Spring Numbers Sections

MWF Morning - 11:30am-12:30pm

 

Networks and Trees

Duncan Parks, Visiting Assist Prof of Biology

• Core 121-02 — MWF 11:30am-12:30pm
• Core 121-07– MWF 1:50-2:50pm

Please see description under 1:50pm portion.

What Do Numbers Sound Like? An Exploration of Digital Sound and Music

Stephen Tufte, Assoc Prof of Physics

• Core 121-01 – MWF 11:30am-12:30pm

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)?

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MWF 1:50-2:50pm

 

Order, Chaos & Randomness

Yung-Pin Chen, Prof of Statistics

• Core 121-05 – 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.

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The Promise and Peril of Cryptocurrency

Mark Dahl, Director of Watzek Library

• Core 121-09 – MWF 1:50-2:50pm

Hailed as “digital gold” and adopted by El Salvador as legal tender, cryptocurrency has fueled celebrity scandals, international crime, and regulatory battles over the past decade—all while consuming terawatts of power. Despite Bitcoin’s dramatic crash in 2022, the crypto industry is regaining momentum, rekindling debates about its rightful role in the global financial system.

This course will examine whether cryptocurrency represents a positive social and economic innovation, a destabilizing and destructive force, or merely a passing fad. In the first weeks, students will explore the blockchain technology that underpins cryptocurrencies like Bitcoin and gain an understanding of the vision of decentralized finance (DeFi) enabled by cryptocurrency. In later weeks, the course will delve into cryptocurrency’s societal impacts across a variety of topical areas, sharpening analytical skills through the use of quantitative datasets.

Key topics include the boom-and-bust ecosystem surrounding crypto, its qualities as a store of value and speculative asset, its cultural influence and socioeconomic implications, its connections to crime, its environmental impact, the challenges of regulation, and its future prospects. In addition to engaging with these topics through readings and discussions, students will develop skills in analyzing, presenting, and constructing data-driven arguments using technology tools in weekly lab sessions.

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Fire: Energy and Civilization

Julio de Paula, Prof of Chemistry

• Core 121-04 – 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.

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Bad Data, Misinterpretation, and Bullshit  {added 11/15/2024}

Alyx Dickson, Asst Speech & Debate Coach

• Core 121-06 - MWF 1:50-2:50pm

The average person is subjected to a staggering number of arguments on a daily basis. Marketing firms estimate that those claims number in the thousands or even tens of thousands. Yet, many of those claims are built upon unstable or deceitful foundations. In some cases, data are unreliable or invalid. In other cases, valid data are unintentionally misinterpreted or misunderstood. And finally, some arguments are intentionally designed to misrepresent data in order to deceive; colloquially, we can call those arguments bullshit.

This course will present an argumentative model to the claims we encounter. Students in the course will examine arguments from sports, politics, health, and economics among other subjects in learning both how to construct better quantitative arguments and to identify bullshit when they come across it.

Was the second sentence of this course description bullshit? That’s the type of claim we’ll examine in this course.

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The Meaning of Health: Bioethics and Medical Analytics

Devin Fitzpatrick, Visiting Asst Prof of Philosophy

• Core 121-03 - MWF 1:50-2:50pm

Recent advances in machine learning, including the development of large-language models like OpenAI’s ChatGPT, have continued a trend of improvements in statistical computing to produce complex outputs from vast amounts of data. At the cutting edge of this technology are healthcare analytics and bioinformatics, interpreting medical data and imagery to scientifically improve health outcomes. The results of this vital work can be life-changing for patients, but it comes with questions and risks. How can data be securely, fairly, and correctly analyzed and interpreted? Which data should be gathered, how, and to what ends? How should we understand “health,” as our goal or ideal, and why? In this course, we will learn the fundamentals of bioethics, focusing on the ethical obligations of health care providers and definitions of health, and of health care analytics using the R programming language, including linear regression analysis powered by machine learning.

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Networks and Trees

Duncan Parks, Visiting Assist Prof of Biology

• Core 121-02 — 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, and use directed graphs to generate critical-time schedules, with a diversion into the structure of generative AI models. 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.

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

Colin Patrick, Visiting Asst Prof of Philosophy

• Core 121-08– 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.

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ABCs of WAR (Wins Above Replacement): An Introduction to Sports Analytics

Matt Scroggs, Visiting Asst Prof of International Affairs

• Core 121-10 – MWF 1:50-2:50pm

In professional sports, the rise of analytics has been a topic of great interest as teams and individuals try to get an edge on their opponents. But what are sports analytics? And how are they used to better understand the sports that we follow? This course will provide an introduction to analytics as applied to three major U.S. sports: baseball, (American) football, and basketball.