The topological structure of the real line, compactness, connectedness, functions, continuity, uniform continuity, sequences and series of functions, uniform convergence, introduction to Lebesgue measure and integration. Prerequisites: MTH 211 and MTH 212, or permission of the instructor.

The topological structure of the real line, compactness, connectedness, functions, continuity, uniform continuity, sequences and series of functions, uniform convergence, introduction to Lebesgue measure and integration. Prerequisites: MTH 211 and MTH 212, or permission of the instructor.

Topics to be covered include properties of the integers, prime numbers, congruences, various Diophantine problems, arithmetical functions and cryptography. Prerequisite: MTH 153, MTH 211, or permission of the instructor.

Theory and applications of limits, derivatives, and integrals of functions of one, two and three variables. Curves in two and three dimensional space, vector functions, double and triple integrals, polar, cylindrical, spherical coordinates. Path integration and Green's Theorem. Prerequisites: MTH 112 or MTH 114. It is suggested that MTH 211 be taken before or concurrently with MTH 212.

Vector spaces, matrices, linear transformations, systems of linear equations. Applications to be selected from differential equations, foundations of physics, geometry, and other topics. Students may not receive credit for both MTH 211 and MTH 221. Prerequisite: MTH 112 or the equivalent, or MTH 111 and MTH 153; MTH 153 is suggested.

Vector spaces, matrices, linear transformations, systems of linear equations. Applications to be selected from differential equations, foundations of physics, geometry, and other topics. Students may not receive credit for both MTH 211 and MTH 221. Prerequisite: MTH 112 or the equivalent, or MTH 111 and MTH 153; MTH 153 is suggested.

Same as PSY 190. An overview of the statistical methods needed for undergraduate research emphasizing methods for data collection, data description, and statistical inference including an introduction to study design, confidence intervals, testing hypotheses, analysis of variance and regression analysis. Techniques for analyzing both quantitative and categorical data will be discussed. Applications are emphasized, and students use SPSS and other statistical software for data analysis. Classes meet for lecture/discussion and a required laboratory that emphasizes the analysis of real data.

Same as PSY 190. An overview of the statistical methods needed for undergraduate research emphasizing methods for data collection, data description, and statistical inference including an introduction to study design, confidence intervals, testing hypotheses, analysis of variance and regression analysis. Techniques for analyzing both quantitative and categorical data will be discussed. Applications are emphasized, and students use SPSS and other statistical software for data analysis. Classes meet for lecture/discussion and a required laboratory that emphasizes the analysis of real data.

Same as PSY 190. An overview of the statistical methods needed for undergraduate research emphasizing methods for data collection, data description, and statistical inference including an introduction to study design, confidence intervals, testing hypotheses, analysis of variance and regression analysis. Techniques for analyzing both quantitative and categorical data will be discussed. Applications are emphasized, and students use SPSS and other statistical software for data analysis. Classes meet for lecture/discussion and a required laboratory that emphasizes the analysis of real data.

Same as PSY 190. An overview of the statistical methods needed for undergraduate research emphasizing methods for data collection, data description, and statistical inference including an introduction to study design, confidence intervals, testing hypotheses, analysis of variance and regression analysis. Techniques for analyzing both quantitative and categorical data will be discussed. Applications are emphasized, and students use SPSS and other statistical software for data analysis. Classes meet for lecture/discussion and a required laboratory that emphasizes the analysis of real data.