Spring Numbers Sections

Spring 2024 Numbers Descriptions are below, listed in order of class time and then by professor last name.

The Numbers preference form is now closed.

Students needing to take Numbers in Spring 2024 were emailed the link the preference form to their LC email accounts on October 18th. The forms were open October 20-30th.

Students will be emailed their Spring 2024 placements by November 3rd (before the first round of general registration for Spring 2024). This email will be sent to LC accounts only.

If you missed submitting your preference form, please email GenEd@lclark.edu with all of your preferences and you will be wait listed for them.

 

MWF Mornings

What do numbers sound like? An exploration of digital sound and music

Albert Bae, Visiting Prof of Physics

Stephen Tufte, Assoc Prof of Physics

  • Core 121-02 – MWF 9:10-10:10am (Bae)
  • Core 121-01 – MWF 11:30am-12:30pm (Tufte)

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)?


Procedural Ethics and Moral Machines

Devin Fitzpatrick, Visiting Asst Prof of Philosophy

  • Core 121-04 - MWF 11:30am-12:30pm

Networks and Trees

Duncan Parks, Visiting Assist Prof of Biology

  • Core 121-03 – MWF 11:30am-12:30pm

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


MWF 1:50 - 2:50pm

Space, Time, Spacetime

Paul Allen, Assoc Prof of Mathematics

  • Core 121-10 – MWF 1:50 - 2:50pm

The goal of this course is to understand, at a conceptual level, the mathematical ideas of space and time present in Einstein’s relativity theories. We begin with a discussion of the concept of time, and explore how scientists and mathematicians (Einstein, Minkowski, Poincare) came to conclude that space and time can most effectively be considered as aspects of a single entity: spacetime. We proceed by exploring the mathematical tradition leading to the geometry of Riemann. The course concludes with Einstein’s reframing of Newton’s physics in the context of Riemannian geometry.


Think Like an Ant: An Introduction to Complex Systems

Ethan Davis, Digital and Data Science Specialist at Watzek

  • Core 121-11 - 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 modes of systems, and how to use those models to understand real-world behavior.


Procedural Ethics and Moral Machines

Devin Fitzpatrick, Visiting Asst Prof of Philosophy

  • Core 121-04 - MWF 11:30am-12:30pm
  • Core 121-05 – MWF 1:50-2:50pm

The recent advent of sophisticated chatbots like OpenAI’s Chat-GPT4 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 ML (machine learning) or 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 itself, and second, how human developers should (or if they can) 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 study ethical theory broadly, focusing on the differences between “procedural ethics” like utilitarianism and non-procedural approaches like virtue and care ethics, and the ethics of AI in particular, as we also learn how to create chatbots ourselves.


Political Math

Ben Gaskins, Assoc Prof of Political Science

  • Core 121-08 – MWF 1:50-2:50pm

This section will engage quantitative reasoning via the use of American elections, public opinion, and survey data. When trying to understand problems of social choice and democratic outcomes, scholars employ a wide variety of quantitative approaches. We will examine common problems associated with figuring out what citizens want, how they express their preferences, and how elections ultimately turn those preferences into policies.


Networks and Trees

Duncan Parks, Visiting Assist Prof of Biology

  • Core 121-03 – MWF 11:30am-12:30pm
  • Core 121-07 – MWF 1:50-2:50pm

The branching network known as a tree is a fundamental geometry in both natural and human systems, from circulatory systems in animals and plants to transportation and utility networks. We will start by applying an understanding of graph models to a variety of real-world examples (such as routing and distribution problems). We will use mathematical tools to build optimal networks in utility or telecommunications contexts. We will then use those tools to build evolutionary trees and evaluate cross-species comparisons in a tree-based context. Finally, we will examine the branching patterns of human circulatory systems and actual plants, examining both the performance of those systems and the fractal geometries that govern their development. Students need not have advanced mathematical skills to use these tools, and students of all backgrounds will encounter new methods and approaches in this course.


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

Colin Patrick, Visiting Assist Prof of Philosophy

  • Core 121-06– MWF 1:50-2:50pm

In this course we’ll learn about and critically examine: some of the benefits and pitfalls of quantificational and data-driven reasoning; some of the philosophical questions arising from efforts to assign numerical values to probability, human characteristics, behavior, and responsibility; and the increasing trend of outsourcing impactful decisions to computer algorithms and AI. 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, with a focus on its similarities to, and differences from, Eurogenic science and inductive reasoning, and its uniquely valuable perspective on many of 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 – assessing, for example, the scientific and logical merit of studies seeking to reveal the foundations of gender and gender-based social disparities in neurological and other biometric data.


Sidewalk Neuroscience: Data in Your Daily Life

Todd Watson, Assoc Prof of Psychology

  • Core 121-09– MWF 1:50-2:50pm

“Numbers have an important story to tell. They rely on you to give them a voice.” –Stephen Few

Should I worry that COVID might have long term effects on my brain? Is yawning really “contagious”? In life, we face questions both big and (seemingly) small. How should we answer them? Scientific journals, the popular press, and social media are awash in information, but how do we separate the good from the bad? How do we separate the bad from the VERY bad?

This section will focus on one of the key features of being a literate and active member of a democracy: the ability to evaluate and make arguments with data. Using the lens of psychology and neuroscience, we will explore ways to use simple, low tech experimental techniques and open-access statistical software and data sets to answer questions both big and small about the world around us. More broadly, will consider how quantitative reasoning can shape and strengthen arguments in academic research,