statistics honors thesis

Honors Theses

What this handout is about.

Writing a senior honors thesis, or any major research essay, can seem daunting at first. A thesis requires a reflective, multi-stage writing process. This handout will walk you through those stages. It is targeted at students in the humanities and social sciences, since their theses tend to involve more writing than projects in the hard sciences. Yet all thesis writers may find the organizational strategies helpful.

Introduction

What is an honors thesis.

That depends quite a bit on your field of study. However, all honors theses have at least two things in common:

• They are based on students’ original research.
• They take the form of a written manuscript, which presents the findings of that research. In the humanities, theses average 50-75 pages in length and consist of two or more chapters. In the social sciences, the manuscript may be shorter, depending on whether the project involves more quantitative than qualitative research. In the hard sciences, the manuscript may be shorter still, often taking the form of a sophisticated laboratory report.

Who can write an honors thesis?

In general, students who are at the end of their junior year, have an overall 3.2 GPA, and meet their departmental requirements can write a senior thesis. For information about your eligibility, contact:

• UNC Honors Program
• Your departmental administrators of undergraduate studies/honors

Why write an honors thesis?

Satisfy your intellectual curiosity This is the most compelling reason to write a thesis. Whether it’s the short stories of Flannery O’Connor or the challenges of urban poverty, you’ve studied topics in college that really piqued your interest. Now’s your chance to follow your passions, explore further, and contribute some original ideas and research in your field.

Develop transferable skills Whether you choose to stay in your field of study or not, the process of developing and crafting a feasible research project will hone skills that will serve you well in almost any future job. After all, most jobs require some form of problem solving and oral and written communication. Writing an honors thesis requires that you:

• ask smart questions
• acquire the investigative instincts needed to find answers
• navigate libraries, laboratories, archives, databases, and other research venues
• develop the flexibility to redirect your research if your initial plan flops
• master the art of time management
• hone your argumentation skills
• organize a lengthy piece of writing
• polish your oral communication skills by presenting and defending your project to faculty and peers

Work closely with faculty mentors At large research universities like Carolina, you’ve likely taken classes where you barely got to know your instructor. Writing a thesis offers the opportunity to work one-on-one with a with faculty adviser. Such mentors can enrich your intellectual development and later serve as invaluable references for graduate school and employment.

Open windows into future professions An honors thesis will give you a taste of what it’s like to do research in your field. Even if you’re a sociology major, you may not really know what it’s like to be a sociologist. Writing a sociology thesis would open a window into that world. It also might help you decide whether to pursue that field in graduate school or in your future career.

How do you write an honors thesis?

Get an idea of what’s expected.

It’s a good idea to review some of the honors theses other students have submitted to get a sense of what an honors thesis might look like and what kinds of things might be appropriate topics. Look for examples from the previous year in the Carolina Digital Repository. You may also be able to find past theses collected in your major department or at the North Carolina Collection in Wilson Library. Pay special attention to theses written by students who share your major.

Choose a topic

Ideally, you should start thinking about topics early in your junior year, so you can begin your research and writing quickly during your senior year. (Many departments require that you submit a proposal for an honors thesis project during the spring of your junior year.)

How should you choose a topic?

• Read widely in the fields that interest you. Make a habit of browsing professional journals to survey the “hot” areas of research and to familiarize yourself with your field’s stylistic conventions. (You’ll find the most recent issues of the major professional journals in the periodicals reading room on the first floor of Davis Library).
• Set up appointments to talk with faculty in your field. This is a good idea, since you’ll eventually need to select an advisor and a second reader. Faculty also can help you start narrowing down potential topics.
• Look at honors theses from the past. The North Carolina Collection in Wilson Library holds UNC honors theses. To get a sense of the typical scope of a thesis, take a look at a sampling from your field.

What makes a good topic?

