Peter L Nye
Presentation of key concepts for understanding and judging reports of statistical analyses and for performing and reporting valid statistical analyses using a limited set of measures and tests.
This course introduces descriptive statistics, probability concepts and statistical inference. We will emphasizes those statistical applications most useful in everyday decision making. Topics include exploratory data analysis, measures of association, cross-tabulation, sampling theory, estimation, hypothesis testing and simple regression analysis. Concepts are illustrated through case problems in consumer economics, social policy, psychology and business.
Student learning goals
Understand the basic concepts of both descriptive and inferential statistics.
Demonstrate the ability to creatively analyze data using statistical methods.
Be skilled at organizing and presenting statistical information in a format that will facilitate informed judgments.
Understand some common biases in interpreting statistical results: why they occur, and how they can be prevented.
General method of instruction
Participatory lectures, case analysis and problem-solving workshops.
Working knowledge of basic algebra.
Class assignments and grading
Course grades will be based on two challenging midterm exams and a comprehensive final exam.