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.

An introduction to discrete (finite) mathematics with emphasis on the study of algorithms and on applications to mathematical modeling and computer science. Topics include sets, logic, graph theory, induction, recursion, counting, and combinatorics.

Differential equations, difference equations, dynamical systems: numerical methods and qualitative analysis. Power series, sequences, and convergence. Situations in science and social science in which calculus naturally arises are emphasized. Intended for students who have had a year of calculus elsewhere. Students may not receive credit for both 114 and 112.

Applications of the integral, dynamical systems, infinite series, and approximation of functions. Situations in science and social sciences in which calculus naturally arises are emphasized. Students may not receive credit for both 114 and 112 Prerequisite: MTH 111 or the equivalent.

Applications of the integral, dynamical systems, infinite series, and approximation of functions. Situations in science and social sciences in which calculus naturally arises are emphasized. Students may not receive credit for both 114 and 112 Prerequisite: MTH 111 or the equivalent.

Applications of the integral, dynamical systems, infinite series, and approximation of functions. Situations in science and social sciences in which calculus naturally arises are emphasized. Students may not receive credit for both 114 and 112 Prerequisite: MTH 111 or the equivalent.

Rates of change, differential equations and their numerical solutions, integration, differentiation, and the fundamental theorem of the calculus. Situations in science and social science in which calculus naturally arises are emphasized.