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Your search for courses · during 25SP · meeting requirements for FSR, Formal or Statistical Reasoning · returned 35 results
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CS 111 Introduction to Computer Science 6 credits
This course will introduce you to computer programming and the design of algorithms. By writing programs to solve problems in areas such as image processing, text processing, and simple games, you will learn about recursive and iterative algorithms, complexity analysis, graphics, data representation, software engineering, and object-oriented design. No previous programming experience is necessary.
- Spring 2025
- FSR, Formal or Statistical Reasoning QRE, Quantitative Reasoning
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NOT open to students who have completed any of the following course(s): CS 200 or greater with a grade of C- or better.
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CS 201 Data Structures 6 credits
Think back to your favorite assignment from Introduction to Computer Science. Did you ever get the feeling that “there has to be a better/smarter way to do this problem”? The Data Structures course is all about how to store information intelligently and access it efficiently. How can Google take your query, compare it to billions of web pages, and return the answer in less than one second? How can one store information so as to balance the competing needs for fast data retrieval and fast data modification? To help us answer questions like these, we will analyze and implement stacks, queues, trees, linked lists, graphs, and hash tables. Students who have received credit for a course for which Computer Science 201 is a prerequisite are not eligible to enroll in Computer Science 201.
- Spring 2025
- FSR, Formal or Statistical Reasoning QRE, Quantitative Reasoning
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Student has completed any of the following course(s): CS 111 with a grade of C- or better or received a score of 4 or better on the Computer Science A AP exam or received a Carleton Computer Science 111 Requisite Equivalency. Not open to students that have taken CS 200.
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CS 202 Mathematics of Computer Science 6 credits
This course introduces some of the formal tools of computer science, using a variety of applications as a vehicle. You’ll learn how to encode data so that when you scratch the back of a DVD, it still plays just fine; how to distribute “shares” of your floor’s PIN so that any five of you can withdraw money from the floor bank account (but no four of you can); how to play chess; and more. Topics that we’ll explore along the way include: logic and proofs, number theory, elementary complexity theory and recurrence relations, basic probability, counting techniques, and graphs.
- Spring 2025
- FSR, Formal or Statistical Reasoning
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Student has completed any of the following course(s): CS 111 with a grade of C- or better or received a score of 4 or better on the AP Computer Science exam or received a Carleton Computer Science 111 or better Requisite Equivalency AND MATH 101 or MATH 111 or greater with a grade of C- or better or greater or received a score of 4 or better on the Calculus AB AP exam or received a score of 4 or better on the Calculus BC AP exam or received a score of 5 or better on the Mathematics IB exam or received a Carleton MATH 111 or better Requisite Equivalency.
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CS 202.00 Spring 2025
- Faculty: Eric Alexander 🏫 👤
- Size:28
- M, WAnderson Hall 223 12:30pm-1:40pm
- FAnderson Hall 223 1:10pm-2:10pm
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15 – reserved for REQ: CS 202 Match (Condition Rule) until 03/07/2025.
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CS 208 Introduction to Computer Systems 6 credits
Are you curious what’s really going on when a computer runs your code? In this course we will demystify the machine and the tools that we use to program it. Our broad survey of how computer systems execute programs, store information, and communicate will focus on the hardware/software interface, including data representation, instruction set architecture, the C programming language, memory management, and the operating system process model.
- Spring 2025
- FSR, Formal or Statistical Reasoning
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Student has completed any one of the following course(s): CS 200 or CS 201 with a grade of C- or better or received a Carleton Computer Science 201 or better Requisite Equivalency.
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CS 208.01 Spring 2025
- Faculty: Tanya Amert 🏫 👤
- Size:28
- M, WLeighton 305 1:50pm-3:00pm
- FLeighton 305 2:20pm-3:20pm
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28 – reserved for REQ: CS 208 Match (Condition Rule) until 3/5/2025
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CS 251 Programming Languages: Design and Implementation 6 credits
What makes a programming language like “Python” or like “Java”? This course will look past superficial properties (like indentation) and into the soul of programming languages. We will explore a variety of topics in programming language construction and design: syntax and semantics, mechanisms for parameter passing, typing, scoping, and control structures. Students will expand their programming experience to include other programming paradigms, including functional languages like Scheme and ML.
