What type of analysis involves looking at relationships within data?

The correct answer focuses on analyzing relationships within data, which is a central aspect of understanding how different variables interact with each other. While the term "Analyzing Data" is quite broad and can encompass various methods of examination, it specifically implies a detailed study of the data's components, including the relationships and patterns between them.

For instance, when analyzing data, one may look at correlations, trends, and dependencies among various data points. This enables researchers or analysts to draw conclusions or make predictions based on the observed relationships, which is essential in fields such as social science, market research, and public health.

Descriptive analysis focuses on summarizing data without delving into relationships. It helps in presenting the basic features of the data but does not explore how one variable may impact another. Statistical analysis, on the other hand, could certainly include methods to examine relationships, but it generally refers to the application of statistical methods to analyze data quantitatively. Comparative analysis specifically involves contrasting two or more datasets to find similarities or differences, rather than solely looking at internal relationships.

Therefore, selecting "Analyzing Data" underscores the importance of examining the relationships that may exist among different datasets, which is crucial for interpretation and understanding within the Community and Family Studies context.