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Term
Time & Day Offered
Level
Credits
Course Duration

Stars and Galaxies — PHY2106.01

Instructor: Hugh Crowl
Days & Time: MO,TH 10:00am-11:50am
Credits: 4

All but a handful of the objects you see in the night sky are stars in our Galaxy, the Milky Way. Although we know about these stars only from studying their light, we know today that they are not just points of light, but large, gravitationally‐bound balls of plasma governed by the laws of physics. Stars, together with dust, gas, and dark matter,

Stars, Planets, Life — PHY2107.01

Instructor: Hugh Crowl
Credits: 4
In the last twenty-five years, the study of life beyond our own planet has gone from science fiction to legitimate science. The course will initially focus on how stars form and evolve, starting from the formation of the universe, and continuing to a discussion of stars as both the synthesizers of heavy elements and the central energy source for solar systems. From there, we

Stars, Planets, Life — PHY2107.01

Instructor: Hugh Crowl
Credits: 4
In the last thirty years, the study of life beyond our own planet has gone from science fiction to legitimate science. The course will initially focus on how stars form and evolve, starting from the formation of the universe, and continuing to a discussion of stars as both the synthesizers of heavy elements and the central energy source for stellar systems. From there, we will

Stars, Planets, Life — PHY2107.01

Instructor: Hugh Crowl
Credits: 4
In the last thirty years, the study of life beyond our own planet has gone from science fiction to legitimate science. The course will initially focus on how stars form and evolve, starting from the formation of the universe, and continuing to a discussion of stars as both the synthesizers of heavy elements and the central energy source for stellar systems. From there, we will

Statistical Methods for Data Analysis — MAT2104.01

Instructor: Katie Montovan
Credits: 4
In this course, we will focus on developing the statistical skills needed to answer questions by collecting data, designing experimental studies, and analyzing large publicly available datasets. The skills learned will also help students to be critical consumers of statistical results. We will use a variety of datasets to develop skills in data management, analysis, and

Statistical Methods for Data Analysis — MAT2104.01

Instructor: Katie Montovan
Credits: 4
In this course, we will focus on developing the statistical skills needed to answer questions by collecting data, designing experimental studies, and analyzing large publicly available datasets. The skills learned will also help students to be critical consumers of statistical results. We will use a variety of datasets to develop skills in data management, analysis, and

Statistical Methods for Data Analysis — MAT2104.01

Instructor: Katie Montovan
Days & Time: TU,FR 8:30am-10:20am
Credits: 4

In this course, we will focus on developing the statistical skills needed to answer questions by collecting data, designing experimental studies, and analyzing large publicly available datasets. The skills learned will also help students to be critical consumers of statistical results. We will use a variety of datasets to develop skills in data management, analysis, and

Statistical Methods for Data Analysis — MAT2104.01

Instructor: Katie Montovan
Credits: 4
In this course, we will focus on developing the statistical skills needed to answer questions by collecting data, designing experimental studies, and analyzing large publicly available datasets. The skills learned will also help students to be critical consumers of statistical results. We will use a variety of datasets to develop skills in data management, analysis, and

Statistical Methods for Data Analysis — MAT2104.01

Instructor: Katie Montovan
Credits: 4
This course focuses on developing the statistical skills needed to design studies, to analyze large datasets and to be a critical consumer of statistical results. We will design studies, collect and analyze data, and create effective presentations of results. We will also analyze large observational datasets. Emphasis will be placed on gaining a solid conceptual understanding

Statistical Methods for Data Analysis — MAT2104.01

Instructor: Andrew McIntyre
Credits: 4
In this course, we will focus on developing the statistical skills needed to answer questions by collecting data, designing experimental studies, and analyzing large publicly available datasets. The skills learned will also help students to be critical consumers of statistical results. We will use a variety of datasets to develop skills in data management, analysis, and

Statistical Methods for Data Analysis — MAT2104.01

Instructor: Katie Montovan
Credits: 4
This course focuses on developing the statistical skills needed to design studies, analyze large datasets and to be a critical consumer of statistical results. We will design studies, collect and analyze data, and create effective presentations of results. We will also analyze large observational datasets. Emphasis will be placed on gaining a solid conceptual understanding of

Statistics and Their Presentation — MAT2236.01

Instructor: Kathryn Montovan
Credits: 4
Statistics is the art of finding meaning in spite of unavoidable uncertainties. Statistics is an important part of modern society -- with politicians, businessmen, economists, and all kinds of scientists depending on statistics and statistical models to estimate and confirm patterns within their data. In this course, we will focus on using basic statistical methods to