- Spring 2025
- FSR, Formal or Statistical Reasoning
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Student has completed any one of the following course(s): CS 200 or CS 201 with a grade of C- or better or received a Carleton Computer Science 201 or better Requisite Equivalency.
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CS 251.00 Spring 2025
- Faculty: David Musicant 🏫 👤
- Size:28
- M, WHulings 316 9:50am-11:00am
- FHulings 316 9:40am-10:40am
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28 – reserved for REQ: CS 251 Match (Condition Rule) until 03/05/2025
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CS 251.02 Spring 2025
- Faculty: Bridger Herman 🏫
- Size:28
- M, WLeighton 305 11:10am-12:20pm
- FLeighton 305 12:00pm-1:00pm
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20 – reserved for REQ: CS 251 Match (Condition Rule) until 3/7/2025
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CS 252 Algorithms 6 credits
A course on techniques used in the design and analysis of efficient algorithms. We will cover several major algorithmic design paradigms (greedy algorithms, dynamic programming, divide and conquer, and network flow). Along the way, we will explore the application of these techniques to a variety of domains (natural language processing, economics, computational biology, and data mining, for example). As time permits, we will include supplementary topics like randomized algorithms, advanced data structures, and amortized analysis.
- Spring 2025
- FSR, Formal or Statistical Reasoning
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Student has completed any of the following course(s): CS 200 or CS 201 with a grade of C- or better or received a Carleton Computer Science 200 Requisite Equivalency AND CS 202 or MATH 236 with a grade of C- or better or received a Carleton Computer Science 202 Requisite Equivalency or received a Carleton Math 236 Requisite Equivalency. MATH 236 will be accepted in lieu of CS 202.
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CS 252.00 Spring 2025
- Faculty: Eric Alexander 🏫 👤
- Size:34
- M, WLanguage & Dining Center 104 9:50am-11:00am
- FLanguage & Dining Center 104 9:40am-10:40am
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34 – reserved for REQ: CS 252 Match (Condition Rule) until 3/5/2025
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CS 254 Computability and Complexity 6 credits
An introduction to the theory of computation. What problems can and cannot be solved efficiently by computers? What problems cannot be solved by computers, period? Topics include formal models of computation, including finite-state automata, pushdown automata, and Turing machines; formal languages, including regular expressions and context-free grammars; computability and uncomputability; and computational complexity, particularly NP-completeness.
- Spring 2025
- FSR, Formal or Statistical Reasoning
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Student has completed any of the following course(s): CS 200 or CS 201 with a grade of C- or better or received a Carleton Computer Science 200 Requisite Equivalency AND CS 202 or MATH 236 with a grade of C- or better or received a Carleton Computer Science 202 Requisite Equivalency or received a Carleton Math 236 Requisite Equivalency. MATH 236 will be accepted in lieu of CS 202.
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CS 257 Software Design 6 credits
It’s easy to write a mediocre computer program, and lots of people do it. Good programs are quite a bit harder to write, and are correspondingly less common. In this course, we will study techniques, tools, and habits that will improve your chances of writing good software. While working on several medium-sized programming projects, we will investigate code construction techniques, debugging and profiling tools, testing methodologies, UML, principles of object-oriented design, design patterns, and user interface design.
- Spring 2025
- FSR, Formal or Statistical Reasoning
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Student has completed any one of the following course(s): CS 200 or CS 201 with a grade of C- or better or received a Carleton Computer Science 201 or better Requisite Equivalency.
