Buried inside each of us is an innate statistician. We receive data everyday, assess its quality, compare it to other data we have received, and analyze it to make decisions about our lives. Do we trust our friend to show up on time? If you go to bed earlier, do your grades improve? How long do you let the cake bake in the oven? Do you give your boyfriend another chance (or, does he give you another chance)? These are all questions that require us to perform complex calculations in our head.

course description

Everyday, epidemiologists make decisions like those above everyday to keep us healthy. They just evaluate different kinds of data and apply statistical methods to the problems that they try to solve. For epidemiologists, statistics is a language that creates formal ways of expressing information and confidence about decisions that we make based on patterns they see in the data.

This course will help you hone your inner epidemiologist to think about how statistics can help us make decisions in our lives. It will expose you to the basic concepts and principles of statistical analysis by showing how we already use those principles in our daily dealings. It will then show you how epidemiologists use the same concepts to make recommendations for the public health of communities, states, nations, and the world.

This course will introduce you to the mathematics behind statistical analyses, but mathematics will not be the focus of the course. Too often people are intimidated by numbers and Greek letters to uncover the intuition behind statistical analyses and reports. As a result, we end up not evaluating numerical analyses that come our way all of the time; some we trust too much, others we trust too little. This class will help you be a knowledgeable consumer of numerical data in our increasingly data-driven world.

course objectives

• describe statistical principles of measurement, central tendency, and dispersion in simple, everyday terms;
• develop an intuition for probabilistic reasoning and its use in decision making; and
• apply statistical principles to problems in students’ own everyday experiences;