(Offered as PSYC 361 and NEUR 361) Although curiosity about the nature of consciousness has animated the work of philosophers, artists and others, this course will approach the topic from a scientific perspective. How do electrochemical signals in our brain produce our experience of colors, sounds, tastes and our awareness of ourselves? We will read and discuss primary source scientific journal articles drawn from both psychology and neuroscience with a focus on questions including: What kinds of brain activity distinguish conscious from unconscious states?

(Offered as NEUR 317 and PSYC 317) Although the ingestive act per se is clear and simple, understanding the multifarious influences that are distilled into the decision at any given moment to eat, or not to eat, remains a ponderous challenge for scientists. The obesity epidemic of the last several decades continues to spread across the globe, leading to a rise in metabolic diseases and more pressing need than ever to understand the neurobiological controls of eating and body weight.

(Offered as PSYC 211 and NEUR 211) Historically, psychologists and neuroscientists have worked somewhat in parallel to one another. While psychologists have traditionally focused on how humans think, feel, and behave, neuroscientists have primarily focused exclusively on the workings of the brain. Cognitive neuroscience is a relatively new discipline that lies at the intersection of these fields and seeks to understand the neurobiological processes that underlie cognition.

(Offered as STAT 360 and MATH 360) This course explores the nature of probability and its use in modeling real world phenomena. There are two explicit complementary goals: to explore probability theory and its use in applied settings, and to learn parallel analytic and empirical problem-solving skills. The course begins with the development of an intuitive feel for probabilistic thinking, based on the simple yet subtle idea of counting. It then evolves toward the rigorous study of discrete and continuous probability spaces, independence, conditional probability, expectation, and variance.

(Offered as STAT 360 and MATH 360) This course explores the nature of probability and its use in modeling real world phenomena. There are two explicit complementary goals: to explore probability theory and its use in applied settings, and to learn parallel analytic and empirical problem-solving skills. The course begins with the development of an intuitive feel for probabilistic thinking, based on the simple yet subtle idea of counting. It then evolves toward the rigorous study of discrete and continuous probability spaces, independence, conditional probability, expectation, and variance.

(Offered as STAT 135 and MATH 135) This course is an introductory statistics course that uses modeling as a unifying framework. The course provides a basic foundation in statistics with a major emphasis on constructing models from data. Students learn important concepts of statistics by mastering powerful and relatively advanced statistical techniques using computational tools. Topics include descriptive and inferential statistics, visualization, probability, study design, and multiple regression.

(Offered as STAT 135 and MATH 135) This course is an introductory statistics course that uses modeling as a unifying framework. The course provides a basic foundation in statistics with a major emphasis on constructing models from data. Students learn important concepts of statistics by mastering powerful and relatively advanced statistical techniques using computational tools. Topics include descriptive and inferential statistics, visualization, probability, study design, and multiple regression.

(Offered as STAT 135 and MATH 135) This course is an introductory statistics course that uses modeling as a unifying framework. The course provides a basic foundation in statistics with a major emphasis on constructing models from data. Students learn important concepts of statistics by mastering powerful and relatively advanced statistical techniques using computational tools. Topics include descriptive and inferential statistics, visualization, probability, study design, and multiple regression.

(Offered as STAT 135 and MATH 135) This course is an introductory statistics course that uses modeling as a unifying framework. The course provides a basic foundation in statistics with a major emphasis on constructing models from data. Students learn important concepts of statistics by mastering powerful and relatively advanced statistical techniques using computational tools. Topics include descriptive and inferential statistics, visualization, probability, study design, and multiple regression.

(Offered as STAT 135 and MATH 135) This course is an introductory statistics course that uses modeling as a unifying framework. The course provides a basic foundation in statistics with a major emphasis on constructing models from data. Students learn important concepts of statistics by mastering powerful and relatively advanced statistical techniques using computational tools. Topics include descriptive and inferential statistics, visualization, probability, study design, and multiple regression.