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CS 257.01 Spring 2025
- Faculty: Jeff Ondich 🏫 👤
- Size:28
- M, WAnderson Hall 329 8:30am-9:40am
- FAnderson Hall 329 8:30am-9:30am
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12 – reserved for REQ: CS 257 Match (Condition Rule) until 3/5/2025
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CS 257.02 Spring 2025
- Faculty: Anya Vostinar 🏫 👤
- Size:28
- M, WAnderson Hall 329 11:10am-12:20pm
- FAnderson Hall 329 12:00pm-1:00pm
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22 – reserved for REQ: CS 257 Match (Condition Rule) until 3/7/2025
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CS 304 Social Computing 6 credits
The last decade has seen a vast increase in the number of applications that connect people with one another. This course presents an interdisciplinary introduction to social computing, a field of study that explores how computational techniques and artifacts are used to support and understand social interactions. We will examine a number of socio-technical systems (such as wikis, social media platforms, and citizen science projects), discuss the design principles used to build them, and analyze how they help people mobilize and collaborate with one another. Assignments will involve investigating datasets from online platforms and exploring current research in the field.
- Spring 2025
- FSR, Formal or Statistical Reasoning QRE, Quantitative Reasoning
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Student has completed any one of the following course(s): CS 200 or CS 201 with a grade of C- or better or received a Carleton Computer Science 201 or better Requisite Equivalency.
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CS 304.00 Spring 2025
- Faculty: Sneha Narayan 🏫 👤
- Size:16
- M, WAnderson Hall 323 12:30pm-1:40pm
- FAnderson Hall 323 1:10pm-2:10pm
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16 – reserved for REQ: CS 304 Match (Condition Rule) until 2/28/2025
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CS 311 Computer Graphics 6 credits
Scientific simulations, movies, and video games often incorporate computer-generated images of fictitious worlds. How are these worlds represented inside a computer? How are they “photographed” to produce the images that we see? What performance constraints and design trade-offs come into play? In this course we learn the basic theory and methodology of three-dimensional computer graphics, including both triangle rasterization and ray tracing. Familiarity with vectors and matrices is recommended but not required.
- Spring 2025
- FSR, Formal or Statistical Reasoning QRE, Quantitative Reasoning
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Student has completed any of the following course(s): CS 208 with grade of C- or better.
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CS 320 Machine Learning 6 credits
What does it mean for a machine to learn? Much of modern machine learning focuses on identifying patterns in large datasets and using these patterns to make predictions about the future. Machine learning has impacted a diverse array of applications and fields, from scientific discovery to healthcare to education. In this artificial intelligence-related course, we’ll both explore a variety of machine learning algorithms in different application areas, taking both theoretical and practical perspectives, and discuss impacts and ethical implications of machine learning more broadly. Topics may vary, but typically focus on regression and classification algorithms, including neural networks.
Not open to students who have previously taken CS 320* (*=Junior Seminar).
X seats held for CS Match until the day after X priority registration.
- Spring 2025
- FSR, Formal or Statistical Reasoning
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Student has completed any of the following course(s): CS 200 or CS 201 with a grade of C- or better or received a Carleton Computer Science 200 Requisite Equivalency AND CS 202 or MATH 236 with a grade of C- or better or received a Carleton Computer Science 202 Requisite Equivalency or received a Carleton Math 236 Requisite Equivalency. MATH 236 will be accepted in lieu of CS 202.
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CS 320.00 Spring 2025
- Faculty: Tom Finzell 🏫
- Size:34
- M, WLanguage & Dining Center 104 11:10am-12:20pm
- FLanguage & Dining Center 104 12:00pm-1:00pm
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19 – reserved for REQ: CS 320 Match (Condition Rule) until 3/7/2025
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CS 347 Advanced Software Design 6 credits
This course helps students to strengthen their ability to design modular, extensible and maintainable software. The focus of the course is on the design of modern cloud applications. Students will learn how to decompose complex applications into a set of back-end services, develop and debug these services, and deploy them in the cloud. This class is structured around a large project that will be extended over the course of the term.
Not open to students who have previously taken CS 347* (*=Junior Seminar).
X seats held for CS Match until the day after X priority registration.
- Spring 2025
- FSR, Formal or Statistical Reasoning
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Student has completed the following course(s): CS 257 with a grade of C- or better or received a Carleton Computer Science 257 Requisite Equivalency.
