Fall Numbers Sections

Fall 2023 Numbers Descriptions are below, listed in order of class time and then by professor last name. Additional section descriptions will be added soon.

The date/time you submit your preferences has no bearing on your placement. The preferences you submit closest to the deadline (on June 27th) will be used.

Please email GenEd@lclark.edu if you have any questions.

MWF 11:30am - 12:30pm

Over the Rainbow: Facets of Color

Anne Bentley, Assoc Prof of Chemistry

  • Core 121-01 – MWF 11:30am-12:30pm

Procedural Ethics and Moral Machines - {added 6/15}

Devin Fitzpatrick, Visiting Asst Prof of Philosophy

  • Core 121-02 - MWF 11:30am-12:30pm

These courses are also taught MWF 1:50-2:50pm. Please see the descriptions there (below).

Dealing with Data in the Wild

Greta Binford, Prof of Biology

  • Core 121-05 – MWF 11:30am-12:30pm {this is a time change}

Do you want to live permanently in Antarctica? Now is your chance, apply for Mission Antarctica! The ice is melting, the penguins are marching; it seems like a perfect time to settle, but many challenges await. Data can help you live and thrive in this changing environment and not be eaten by a leopard seal. However, most of us do not know how to organize, analyze, and translate real-life data into decisions. In this class, we undergo a series of scenarios to teach you how to use data to design and evaluate if we are making a difference in our new society. These scenarios include case studies related to disease, food security, conservation, sustainability, and nutrition. Through a combination of lectures, hands-on problem solving, and collaboration, this course teaches introductory data literacy skills such as data management, basic coding using R, analytics, and visualization useful for decision making and your careers. Most importantly, no penguins will be harmed in this adventure, we promise.

MWF 1:50 - 2:50pm

Over the Rainbow: Facets of Color

Anne Bentley, Assoc Prof of Chemistry

  • Core 121-01 – MWF 11:30am-12:30pm
  • Core 121-05 – MWF 1:50-2:50pm

What’s so amazing that keeps us stargazing? This course will introduce the physical, chemical, and biological origins of color while also addressing a number of fascinating questions. What is color? How is color measured? How can a blue and black dress appear gold and white? How can color be used in scientific research? Where is color found in our cultures, politics, and advertising? From indigo derived from plants to mauve first made in a lab, we will examine the origins and history of color in nature, paints, and dyes. Classwork will include reading, class discussions, lecture, in-class hands-on and problem-solving activities, and the preparation and analysis of data.

American Inequality

Maryann Bylander, Assoc Prof of Sociology

  • Core 121-10 – MWF 1:50-2:50pm

This course engages with social statistics to describe, analyze and understand key forms of inequality with the United States. While the ultimate goal of the course is for students to become better consumers of social statistics, we engage primarily with data related to race, class, and gender-based inequalities in order to do so. Together, we will draw on social statistics to explore questions of local relevance, including: Is homelessness increasing in Portland? What is the best way to measure poverty in our community? How can we determine if there is discrimination in rental markets in Portland? Substantively, students will learn to 1) describe, interpret, and visually represent social statistics 2) assess the validity of statistics and causal claims and 3) critically evaluate social statistics reported in the media. We will also explore examples of “data activism” which seek to draw attention to issues of power, representation, and oppression inherent in the creation of social statistics and their use. Throughout the course we will be mindful of the fact that numbers are not objective “facts” but rather imperfect, produced representations of the world actively constructed by people. At the same time, we will also work to understand how statistics can provide useful and unique perspectives on the social world, complementing and supporting other ways of knowing.

Order, Chaos & Randomness

Yung-Pin Chen, Prof of Statistics

  • Core 121-09 – MWF 1:50-2:50pm

Chances are all around us every day of our lives. Chaotic and unpredictable phenomena appear in nature. Despite the disorderly occurrences, we can find observable patterns or visible regularities of form in very diverse contexts in the natural world. In this course we will explore both chaotic and random phenomena in nature and in our daily lives. The course is centered around a collection of class discussions and activities that develop effective thinking and build analytic reasoning skills as habits of mind. The exploring topics include: numbers as a language, number system (including complex numbers), numerical patterns in nature, infinity, fractals, randomness, random walks, sampling, data, and distribution models.

Fire, Energy, and Civilization - {added 8/1}

Ethan Davis, Digital and Data Science Specialist at Watzek Library

  • Core 121-13 – MWF 1:50-2:50pm

We’ve all seen a lone ant wandering aimlessly across our kitchen counter, with no apparent plan or thought, thwarted in its mission by something as simple as an orange peel. How then, does a colony composed of nearly identical ants collectively solve complex problems, adapt to changing environments, and process information to make seemingly intelligent decisions? The study of complex systems focuses on cases like ant colonies, where many individuals following simple rules can exhibit collective behavior that is markedly different from what happens on the individual level.

This course will follow the history and practice of complex systems science, and use it to connect disparate areas of study, from Protozoa, to ants, algorithms, and society. Students will learn the basic programming skills needed to build computational models of systems, and how to use those models to understand real-world behavior.

