Statistics is… Mathematics: The tools used to analyze data and quantify uncertainty are mathematical in nature (e.g., probability, counting methods). English: It is not enough to analyze data. The numbers have to be explained or interpreted in the context of the original problem in order to be useful for making decisions. History: Problems generally don’t arise from a vacuum. What came before will influence the current analysis (e.g., previous experiments).

Statistics is… Philosophy: Statistics isn’t just a tool we use. It is a way of thinking about and approaching problems; a logical structure used to analyze data and make decisions; a field of study that continues to evolve as new problems arise. Other Arts and Sciences: Again, the context in which a problem occurs is vitally important. The early development of statistical methods were driven by the need to answer questions in biology, psychology, sociology, agriculture.

How does it all work? First we start with a question… Take a Survey, Follow a Process, Conduct an Experiment, Observe a System or Situation Raw Data (needs work) Perform a Statistical Analysis and Make Some Interpretations Information

Things to keep in mind… VARIABILITY affects everything we do. There is inherent variability between individuals in a population as well as variability that results from sampling. If planned correctly, we can explain both kinds of variability with statistics. RANDOMNESS doesn’t mean that something is either haphazard or unpredictable. Random sampling is fundamental to statistics. ERROR doesn’t mean mistake. Random error is a natural part of statistics. BIAS is trouble.

More things to keep in mind… Everything is relative. The context of the data matters. What looks like a “large” difference in one situation may not be so big in another. It’s not the size of the population that matters, it’s the size of the sample. In random samples sample size and variability determine overall level of uncertainty (more variability  bigger sample needed). Statistics gives us evidence, not proof. There is almost always room for alternate interpretation.

Acknowledgements Thanks to Dr. Jill Thomley for these slides.