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CS 348 Parallel and Distributed Computing 6 credits
As multi-core machines become more prevalent, different programming paradigms have emerged for harnessing extra processors for better performance. This course explores parallel computation for both shared memory and distributed parallel programming paradigms. In particular, we will explore how these paradigms affect the code we write, the libraries we use, and the advantages and disadvantages of each. Topics will include synchronization primitives across these models for parallel execution, debugging concurrent programs, fork/join parallelism, example parallel algorithms, computational complexity and performance considerations, computer architecture as it relates to parallel computation, and related theory topics.
- Spring 2025
- FSR, Formal or Statistical Reasoning
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Student has completed any one of the following course(s): CS 200 or CS 201 with a grade of C- or better or received a Carleton Computer Science 201 or better Requisite Equivalency.
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CS 348.00 Spring 2025
- Faculty: David Musicant 🏫 👤
- Size:34
- M, WAnderson Hall 329 1:50pm-3:00pm
- FAnderson Hall 329 2:20pm-3:20pm
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21 – reserved for REQ: CS 348 Match (Condition Rule) until 3/7/2025
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CS 361 Artificial Life and Digital Evolution 6 credits
The field of artificial life seeks to understand the dynamics of life by separating them from the substrate of DNA. In this course, we will explore how we can implement the dynamics of life in software to test and generate biological hypotheses, with a particular focus on evolution. Topics will include the basic principles of biological evolution, transferring experimental evolution techniques to computational systems, cellular automata, computational modeling, and digital evolution. All students will be expected to complete and present a term research project recreating and extending recent work in the field of artificial life.
- Spring 2025
- FSR, Formal or Statistical Reasoning
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Student has completed any one of the following course(s): CS 200 or CS 201 with a grade of C- or better or received a Carleton Computer Science 201 or better Requisite Equivalency.
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LING 110 Mechanics of Language: Systems and Structures 6 credits
The capacity to acquire and use natural languages such as English is surely one of the more remarkable features of human nature. In this course, we explore several aspects of this ability. Topics include the sound systems of natural languages, the structure of words, principles that regulate word order, the course of language acquisition in children, and what these reveal about the nature of the mind.
Not open to students who have taken LING 100 – The Noun.
- Spring 2025
- FSR, Formal or Statistical Reasoning
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LING 110.00 Spring 2025
- Faculty: Cherlon Ussery 🏫 👤
- Size:30
- T, THWeitz Center 235 1:15pm-3:00pm
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Sophomore priority
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LING 115 Introduction to the Theory of Syntax 6 credits
This course is organized to enable the student to actively participate in the construction of a rather elaborate theory of the nature of human cognitive capacity to acquire and use natural languages. In particular, we concentrate on one aspect of that capacity: the unconscious acquisition of a grammar that enables a speaker of a language to produce and recognize sentences that have not been previously encountered. In the first part of the course, we concentrate on gathering notation and terminology intended to allow an explicit and manageable description. In the second part, we depend on written and oral student contributions in a cooperative enterprise of theory construction.
- Spring 2025
- FSR, Formal or Statistical Reasoning
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LING 115.00 Spring 2025
- Faculty: Catherine Fortin 🏫 👤
- Size:20
- M, WLeighton 426 11:10am-12:20pm
- FLeighton 426 12:00pm-1:00pm
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Sophomore Priority
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MATH 111 Introduction to Calculus 6 credits
An introduction to the differential and integral calculus. Derivatives, antiderivatives, the definite integral, applications, and the fundamental theorem of calculus.
Not open to students who have received credit for MATH 101
- Spring 2025
- FSR, Formal or Statistical Reasoning
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Student has received a score of 111 on the Carleton Math Placement exam. NOT open to students who have received credit for Mathematics 101 or received a score of 4 or better on the Calculus AB AP exam or received a score of 4 or better on the Calculus BC AP exam or received a score of 5 or better on the Calculus IB exam or received a Carleton Math 111 or better Requisite Equivalency. For more information, see the Mathematics' web page.
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MATH 120 Calculus 2 6 credits
Inverse functions, integration by parts, improper integrals, modeling with differential equations, vectors, calculus of functions of two independent variables including directional derivatives and double integrals, Lagrange multipliers.