Statistics and Their Presentation — MAT2114.01

Instructor: Kathryn Montovan
Credits: 4
Statistics is the art of finding meaning in mathematical abstracts. It is looking at patterns and trying to reason what those patterns mean for the future. Statistics have pervaded modern society--politics, business, economics, and all walks of science depend on statistics and the models contained within to estimate and confirm patterns within their data. This course will focus

Statistics for Data Analysis — MAT4216.01

Instructor: Josef Mundt
Credits: 4
In this course, we will focus on developing the statistical skills needed to answer questions by collecting data, designing experimental studies, and analyzing large publicly available datasets. The skills learned will also help students to be critical consumers of statistical results. We will use a variety of datasets to develop skills in data management, analysis and

Statistics for Social Science — SOC4103.01

Instructor: Emily Waterman
Days & Time: MO,TH 1:40pm-3:30pm
Credits: 4

In this course students will learn to use social science statistics to test their own research questions, while becoming more educated consumers of statistical analyses presented in research and news sources. Students will employ various inferential statistics techniques commonly used in social science, such as confidence intervals, t-tests, chi

Statistics for Social Science — SOC4103.01

Instructor: Emily Waterman
Credits: 4
In this course students will learn to use social science statistics to test their own research questions, while becoming more educated consumers of statistical analyses presented in research and news sources. Students will employ various inferential statistics techniques commonly used in social science, such as confidence intervals, t-tests, chi-square testing, correlation,

Statistics for Social Science — SOC4103.01

Instructor: Emily Waterman
Credits: 4
In this course students will learn to use social science statistics to test their own research questions, while becoming more educated consumers of statistical analyses presented in research and news sources. Students will employ various inferential statistics techniques commonly used in social science, such as confidence intervals, t-tests, chi-square testing, correlation,

Statistics for Social Science — SOC4103.01

Instructor: Emily Waterman
Credits: 4
In this course students will learn to use social science statistics to test their own research questions, while becoming more educated consumers of statistical analyses presented in research and news sources. Students will employ various inferential statistics techniques commonly used in social science, such as confidence intervals, t-tests, chi-square testing, correlation,

Statistics for the Social Sciences — SOC4103.01) (cancelled

Instructor: Debbie Warnock
Credits: 4
In this course students will learn to harness social statistics as a powerful tool for answering social science research questions, while becoming more educated consumers of statistical analyses presented in research and news sources. Using nationally representative data sets we will employ various inferential statistics techniques, such as confidence intervals, t-tests, chi

Statistics for the Social Sciences — SOC4103.01

Instructor: Debbie Warnock
Credits: 4
In this course students will learn to harness social statistics as a powerful tool for answering social science research questions, while becoming more educated consumers of statistical analyses presented in research and news sources. Using nationally representative data sets we will employ various inferential statistics techniques, such as confidence intervals, t-tests, chi

Statistics for the Social Sciences — SCT4105.01

Instructor: Debbie Warnock
Credits: 4
In this course students will learn to harness social statistics as a powerful tool for answering social science research questions, while becoming more educated consumers of statistical analyses presented in research and news sources. Using nationally representative data sets we will employ various inferential statistics techniques, such as confidence intervals, t-tests, chi

Steal This Book: Literature of the 60s and 70s — LIT2248.01

Instructor: Benjamin Anastas
Days & Time: TBA
Credits: 4
The 1960s and 70s have been so thoroughly trivialized by the culture wars that Timothy Leary’s mantra ‘Turn on, tune in and drop out’ has become the era’s defining slogan. But the counter-culture helped produce some of the most genre-breaking literature we have, and this course will dive into the alternative canon for a long, strange trip among the famous, the forgotten, and

Still + Moving Image — PHO2156.01

Instructor: Jonathan Kline
Credits: 4
In this remote course we will explore the rich terrain between photography and film from the early 20th century to the present moment. Through weekly screenings, pdfs of published texts, and synchronous small discussion groups, we will study the still/moving image work of Moholy-Nagy, Helen Levitt, Gordon Parks, Mary Ellen Mark, RaMell Ross, and others. Written responses will

Stimulus, Sensation, and the Brain: Psychophysical Investigations of Perception — BIO4126.01

Instructor: David Edelman
Credits: 4
How do animals extract information that is critical for survival from an often complex and ambiguous world? When an octopus sees a crab, what features and behaviors of that crab are capturing the octopus attention? How can we investigate sensory percepts in animals that cant report those percepts to us via natural language? What are the neural correlates of perception? In this