• It’s fascinating. Above all, choose something that grips your imagination. If you don’t, the chances are good that you’ll struggle to finish.
• It’s doable. Even if a topic interests you, it won’t work out unless you have access to the materials you need to research it. Also be sure that your topic is narrow enough. Let’s take an example: Say you’re interested in the efforts to ratify the Equal Rights Amendment in the 1970s and early 1980s. That’s a big topic that probably can’t be adequately covered in a single thesis. You need to find a case study within that larger topic. For example, maybe you’re particularly interested in the states that did not ratify the ERA. Of those states, perhaps you’ll select North Carolina, since you’ll have ready access to local research materials. And maybe you want to focus primarily on the ERA’s opponents. Beyond that, maybe you’re particularly interested in female opponents of the ERA. Now you’ve got a much more manageable topic: Women in North Carolina Who Opposed the ERA in the 1970s and 1980s.
• It contains a question. There’s a big difference between having a topic and having a guiding research question. Taking the above topic, perhaps your main question is: Why did some women in North Carolina oppose the ERA? You will, of course, generate other questions: Who were the most outspoken opponents? White women? Middle-class women? How did they oppose the ERA? Public protests? Legislative petitions? etc. etc. Yet it’s good to start with a guiding question that will focus your research.

Goal-setting and time management

The senior year is an exceptionally busy time for college students. In addition to the usual load of courses and jobs, seniors have the daunting task of applying for jobs and/or graduate school. These demands are angst producing and time consuming If that scenario sounds familiar, don’t panic! Do start strategizing about how to make a time for your thesis. You may need to take a lighter course load or eliminate extracurricular activities. Even if the thesis is the only thing on your plate, you still need to make a systematic schedule for yourself. Most departments require that you take a class that guides you through the honors project, so deadlines likely will be set for you. Still, you should set your own goals for meeting those deadlines. Here are a few suggestions for goal setting and time management:

Start early. Keep in mind that many departments will require that you turn in your thesis sometime in early April, so don’t count on having the entire spring semester to finish your work. Ideally, you’ll start the research process the semester or summer before your senior year so that the writing process can begin early in the fall. Some goal-setting will be done for you if you are taking a required class that guides you through the honors project. But any substantive research project requires a clear timetable.

Set clear goals in making a timetable. Find out the final deadline for turning in your project to your department. Working backwards from that deadline, figure out how much time you can allow for the various stages of production.

Here is a sample timetable. Use it, however, with two caveats in mind:

• The timetable for your thesis might look very different depending on your departmental requirements.
• You may not wish to proceed through these stages in a linear fashion. You may want to revise chapter one before you write chapter two. Or you might want to write your introduction last, not first. This sample is designed simply to help you start thinking about how to customize your own schedule.

Sample timetable

Avoid falling into the trap of procrastination. Once you’ve set goals for yourself, stick to them! For some tips on how to do this, see our handout on procrastination .

Consistent production

It’s a good idea to try to squeeze in a bit of thesis work every day—even if it’s just fifteen minutes of journaling or brainstorming about your topic. Or maybe you’ll spend that fifteen minutes taking notes on a book. The important thing is to accomplish a bit of active production (i.e., putting words on paper) for your thesis every day. That way, you develop good writing habits that will help you keep your project moving forward.

Make yourself accountable to someone other than yourself

Since most of you will be taking a required thesis seminar, you will have deadlines. Yet you might want to form a writing group or enlist a peer reader, some person or people who can help you stick to your goals. Moreover, if your advisor encourages you to work mostly independently, don’t be afraid to ask them to set up periodic meetings at which you’ll turn in installments of your project.

Brainstorming and freewriting

One of the biggest challenges of a lengthy writing project is keeping the creative juices flowing. Here’s where freewriting can help. Try keeping a small notebook handy where you jot down stray ideas that pop into your head. Or schedule time to freewrite. You may find that such exercises “free” you up to articulate your argument and generate new ideas. Here are some questions to stimulate freewriting.

Questions for basic brainstorming at the beginning of your project:

• What do I already know about this topic?
• Why do I care about this topic?
• Why is this topic important to people other than myself
• What more do I want to learn about this topic?
• What is the main question that I am trying to answer?
• Where can I look for additional information?
• Who is my audience and how can I reach them?
• How will my work inform my larger field of study?
• What’s the main goal of my research project?