Not open to students who have received credit for MATH 211 or have a score of 4 or 5 on the AP Calculus BC exam.
- Spring 2025
- FSR, Formal or Statistical Reasoning
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Student has completed any of the following course(s): MATH 101 or MATH 111 with a grade of C- or better or received a scored of 4 or better on AP Calculus AB test or received a scored of 5 or better on Calculus IB test or received a Carleton Math 111 Requisite Equivalency or placement exam. NOT open to students who received a scored of 4 or better on the AP Calculus BC test or completed MATH 211 with a grade of C- or better.
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MATH 134 Linear Algebra with Applications 6 credits
Linear algebra centers on the geometry, algebra, and applications of linear equations. It is pivotal to many areas of mathematics, natural sciences, computer science, and engineering. To study linear equations, we will develop concepts including matrix algebra, linear independence, determinants, eigenvectors, and orthogonality. Students will use these tools to model real world problems and solve these problems using computational software.
This course is not open to students who have received credit for MATH 232.
- Spring 2025
- FSR, Formal or Statistical Reasoning
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Not open to students who have taken MATH 232 or equivalents.
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MATH 210 Calculus 3 6 credits
Vectors, curves, calculus of functions of three independent variables, including directional derivatives and triple integrals, cylindrical and spherical coordinates, line integrals, Green’s theorem, sequences and series, power series, Taylor series.
This course cannot be substituted for MATH 211
- Spring 2025
- FSR, Formal or Statistical Reasoning
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Student has completed any of the following course(s): MATH 120 with a grade of C- or better. Students who have received a score of 4 or greater on the AP Calculus BC exam should register for MATH 211.
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MATH 232 Linear Algebra 6 credits
Linear algebra centers on the study of highly structured functions called linear transformations. Given the abundance of nonlinear functions in mathematics, it may come as a surprise that restricting to linear ones opens the door to a rich and powerful theory that finds applications throughout mathematics, statistics, computer science, and the natural and social sciences. Linear transformations are everywhere, once we know what to look for. They appear in calculus as the functions that are used to define lines and planes in Euclidean space. In fact, differentiation is also a linear transformation that takes one function to another. The course focuses on developing geometric intuition as well as computational matrix methods. Topics include kernel and image of a linear transformation, vector spaces, determinants, eigenvectors and eigenvalues.
This course is not open to students who have received credit for MATH 134.
- Spring 2025
- FSR, Formal or Statistical Reasoning
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Student has completed any of the following course(s): MATH 120 or MATH 211 with a grade of C- or better or received a Carleton Math 211 Requisite Equivalency.
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MATH 236 Mathematical Structures 6 credits
Basic concepts and techniques used throughout mathematics. Topics include logic, mathematical induction and other methods of proof, problem solving, sets, cardinality, equivalence relations, functions and relations, and the axiom of choice. Other topics may include: algebraic structures, graph theory, and basic combinatorics.
- Spring 2025
- FSR, Formal or Statistical Reasoning
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Student has completed any of the following course(s): MATH 134 or MATH 232 AND MATH 210 or MATH 211 with a grade of C- or better or equivalent.
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MATH 241 Ordinary Differential Equations 6 credits
Ordinary differential equations are a fundamental language used by mathematicians, scientists, and engineers to describe processes involving continuous change. In this course we develop ordinary differential equations as models of real world phenomena and explore the mathematical ideas that arise within these models. Topics include separation of variables; phase portraits; equilibria and their stability; non-dimensionalization; bifurcation analysis; and modeling of physical, biological, chemical, and social processes.
- Spring 2025
- FSR, Formal or Statistical Reasoning
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Student must have completed any of the following course(s): MATH 134 or MATH 232 AND MATH 120 or MATH 211 with a grade of C- or better or equivalents.
