MATH 1710

Statistical Theory and Application in the Real World

Course Description

Course information provided by the Courses of Study 2019-2020.

Introductory statistics course discussing techniques for analyzing data occurring in the real world and the mathematical and philosophical justification for these techniques. Topics include population and sample distributions, central limit theorem, statistical theories of point estimation, confidence intervals, testing hypotheses, the linear model, and the least squares estimator. The course concludes with a discussion of tests and estimates for regression and analysis of variance (if time permits). The computer is used to demonstrate some aspects of the theory, such as sampling distributions and the Central Limit Theorem. In the lab portion of the course, students learn and use computer-based methods for implementing the statistical methodology presented in the lectures.

When Offered Fall, Spring.

Prerequisites/Corequisites Prerequisite: high school mathematics. No previous familiarity with computers presumed.
Forbidden Overlaps Forbidden Overlap: due to an overlap in content, students will receive credit for only one course in the following group: AEM 2100, BTRY 3010, BTRY 6010, ENGRD 2700, HADM 2010, ILRST 2100, ILRST 6100, MATH 1710, PAM 2100, PAM 2101, PSYCH 2500, SOC 3010, STSCI 2100, STSCI 2150, STSCI 2200.  In addition, no credit for MATH 1710 if taken after ECON 3130, ECON 3140, MATH 4720, or any other upper-level course focusing on the statistical sciences (e.g., those counting toward the statistics concentration for the math major).

Distribution Category (MQR-AS)

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