Math 360:
Probability & Statistics I

Topics include probability definitions and theorems; discrete and continuous random variables including the binomial, hypergeometric, Poisson and normal random variables; and the applications of probability to such statistical topics as sampling distributions, point estimation, confidence intervals, and/or tests of hypothesis. Both the theory and applications of probability and statistics will be included. Prerequisites: MATH 223 or permission of the instructor.

Math 262:
R/Applied Statistics

An introduction to statistics with emphasis on applications. Topics include the description of data with numerical summaries and graphs, the production of data through sampling and experimental design, techniques of making inferences from data such as confidence intervals and hypothesis tests for both categorical and quantitative data. The course includes an introduction to computer analysis of data with a statistical computing package. (Those who have completed MATH 350 may not enroll in this course for credit, and no student may reveive credit for more than one 200-level statisticcs course, including credit for more than one of the following courses: BIOL 250, ECON 202, MATH 242, MATH 262, PLSC 251, PSYC 250, and SOCL 211.) Offered every semester

Math 222:
Calculus II

Derivatives and antiderivatives of the transcendental functions, methods of integration, applications of definite integrals, sequences, improper integrals, and series. Prerequisites: MATH 221. Offered every semester