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MATH 271 Optimization 6 credits
Optimization is all about selecting the "best" thing. Finding the most likely strategy to win a game, the route that gets you there the fastest, or the curve that most closely fits given data are all examples of optimization problems. In this course we study linear optimization (also known as linear programming), the simplex method, and duality from both a theoretical and a computational perspective. Applications will be selected from statistics, economics, computer science, and more. Additional topics in nonlinear and convex optimization will be covered as time permits.
- Spring 2025
- FSR, Formal or Statistical Reasoning
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Student must have completed any of the following course(s): MATH 134 or MATH 232 AND MATH 120 or MATH 211 with a grade of C- or better or equivalents.
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MATH 331 Real Analysis II (Measure Theory) 6 credits
Further topics in analysis such as measure theory, Lebesgue integration or Banach and Hilbert spaces.
- Spring 2025
- FSR, Formal or Statistical Reasoning
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Student has completed any of the following course(s): MATH 321 with a grade of C- or better.
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MATH 341 Partial Differential Equations 6 credits
An introduction to partial differential equations with emphasis on the heat equation, wave equation, and Laplace’s equation. Topics include the method of characteristics, separation of variables, Fourier series, Fourier transforms and existence/uniqueness of solutions.
- Spring 2025
- FSR, Formal or Statistical Reasoning
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Student has completed any of the following course(s): MATH 241 with grade of C- or better.
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MATH 342 Introduction to Groups, Rings, and Fields 6 credits
Introduction to algebraic structures, including groups, rings, and fields. Homomorphisms and quotient structures, polynomials, unique factorization. Other topics may include applications such as Burnside’s counting theorem, symmetry groups, polynomial equations, or geometric constructions.
- Spring 2025
- FSR, Formal or Statistical Reasoning
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Student has completed any of the following course(s): MATH 236 with a grade of C- or better or received a Carleton Mathematics 236 Requisite Equivalency.
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PHIL 210 Logic 6 credits
The study of formal logic has obvious and direct applicability to a wide variety of disciplines (including mathematics, computer science, linguistics, philosophy, cognitive science, and many others). Indeed, the study of formal logic helps us to develop the tools and know-how to think more clearly about arguments and logical relationships in general; and arguments and logical relationships form the backbone of any rational inquiry. In this course we will focus on propositional logic and predicate logic, and look at the relationship that these have to ordinary language and thought.
- Spring 2025
- FSR, Formal or Statistical Reasoning
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PHIL 210.00 Spring 2025
- Faculty: Jason Decker 🏫 👤
- Size:25
- M, WWeitz Center 233 9:50am-11:00am
- FWeitz Center 233 9:40am-10:40am
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PSYC 200 Measurement and Data Analysis in Psychology 6 credits
The course considers the role of measurement and data analysis focused on behavioral sciences. Various forms of measurement and standards for the evaluation of measures are explored. Students learn how to summarize, organize, and evaluate data using a variety of techniques that are applicable to research in psychology and other disciplines. Among the analyses discussed and applied are tests of means, various forms of analysis of variance, correlation and regression, planned and post-hoc comparisons, as well as various non-parametric tests. Research design is also explored.
Requires concurrent registration in PSYC 201.
Waitlist Information: If you have already registered for PSYC 200 and PSYC 201, but would like to waitlist for a second PSYC 201 lab section, you will need to remove the lecture section by clicking the Minus Sign icon next to PSYC 200, prior to completing the waitlist process. If you are offered a seat in the lab, you will be able to register for the lecture at the same time.
- Spring 2025
- FSR, Formal or Statistical Reasoning QRE, Quantitative Reasoning
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Student has completed any of the following course(s): PSYC 110 with a grade of C- or better or received a score of 4 or better on the Psychology AP exam or received a score of 6 or better on the Psychology IB exam OR CGSC/PSYC 232 and CGSC/PSYC 233 with a grade of C- or better.
- PSYC 201: Measurement and Data Analysis Lab
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PSYC 200.00 Spring 2025
- Faculty: Mitchell Campbell 🏫 👤
- Size:26
- T, THAnderson Hall 121 10:10am-11:55am
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STAT 120 Introduction to Statistics 6 credits
Introduction to statistics and data analysis. Practical aspects of statistics will be emphasized, including extensive use of programming in the statistical software R, interpretation and communication of results. Topics include: exploratory data analysis, correlation and linear regression, design of experiments, the normal distribution, randomization approach to inference, sampling distributions, estimation, and hypothesis testing. Students who have taken Mathematics 211 are encouraged to consider the more advanced Mathematics 240/Statistics 250 Probability/Statistical Inference sequence.
