Final answer:
Descriptive analytics involve summarizing data attributes using descriptive statistics, which can be displayed graphically or numerically. Inferential statistics can follow for deeper analysis. Cluster analysis can group data based on its specific characteristics.
Step-by-step explanation:
“Descriptive analytics” summarize activity or data based on certain attributes. This technique of organizing and summarizing data is a key aspect of descriptive statistics. The process can be accomplished through various means such as graphing or numerical means like computing an average. Descriptive statistics provide a summary of data, which can be further analyzed using inferential statistics. Such inferential techniques use the principles of probability to make determinations about the data and to judge the confidence level of these conclusions.
Additionally, in fields where a variety of communities or samples are studied, cluster analysis might be relevant. Cluster analysis is a set of techniques that build classifications of data, and the method adopted depends on the nature of the data. The characteristics of data, such as being hierarchical or reticulate, divisive or agglomerative, monothetic or polythetic, and qualitative or quantitative, influence the choice of cluster analysis technique.