The emphasis of this class is to understand the logical basis, set of assumptions, and underlying mechanics of statistical hypothesis testing, with the aim that by the end of the course people will be able to manipulate simple data sets, accurately describe statistical relationships, and understand the results of published research. We will focus on both parametric and non-parametric univariate statistics, but will touch on multivariate techniques (time allowing), which are essential to manipulating more complex data sets. The class assumes no previous background in either mathematics, computing, or statistics beyond the level of basic arithmetic. In class, we will learn to carry out basic statistical tests by focusing on the more theoretical aspects of statistics using simple equations (plug and chug) to highlight the procedures, and in the labs we will focus on using MINITAB and EXCEL to manage data sets and perform the same and more complex tests. Please read the assigned chapters before class so that you have a background to what is being discussed, and can come armed with questions. Grading is based on statistical concepts and the ability to follow statistical procedures on paper and on the computer, not on the rote memorization of equations. Students are encouraged to attend office hours and work together on the problem sets, but all assignments must be handed in as individual pieces of work. However, the final take-home exam is to be completed individually, with no collaboration.