Questions for reflection throughout your project:

• What’s my main argument? How has it changed since I began the project?
• What’s the most important evidence that I have in support of my “big point”?
• What questions do my sources not answer?
• How does my case study inform or challenge my field writ large?
• Does my project reinforce or contradict noted scholars in my field? How?
• What is the most surprising finding of my research?
• What is the most frustrating part of this project?
• What is the most rewarding part of this project?
• What will be my work’s most important contribution?

Research and note-taking

In conducting research, you will need to find both primary sources (“firsthand” sources that come directly from the period/events/people you are studying) and secondary sources (“secondhand” sources that are filtered through the interpretations of experts in your field.) The nature of your research will vary tremendously, depending on what field you’re in. For some general suggestions on finding sources, consult the UNC Libraries tutorials . Whatever the exact nature of the research you’re conducting, you’ll be taking lots of notes and should reflect critically on how you do that. Too often it’s assumed that the research phase of a project involves very little substantive writing (i.e., writing that involves thinking). We sit down with our research materials and plunder them for basic facts and useful quotations. That mechanical type of information-recording is important. But a more thoughtful type of writing and analytical thinking is also essential at this stage. Some general guidelines for note-taking:

First of all, develop a research system. There are lots of ways to take and organize your notes. Whether you choose to use note cards, computer databases, or notebooks, follow two cardinal rules:

• Make careful distinctions between direct quotations and your paraphrasing! This is critical if you want to be sure to avoid accidentally plagiarizing someone else’s work. For more on this, see our handout on plagiarism .
• Record full citations for each source. Don’t get lazy here! It will be far more difficult to find the proper citation later than to write it down now.

Keeping those rules in mind, here’s a template for the types of information that your note cards/legal pad sheets/computer files should include for each of your sources:

Abbreviated subject heading: Include two or three words to remind you of what this sources is about (this shorthand categorization is essential for the later sorting of your sources).

Complete bibliographic citation:

• author, title, publisher, copyright date, and page numbers for published works
• box and folder numbers and document descriptions for archival sources
• complete web page title, author, address, and date accessed for online sources

Notes on facts, quotations, and arguments: Depending on the type of source you’re using, the content of your notes will vary. If, for example, you’re using US Census data, then you’ll mainly be writing down statistics and numbers. If you’re looking at someone else’s diary, you might jot down a number of quotations that illustrate the subject’s feelings and perspectives. If you’re looking at a secondary source, you’ll want to make note not just of factual information provided by the author but also of their key arguments.

Your interpretation of the source: This is the most important part of note-taking. Don’t just record facts. Go ahead and take a stab at interpreting them. As historians Jacques Barzun and Henry F. Graff insist, “A note is a thought.” So what do these thoughts entail? Ask yourself questions about the context and significance of each source.

Interpreting the context of a source:

• Who wrote/created the source?
• When, and under what circumstances, was it written/created?
• Why was it written/created? What was the agenda behind the source?
• How was it written/created?
• If using a secondary source: How does it speak to other scholarship in the field?

Interpreting the significance of a source:

• How does this source answer (or complicate) my guiding research questions?
• Does it pose new questions for my project? What are they?
• Does it challenge my fundamental argument? If so, how?
• Given the source’s context, how reliable is it?

You don’t need to answer all of these questions for each source, but you should set a goal of engaging in at least one or two sentences of thoughtful, interpretative writing for each source. If you do so, you’ll make much easier the next task that awaits you: drafting.

The dread of drafting

Why do we often dread drafting? We dread drafting because it requires synthesis, one of the more difficult forms of thinking and interpretation. If you’ve been free-writing and taking thoughtful notes during the research phase of your project, then the drafting should be far less painful. Here are some tips on how to get started:

Sort your “evidence” or research into analytical categories:

• Some people file note cards into categories.
• The technologically-oriented among us take notes using computer database programs that have built-in sorting mechanisms.
• Others cut and paste evidence into detailed outlines on their computer.
• Still others stack books, notes, and photocopies into topically-arranged piles.There is not a single right way, but this step—in some form or fashion—is essential!

If you’ve been forcing yourself to put subject headings on your notes as you go along, you’ll have generated a number of important analytical categories. Now, you need to refine those categories and sort your evidence. Everyone has a different “sorting style.”

