges, and standard deviations, which are useful for understanding the central tendency and variability within the data. By presenting information in a clear and straightforward manner, descriptive statistics allow researchers to convey essential characteristics of the data without making inferential claims or comparisons.

For example, if a researcher is studying crime rates in different neighborhoods, descriptive statistics would allow them to calculate the average crime rate, the most frequently occurring offense, or the range of crime rates observed in the study. This provides a clear snapshot of the data, making it easier for decision-makers to identify trends or draw preliminary insights.

In contrast, the other options involve different types of analyses. Theories about criminal behavior would typically involve inferential or theoretical frameworks rather than straightforward summaries of observed data. Comparative analyses between groups would require inferential statistics, as it involves making comparisons and testing hypotheses. Finally, detailed case studies would focus on individual variability rather than summarizing larger datasets, which is the essence of descriptive statistics.