Fire, Energy, and Civilization - {added 6/2}

Julio de Paula, Prof of Chemistry

  • Core 121-06 – MWF 1:50-2:50pm

The ancient Greeks described the composition of all matter and nature in terms of the “elements” earth, air, fire, and water. This course dives deep into “Fire,” more commonly referred to today as “Energy.” Early energy sources such as the burning of wood, followed by coal, and then oil, have led to the accumulation of carbon dioxide in the atmosphere. The prospect of climate change has motivated the development of a dizzying array of alternative energy technologies that use sources as diverse as tides, kelp, and the deep earth. This course will discuss fundamental concepts such as heat, work, the laws of thermodynamics, and the generation of electricity. Then we will center our inquiry on this guiding question: “What must be done to reach the goal of net-zero global carbon emissions?”

To address this question, we will investigate energy usage in agriculture, manufacturing, buildings, and transportation. We will explore the influence of energy on community health, poverty, and security. Our inquiry will be rooted in mining publicly available datasets that we will analyze with online tools and spreadsheets. We will interpret and construct graphical representations of data and work in teams to tackle the pressing challenge of an equitable transition to global net-zero carbon emissions.

This section is intended for students with no previous experience with statistics.

Procedural Ethics and Moral Machines

Devin Fitzpatrick, Visiting Asst Prof of Philosophy

  • Core 121-02 - MWF 11:30am-12:30pm - {added 6/15}
  • Core 121-12 – MWF 1:50-2:50pm

The recent advent of sophisticated AI (artificial intelligence) chatbots raises urgent questions about the ethics of their use and development. These concerns are as varied as the chatbots’ utility, ranging from the replacement of creative labor like writers and artists by AI, the risk of chatbots harassing users or AI expressing bias, and the emotional dependency of users forming relationships with chatbot partners. There arise two broad questions: first, what moral restrictions should (or can) be on AI chatbots themselves, and second, how human developers should behave ethically in creating AI. But there is a third question that is less discussed: how the moral systems we humans impose on ourselves might differ from the moral codes that AI should obey. In this course, we will learn about this history of human morality and the differences between “procedural ethics” like utilitarianism and non-procedural approaches like virtue and care ethics, as we also learn how to create chatbots ourselves.

Probability, Quantification, and Ideology: Numbers in Their Human Context(s)

Colin Patrick, Visiting Assist Prof of Philosophy

  • Core 121-04 – MWF 1:50-2:50pm

In this course we’ll examine some of the benefits and pitfalls of quantificational and “data-driven” reasoning, some philosophical questions arising from efforts to assign numerical values to probability, to human characteristics, behavior, and responsibility, and the increasing trend of outsourcing impactful decisions to computer algorithms and AI operating – supposedly “objectively” – on the basis of quantified data. We’ll learn some of the basics of inductive logic, scientific method, and probability theory, with an emphasis on thinking carefully and critically about the mathematical formulae they use, and what the numerical values they operate with really mean in context. We will explore North American Indigenous epistemology – its similarities to, and differences from, Eurogenic science and inductive reasoning, and its uniquely valuable perspective on the course themes. Lastly, we will think critically about the ideological purposes often lurking behind efforts to assign numbers to individual human beings – from their intelligence to their responsibility for carbon emissions – and assess the scientific and logical merit (or otherwise) of studies seeking to reveal the foundations of gender-based social disparities in neurological and other biometric data.

Politicians Lie, Numbers Can Mislead: The Politics of Numbers

Matt Scroggs, Visiting Asst Prof of International Affairs

  • Core 121-11 – MWF 1:50-2:50pm

People have complex, nuanced political beliefs, so how can we figure them out? People aren’t always truthful about what they believe in or why they vote the way they do. As countries become more democratic, are they less likely to fight wars or more likely to win them? There are serious disagreements about how to measure concepts like “democracy” and “war.” How does partisanship influence the way that people interpret information? During the COVID-19 pandemic, we have seen that Democrats and Republicans respond very differently to pronouncements from places like the World Health Organization or Center for Disease Control, presumed experts in their field. In studying the political behavior of humans, we are dealing with subjects that can respond and change their actions based on the very research that we conduct! But deciphering the political behavior of individuals, parties, and countries, among other actors, allows us to understand patterns from past events, predict future outcomes, and learn how to improve those outcomes. This course will explore various quantitative approaches to understanding the actions and decisions of political actors from individuals at the micro-level all the way to how countries interact at the macro-level. Students will not only become capable consumers of quantitative analysis, but also learn how to conduct research of their own and present their results in a clear and refined manner.

What Do Numbers Sound Like? An Exploration of Digital Sound and Music - {added 6/28}

Stephen Tufte, Assoc Prof of Physics

  • Core 121-07 – MWF 1:50-2:50pm

One of the primary ways that we receive information about the world around us is through our ears. Since the late 1800s we have been able to measure, record, and play back sound information using mechanical devices. In the last 50 years we have dramatically shifted the way that we do this. The vast majority of the sound information that currently barrages us is now digital.

This course will present the physical basis of sound (pressure waves in air) and will discuss how we can measure sound waves, with a strong focus on the modern approach of digitizing sound; in other words, turning sounds into numbers. We will learn how to use digital sound recorders along with powerful computer software to measure, store, transmit, and mathematically process this sound information into more meaningful forms.

By learning to analyze the sounds that surround us quantitatively, we can address a wide range of interesting and important questions. For example, what is high-fidelity and how is this affected by compression algorithms? Does vinyl sound better? What is a sound spectrum and how is it useful? How has the shift to digital music affected how music is recorded, distributed, and consumed? How are sounds used to scientifically investigate nature (e.g. seismology, echolocation, ultrasonic imaging, animal communication)?