In Chapter 1, you learned that data are observations that you or someone else (or something else) records.You also learned that data are more than just numbers or lists of characteristics. David Moore, a well-known statistician, defined data as “numbers in context.” By this he meant that data consist not only of numbers we record, but also of the story behnid the numbers. For example, 70. 75, 70, 70, 65 are just numbers. But in fact these numbers represent the maximum allowable speed limit for cars on a rural interstate in mph. Now these numbers have a context and have been elevated to data. So data has context and can be much more interesting than numbers right?

Data plays a pivotal role in or economy, culture, and everyday lives. A lot of the data in this textook is concerned with data collected for what we might call “professional” purposes such as answering scientific questions or making business decisions. But in fact, data is everywhere. Google, for example, saves every search you make and combines this with data on which links you click in order to improve the way it presents information (and, of course, to determine which advertisements will appear on your search results).

Data tells a story. Understanding the context of the data helps to determine the story that the data is trying to tell. In Chapter 2, you learned how to graphically display qualitative and quantitative data. Recall the statistical process revolves around a research topic. This topic will usually include a narrative to get the context of the data you will need to collect.

Discussion Board Resource: How to Tell a Story With Data

Initial Post – Read the article How to Tell a Story With Data to help you to write a narrative that could possible describe the data collected and used to construct the time-series graph shown in the time-series plot below. Your narrative should include at least 5 sentences.

You might also consider the following questions to help you to get a better idea of the context of the data and write your narrative.

• What are the objects of interest?
• What variables were measured?
• How were they measured?
• What are the units of measurement?
• Who collected the data?
• How did they collect the data?
• Where were the data collected?
• Why were the data collected?