Your insightful differentiation between data analytics and statistics underscores the nuanced yet critical distinctions between these two data$-$oriented disciplines. Statistics, with its focus on drawing conclusions and making predictions based on data analysis, serves as the foundational bedrock upon which the broader field of data analytics builds. Data analytics, encompassing a wider spectrum of activities including data collection, processing, and interpretation, extends beyond traditional statistical methodologies to incorporate advanced tools like machine learning and artificial intelligence, enabling the extraction of deeper insights from complex datasets.

The delineation of analytics tools into descriptive, predictive, and prescriptive categories elucidates the various ways in which data can be leveraged to inform business strategy and operations. Descriptive analytics provides a backward$-$looking view to understand past performances, predictive analytics offers a forward$-$looking perspective to forecast future trends, and prescriptive analytics delivers actionable recommendations based on these forecasts, guiding businesses toward optimal decision$-$making paths.

The example of a retail business utilizing sales data to adjust inventory and marketing strategies exemplifies the practical application of data analytics in optimizing business operations. Such data$-$driven approaches not only enhance decision$-$making but also streamline operations and improve customer experiences, ultimately contributing to business growth and success.

As a marketing manager, the application of data analytics in understanding customer behavior, evaluating campaign effectiveness, and guiding strategic decisions is indispensable. The adoption of data analytics within your organization promises significant benefits, from improved performance and operational optimization to the identification of new growth opportunities, highlighting the transformative potential of data analytics in shaping business strategies and outcomes.

Both data analytics and statistics involve analyzing and interpreting data. However, data analytics assist in making important decisions by identifying critical facts and trends. Statistics consists of applying a methodology to do data analysis with the intention of estimation or inference. Both require identifying data categories.

Can you show how to use the Excel formula to compute the Geometric mean of the following set of numbers: $13,15,16,$ and $28?$