Not open to students who have already received credit for Psychology 200/201, Sociology/Anthropology 239 or Statistics 250
- Spring 2025
- FSR, Formal or Statistical Reasoning QRE, Quantitative Reasoning
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Not open to students that have taken PSYC 200 , PSYC 201, SOAN 239 or STAT 250.
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STAT 220 Introduction to Data Science 6 credits
This course will cover the computational side of data analysis, including data acquisition, management, and visualization tools. Topics may include: data scraping, data wrangling, data visualization using packages such as ggplots, interactive graphics using tools such as Shiny, an introduction to classification methods, and understanding and visualizing spatial data. We will use the statistics software R in this course.
- Spring 2025
- FSR, Formal or Statistical Reasoning QRE, Quantitative Reasoning
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Student has completed any of the following course(s): STAT 120 or STAT 230, or STAT 250 with a grade of C- or better.
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STAT 230 Applied Regression Analysis 6 credits
A second course in statistics covering simple linear regression, multiple regression and ANOVA, and logistic regression. Exploratory graphical methods, model building and model checking techniques will be emphasized with extensive use of statistical software R to analyze real-life data.
- Spring 2025
- FSR, Formal or Statistical Reasoning QRE, Quantitative Reasoning
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Student has completed any of the following course(s): STAT 120 or STAT 250 or PSYC 200 or SOAN 239 with a grade of C- or better or received a score of 4 or better on the Statistics AP exam.
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STAT 250 Introduction to Statistical Inference 6 credits
Introduction to modern mathematical statistics. The mathematics underlying fundamental statistical concepts will be covered as well as applications of these ideas to real-life data. Topics include: resampling methods (permutation tests, bootstrap intervals), classical methods (parametric hypothesis tests and confidence intervals), parameter estimation, goodness-of-fit tests, regression, and Bayesian methods. The statistical package R will be used to analyze data sets.
- Spring 2025
- FSR, Formal or Statistical Reasoning QRE, Quantitative Reasoning
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Student has completed any of the following course(s): MATH 240 with a grade of C- or better.
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STAT 285 Statistical Consulting 2 credits
Students will apply their statistical knowledge by analyzing data problems solicited from the Northfield community. Students will also learn basic consulting skills, including communication and ethics.
This course is repeatable, priority will be given first to Statistics majors who have not previously taken the course and then to other students who have not taken the course. Students who have previously taken the course should reach out to the instructor to discuss entry into the course.
12 seats held for Statistics majors until the day after rising junior priority registration.
- Spring 2025
- FSR, Formal or Statistical Reasoning QRE, Quantitative Reasoning
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Student has completed the following course(s): STAT 230 with a grade of C- or better.
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STAT 285.00 Spring 2025
- Faculty: Katie St. Clair 🏫 👤
- Grading:S/CR/NC
- TCMC 304 10:10am-11:55am
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All interested students are encouraged to add to the waitlist and the instructor will reach out after registration. This course is repeatable, but if the instructor cannot admit every student on the waitlist, priority will be given first to Statistics majors who have not previously taken the course and then to other students who have not taken the course.
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STAT 320 Time Series Analysis 6 credits
Models and methods for characterizing dependence in data that are ordered in time. Emphasis on univariate, quantitative data observed over evenly spaced intervals. Topics include perspectives from both the time domain (e.g., autoregressive and moving average models, and their extensions) and the frequency domain (e.g., periodogram smoothing and parametric models for the spectral density). Exposure to matrix algebra may be helpful but is not required.
- Spring 2025
- FSR, Formal or Statistical Reasoning QRE, Quantitative Reasoning
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Student has completed the following course(s): STAT 230 and STAT 250 with a grade of C- or better.