1: Describing Data and Ethics

Overview Section

When starting on the journey of learning statistics one of the first things that comes to mind are the controversial ways in which statistics are used. This elicits a conversation around the ethics of statistics. Consider the following scenario:

 Case-Study: Funding for Social Services

Maria works in social services for a program which advocates for abused, abandoned and neglected children. The program keeps detailed records of the children and their moves and services throughout the dependency care system. Much of the funding for the program is determined by the numbers associated with the record keeping. In the U.S., sources of funding varies from state to state but it is generally a mix of local, state and federal dollars. The allocation of grants and other funding is typically tied to the result of some metric that can be measured over time. Maria is struggling to understand how best to describe her metrics and perhaps more importantly how to ethically balance the need to comply with reporting and the need to justify additional funding. How can Maria work with her data and balancing the competing forces within an ethical decision-making process?

Since you are reading these notes you are probably thinking about statistics. Just like Maria in the example above, we need to think about how we use basic descriptive statistics in our work and daily lives. Descriptive statistics are basic operations performed on data. Descriptive statistics do not convey any significance, prediction, nor certainty, they simply describe the data in front of you. Before Maria can have any conversations with funding agencies or regulatory bodies she must be familiar with her clients, staff, hours of service, and outcomes, which she can learn from descriptive statistics. Maria would not (or should not) attend a meeting without being informed of this information. As statistical concepts become more complex, the importance of understanding the fundamental building blocks of descriptive statistics becomes more apparent, allowing us to correctly select and apply more advanced inferential statistics. These advanced techniques allow us to model the real world, based on our own local or sample data.

The first step in understanding descriptive statistics is to start thinking about some ways in which statistics and numbers are used. Select some media content on a study, poll, or trend, and you will see statistics. Whether political polling, the effectiveness of a product, or an analysis of your favorite sports team, statistics is all around us. Often, we are not even aware of some of the potential misuses of data in our world. For example, how was the sample drawn? What exact question was asked? What data were included and what data was not included? The information in the accompanying materials on ethics (links: ethics in statistics, use and misuse of numbers, and statistics ethics advice) are presented to get you thinking about the issues around ethics.

So, as we begin our journey of learning statistics, let’s start with some of the ethics involved in statistics along with some basic concepts of descriptive statistics.


Upon completion of this lesson, you should be able to:

  • Identify ethical dilemmas
  • Choose among alternative actions using the ASA ethical guidelines as a framework for values
  • Correctly identify measures of central tendency (mean, median, and mode)
  • Match appropriate descriptive statistics with the type of data
  • Match the appropriate graph with type of data