1. Winter Institute on Statistical Literacy for Librarians, February 17-19, 2010 Review of the Pre- workshop Readings Chuck Humphrey

2. “The Numbers Game” 1. Understanding how to read statistics makes people better citizens. 2. Don’t ascribe greater precision to statistics than what the methodology and data allow or warrant. “[P]recision comes at a price: before you can count something, you have to define what it is you’re counting, and often that’s not as simple as it sounds.” 3. If you don’t have a population, you need a sample, which involves error (or a measurement of uncertainty.) 4. Patterns occur randomly and may not involve causality.

3. “The Numbers Game” 5. Reading and interpreting statistics requires a critical attitude. You need to reach “a proper balance between credulousness and disdain” for statistics. “Assuming, that is, that we can trust the numbers.”

4. Points from Stats in the News 1. Statistics are often used to describe relationships, e.g., economic strength is correlated with employment and job creation. 2. Be a critical reader of statistics. Challenge the face validity of reported statistics. The statistic may be right but the interpretation may be wrong. 3. Statistics must have a data source. 4. Data sources will have an observational unit that is the source for the information. 5. Data are collected using a variety of methodologies, which must be understood when interpreting statistics.

5. Points from Stats in the News 6. Statistics from observational data take place in the context of time, place and content. Time is often a necessary factor in interpreting statistics, especially when comparisons are being made. Trends provide a comparative measure for interpretation. 7. Statistics are summaries from the data. Knowing the unit of observation is important to know what is being described by these summaries. 8. Statistics are based on definitions and classifications. Knowing what is included and excluded in a statistic is essential for interpretation.

6. Points from Stats in the News 9. When comparing statistics, take into account how the methodologies may contribute to differences. 10. Don’t attribute greater precision to statistics than the methodology permits. 11. Rely on other knowledge to help interpret statistics.