Formulate working arguments for your entire thesis and individual chapters. Once you’ve sorted your evidence, you need to spend some time thinking about your project’s “big picture.” You need to be able to answer two questions in specific terms:

• What is the overall argument of my thesis?
• What are the sub-arguments of each chapter and how do they relate to my main argument?

Keep in mind that “working arguments” may change after you start writing. But a senior thesis is big and potentially unwieldy. If you leave this business of argument to chance, you may end up with a tangle of ideas. See our handout on arguments and handout on thesis statements for some general advice on formulating arguments.

Divide your thesis into manageable chunks. The surest road to frustration at this stage is getting obsessed with the big picture. What? Didn’t we just say that you needed to focus on the big picture? Yes, by all means, yes. You do need to focus on the big picture in order to get a conceptual handle on your project, but you also need to break your thesis down into manageable chunks of writing. For example, take a small stack of note cards and flesh them out on paper. Or write through one point on a chapter outline. Those small bits of prose will add up quickly.

Just start! Even if it’s not at the beginning. Are you having trouble writing those first few pages of your chapter? Sometimes the introduction is the toughest place to start. You should have a rough idea of your overall argument before you begin writing one of the main chapters, but you might find it easier to start writing in the middle of a chapter of somewhere other than word one. Grab hold where you evidence is strongest and your ideas are clearest.

Keep up the momentum! Assuming the first draft won’t be your last draft, try to get your thoughts on paper without spending too much time fussing over minor stylistic concerns. At the drafting stage, it’s all about getting those ideas on paper. Once that task is done, you can turn your attention to revising.

Peter Elbow, in Writing With Power, suggests that writing is difficult because it requires two conflicting tasks: creating and criticizing. While these two tasks are intimately intertwined, the drafting stage focuses on creating, while revising requires criticizing. If you leave your revising to the last minute, then you’ve left out a crucial stage of the writing process. See our handout for some general tips on revising . The challenges of revising an honors thesis may include:

Juggling feedback from multiple readers

A senior thesis may mark the first time that you have had to juggle feedback from a wide range of readers:

• your adviser
• a second (and sometimes third) faculty reader
• the professor and students in your honors thesis seminar

You may feel overwhelmed by the prospect of incorporating all this advice. Keep in mind that some advice is better than others. You will probably want to take most seriously the advice of your adviser since they carry the most weight in giving your project a stamp of approval. But sometimes your adviser may give you more advice than you can digest. If so, don’t be afraid to approach them—in a polite and cooperative spirit, of course—and ask for some help in prioritizing that advice. See our handout for some tips on getting and receiving feedback .

Refining your argument

It’s especially easy in writing a lengthy work to lose sight of your main ideas. So spend some time after you’ve drafted to go back and clarify your overall argument and the individual chapter arguments and make sure they match the evidence you present.

Organizing and reorganizing

Again, in writing a 50-75 page thesis, things can get jumbled. You may find it particularly helpful to make a “reverse outline” of each of your chapters. That will help you to see the big sections in your work and move things around so there’s a logical flow of ideas. See our handout on  organization  for more organizational suggestions and tips on making a reverse outline

Plugging in holes in your evidence

It’s unlikely that you anticipated everything you needed to look up before you drafted your thesis. Save some time at the revising stage to plug in the holes in your research. Make sure that you have both primary and secondary evidence to support and contextualize your main ideas.

Saving time for the small stuff

Even though your argument, evidence, and organization are most important, leave plenty of time to polish your prose. At this point, you’ve spent a very long time on your thesis. Don’t let minor blemishes (misspellings and incorrect grammar) distract your readers!

Formatting and final touches

You’re almost done! You’ve researched, drafted, and revised your thesis; now you need to take care of those pesky little formatting matters. An honors thesis should replicate—on a smaller scale—the appearance of a dissertation or master’s thesis. So, you need to include the “trappings” of a formal piece of academic work. For specific questions on formatting matters, check with your department to see if it has a style guide that you should use. For general formatting guidelines, consult the Graduate School’s Guide to Dissertations and Theses . Keeping in mind the caveat that you should always check with your department first about its stylistic guidelines, here’s a brief overview of the final “finishing touches” that you’ll need to put on your honors thesis:

