Math 217 Probability and Statistics
[this course page is under construction]
- General description.
An introduction to probability theory and mathematical statistics that emphasizes the
probabilistic foundations required to understand probability models and statistical
methods. Topics covered will include the probability axioms, basic combinatorics,
discrete and continuous random variables, probability distributions, mathematical expectation,
common families of probability distributions, and the central limit theorem.
This course is cross-listed as Econ 260 and as Econ 360.
Clark's Academic Catalog
One year of college calculus (Math 121 or 125).
- Course goals.
- To provide students with a good understanding of the theory of probability, both
discrete and continuous, including some combinatorics, a variety of useful
distributions, expectation and variance, analysis of sample statistics, and
central limit theorems, as described in the syllabus.
- To help students develop the ability to solve problems using probability.
- To introduce students to some of the basic methods of statistics and prepare them
for further study in statistics.
- To develop abstract and critical reasoning by studying logical proofs and the
axiomatic method as applied to basic probability.
- To make connections between probability and other branches of mathematics, and
to see some of the history of probability.
- Syllabus [to be determined]
- Textbook. [to be determined]
- Course Hours. [to be determined]
- Assignments & tests.
There will be numerous short homework assignments, mostly
from the text, occasional quizzes, two tests during the semester, and a two-hour
final exam during finals week.
- Course grade. [tentative]
The course grade will be determined as follows:
2/9 assignments and quizzes,
2/9 each of the two midterms, and
1/3 for the final exam.
Class notes, quizzes, tests, homework assignments
[to be filled in as the course progresses]
This page is located on the web at
David E. Joyce