A laboratory course exploring anatomical research methods, neurochemical techniques, behavioral testing, design of experiments and data analysis. Prerequisites: CHM 111 or 118, and PSY 130 or NSC 125or NSC 210 (can be taken concurrently) or permission of the instructor. Not open to seniors. Enrollment limited to 16.

The course will provide an introduction to the organization and function of the mammalian nervous system along with an exploration of the brain using multiple levels of analysis ranging from molecular to cognitive and behavioral approaches. The course will develop an appreciation of how brain cells interact to orchestrate responses and experiences. Emphasis will be placed on the cellular and molecular physiology of the nervous system with a focus on retinal phototransduction and mechanisms governing motor control. The material will be presented at a level accessible for life science majors.

Same as SDS 220. An application-oriented introduction to modern statistical inference: study design, descriptive statistics; random variables; probability and sampling distributions; point and interval estimates; hypothesis tests, resampling procedures and multiple regression. A wide variety of applications from the natural and social sciences are used. Classes meet for lecture/discussion and for a required laboratory that emphasizes analysis of real data. MTH 220 satisfies the basis requirement for biological science, engineering, environmental science, neuroscience and psychology.

Same as SDS 220. An application-oriented introduction to modern statistical inference: study design, descriptive statistics; random variables; probability and sampling distributions; point and interval estimates; hypothesis tests, resampling procedures and multiple regression. A wide variety of applications from the natural and social sciences are used. Classes meet for lecture/discussion and for a required laboratory that emphasizes analysis of real data. MTH 220 satisfies the basis requirement for biological science, engineering, environmental science, neuroscience and psychology.

Same as SDS 220. An application-oriented introduction to modern statistical inference: study design, descriptive statistics; random variables; probability and sampling distributions; point and interval estimates; hypothesis tests, resampling procedures and multiple regression. A wide variety of applications from the natural and social sciences are used. Classes meet for lecture/discussion and for a required laboratory that emphasizes analysis of real data. MTH 220 satisfies the basis requirement for biological science, engineering, environmental science, neuroscience and psychology.

Same as SDS 320. An introduction to the mathematical theory of statistics and to the application of that theory to the real world. Topics include functions of random variables, estimation, likelihood and Bayesian methods, hypothesis testing and linear models. Prerequisites: a course in introductory statistics, MTH 212 and MTH 246, or permission of the instructor.

Same as SDS 291. Theory and applications of regression techniques; linear and nonlinear multiple regression models, residual and influence analysis, correlation, covariance analysis, indicator variables and time series analysis. This course includes methods for choosing, fitting, evaluating and comparing statistical models and analyzes data sets taken from the natural, physical and social sciences. Prerequisite: one of the following: PSY 201, GOV 190, MTH 220, ECO 220, or the equivalent or a score of 4 or 5 on the AP Statistics examination. Enrollment limited to 25.

Same as SDS 291. Theory and applications of regression techniques; linear and nonlinear multiple regression models, residual and influence analysis, correlation, covariance analysis, indicator variables and time series analysis. This course includes methods for choosing, fitting, evaluating and comparing statistical models and analyzes data sets taken from the natural, physical and social sciences. Prerequisite: one of the following: PSY 201, GOV 190, MTH 220, ECO 220, or the equivalent or a score of 4 or 5 on the AP Statistics examination. Enrollment limited to 25.

Same as SDS 290. A survey of statistical methods needed for scientific research, including planning data collection and data analyses that provide evidence about a research hypothesis. The course can include coverage of analyses of variance, interactions, contrasts, multiple comparisons, multiple regression, factor analysis, causal inference for observational and randomized studies and graphical methods for displaying data. Special attention is given to analysis of data from student projects such as theses and special studies. Statistical software is used for data analysis.

Same as SDS 220. An application-oriented introduction to modern statistical inference: study design, descriptive statistics; random variables; probability and sampling distributions; point and interval estimates; hypothesis tests, resampling procedures and multiple regression. A wide variety of applications from the natural and social sciences are used. Classes meet for lecture/discussion and for a required laboratory that emphasizes analysis of real data. MTH 220 satisfies the basis requirement for biological science, engineering, environmental science, neuroscience and psychology.