• Honors Thesis
• Name of Department
• University of North Carolina
• These parts of the thesis will vary in format depending on whether your discipline uses MLA, APA, CBE, or Chicago (also known in its shortened version as Turabian) style. Whichever style you’re using, stick to the rules and be consistent. It might be helpful to buy an appropriate style guide. Or consult the UNC LibrariesYear Citations/footnotes and works cited/reference pages  citation tutorial
• In addition, in the bottom left corner, you need to leave space for your adviser and faculty readers to sign their names. For example:

Approved by: _____________________

Adviser: Prof. Jane Doe

• This is not a required component of an honors thesis. However, if you want to thank particular librarians, archivists, interviewees, and advisers, here’s the place to do it. You should include an acknowledgments page if you received a grant from the university or an outside agency that supported your research. It’s a good idea to acknowledge folks who helped you with a major project, but do not feel the need to go overboard with copious and flowery expressions of gratitude. You can—and should—always write additional thank-you notes to people who gave you assistance.
• Formatted much like the table of contents.
• You’ll need to save this until the end, because it needs to reflect your final pagination. Once you’ve made all changes to the body of the thesis, then type up your table of contents with the titles of each section aligned on the left and the page numbers on which those sections begin flush right.
• Each page of your thesis needs a number, although not all page numbers are displayed. All pages that precede the first page of the main text (i.e., your introduction or chapter one) are numbered with small roman numerals (i, ii, iii, iv, v, etc.). All pages thereafter use Arabic numerals (1, 2, 3, 4, 5, etc.).
• Your text should be double spaced (except, in some cases, long excerpts of quoted material), in a 12 point font and a standard font style (e.g., Times New Roman). An honors thesis isn’t the place to experiment with funky fonts—they won’t enhance your work, they’ll only distract your readers.
• In general, leave a one-inch inch margin on all sides. However, for the copy of your thesis that will be bound by the library, you need to leave a 1.25-inch margin on the left.

How do I defend my honors thesis?

Graciously, enthusiastically, and confidently. The term defense is scary and misleading—it conjures up images of a military exercise or an athletic maneuver. An academic defense ideally shouldn’t be a combative scene but a congenial conversation about the work’s merits and weaknesses. That said, the defense probably won’t be like the average conversation that you have with your friends. You’ll be the center of attention. And you may get some challenging questions. Thus, it’s a good idea to spend some time preparing yourself. First of all, you’ll want to prepare 5-10 minutes of opening comments. Here’s a good time to preempt some criticisms by frankly acknowledging what you think your work’s greatest strengths and weaknesses are. Then you may be asked some typical questions:

• What is the main argument of your thesis?
• How does it fit in with the work of Ms. Famous Scholar?
• Have you read the work of Mr. Important Author?

NOTE: Don’t get too flustered if you haven’t! Most scholars have their favorite authors and books and may bring one or more of them up, even if the person or book is only tangentially related to the topic at hand. Should you get this question, answer honestly and simply jot down the title or the author’s name for future reference. No one expects you to have read everything that’s out there.

• Why did you choose this particular case study to explore your topic?
• If you were to expand this project in graduate school, how would you do so?

Should you get some biting criticism of your work, try not to get defensive. Yes, this is a defense, but you’ll probably only fan the flames if you lose your cool. Keep in mind that all academic work has flaws or weaknesses, and you can be sure that your professors have received criticisms of their own work. It’s part of the academic enterprise. Accept criticism graciously and learn from it. If you receive criticism that is unfair, stand up for yourself confidently, but in a good spirit. Above all, try to have fun! A defense is a rare opportunity to have eminent scholars in your field focus on YOU and your ideas and work. And the defense marks the end of a long and arduous journey. You have every right to be proud of your accomplishments!

Works consulted

We consulted these works while writing this handout. This is not a comprehensive list of resources on the handout’s topic, and we encourage you to do your own research to find additional publications. Please do not use this list as a model for the format of your own reference list, as it may not match the citation style you are using. For guidance on formatting citations, please see the UNC Libraries citation tutorial . We revise these tips periodically and welcome feedback.

Atchity, Kenneth. 1986. A Writer’s Time: A Guide to the Creative Process from Vision Through Revision . New York: W.W. Norton.

