For centuries, human beings lived with "uncertainties" every day, unaware of probability theory and how it might be applied to the solution of simple problems of daily living or used to study the laws of nature. It was not until the advent of the scientific method, with its emphasis on observation and experimentation, that people began to think about the role probability might play in areas of life that once seemed ruled by blind chance. Today, of course, probability is the basis of statistics and game theory, and can be immensely useful to anyone engaged in business, social and physical sciences, and many other areas.
This course consists of two parts. The first half will focus on probability theory and its applications (random variables, conditional probability, probability distributions); the second part will discuss some topics from statistics (sampling, estimation, confidence interval, hypothesis testing).
We will develop
the mathematical structure underlying probabilistic reasoning and
apply it to problems across a broad range of fields. The mathematical
background required is an understanding of integration and infinite
series. Applications are taken from many areas, including medical
diagnosis, quality control, gambling, political polls, and
others.
Math 220 fulfills the Quantitative Reasoning overlay course
requirement and counts toward the mathematics major/minor as an
elective.
Prerequisite: 116 or the equivalent. Open to
first-year students by permission of the instructor.
Distribution: Mathematical Modeling. Fulfills the Quantitative
Reasoning overlay requirement.
