Statistics Data Driven Decision Making

It is known that there are two data types that are utilized to evaluate and draw meaningful conclusions through statistics, population and sample data. These two data types are utilized to formulate end conclusions of data that is to be collected and data that is to be reviewed. The description of population data can best be explained, as the complete collection of all data that is to be queried/collected and reviewed. Sample data, a subset of population data, is the partial collection and review of all data that is to be queried. The relationship of these two data types is simple; sample data is represented as a reflection of the population data and shares a common goal in this comparison through statistics. This can also either be represented as a part or as a whole of all data being evaluated. However we tend to utilize sample data more often than population data primarily as a result that sample data is utilized to formulate a coherent approach to drawing meaningful conclusions about the population. We utilize this through random sampling of population data to gather and make an assumption based on the population. This can kind of draw the conclusion that sample data and population data go hand in hand. As an example if we utilize “Culture Matters: A Survey Study of Social Q&A Behavior” an article which conducted, in 2009, a social survey of questions and answers based on cultural behaviors, we can come to find relatable data that can be identified through the understanding of sample and population data. An overview of this article notes that sample data was collected from four countries and turned overs responses from 933 people, of the population, who held similar job roles and were employed by a singular organization. This was completed to ascertain an understanding of what motivated an individual’s response to ask and answer questions while accessing a social network site. In this response the United States and the United Kingdom provided data which