Barzun, Jacques, and Henry F. Graff. 2012. The Modern Researcher , 6th ed. Belmont, CA: Wadsworth Cengage Learning.

Elbow, Peter. 1998. Writing With Power: Techniques for Mastering the Writing Process . New York: Oxford University Press.

Graff, Gerald, and Cathy Birkenstein. 2014. “They Say/I Say”: The Moves That Matter in Academic Writing , 3rd ed. New York: W.W. Norton and Company.

Lamott, Anne. 1994. Bird by Bird: Some Instructions on Writing and Life . New York: Pantheon.

Lasch, Christopher. 2002. Plain Style: A Guide to Written English. Philadelphia: University of Pennsylvania Press.

Turabian, Kate. 2018. A Manual for Writers of Term Papers, Theses, Dissertations , 9th ed. Chicago: University of Chicago Press.

You may reproduce it for non-commercial use if you use the entire handout and attribute the source: The Writing Center, University of North Carolina at Chapel Hill

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Undergraduate research in statistics provides opportunities for gaining experience in data analysis, reading and writing about statistics, and collaboration with Statistics faculty mentors and their research teams. By doing an undergraduate research project, you will develop a deeper understanding of statistics, whether as a first/second year student considering a statistics major, or as a junior/senior considering graduate school and other career options. It is recommended that students considering graduate school participate in research during the course of their academic studies.

The two largest programs for Undergraduate research in data science and statistics are the Undergraduate Research Program in Statistics and the honors thesis. There are also other faculty research projects that include undergraduates that are not in either of these programs. Other statistics research-related activities involving undergraduates include the following:

• The Undergraduate Research Opportunity Program (UROP) provides research opportunities for first and second year students.
• The annual  Michigan Student Symposium for Interdisciplinary Statistical Sciences   (MSSISS) . MSSISS provides a forum for presenting completed research projects, and an opportunity to see the range and scope of statistical activity across the University of Michigan. Most of the research projects are carried out by graduate students, but undergraduates are welcome to participate and many have!
• The Statistics department occasionally runs a data mining competition. 
• A relevant national forum is the free  Electronic Undergraduate Statistics Research Conference , and the associated  Undergraduate Statistics Project Competition .
• The   Center for Statistics, Computing, and Analytics Research   (CSCAR) sometimes employs undergraduates. Email  [email protected]  if you are interested in learning more about opportunities for involvement with CSCAR.

Undergraduate Research Program in Statistics (URPS)

URPS is a competitive program where Statistics faculty offer undergraduate reserach projects in the winter semester.

2025 Projects will be posted, including meeting information and an application link, in November 2024.

Past Projects

Writing an Honors Thesis

An honors thesis provides an opportunity for eligible students to carry out faculty-supervised research in their senior year. The application process and requirements for the Statistics ,   Data Science , and Informatics honors programs are described on the department website.  Students are encouraged to contribute their thesis to the   archive of honors theses   at the University of Michigan Library.

Past Honors Theses

• Qi Chen, Statistics - Conditional Clustering Method on KNN for Big Data
• Yize Hao, Data Science - PAL versus SMC: Two Approaches in Compartmental Modeling
• Zhongming Jiang, Statistics - Large N, Small T, Multiple P. A Causal Matrix Completion Method for CRM Panel Data
• Xinpei Shen, Data Science - A Dimension Reduction Approach to Multivariate Mediation Analysis
• Weizhe Sun,  Statistics -   Model Based Inference of Stochastic Volatility via Iterated Filtering
• Jiayi Xu, Data Science - Investigating Measles Dynamics in the Pre-Vaccination Era: A POMP Model Approach
• Ziyu Zhou, Statistics - Kernel Dimension Reduction with Missing Data
• Zuyuan Han, Data Science - Signature Methods in Variance Swap Pricing
• Yiwen (Oliver) Wu, Data Science - Assessment of Privacy in Synthetic Data
• Chen Shang, Statistics and Mathematics -  Mat ́ern Models for Graphs: Definition and Inference
• Mingxuan Ge, Statistics and Mathematics -  Redistribution of Equity Returns After The Minimum Wage Policy
• Will Schmutz, Data Science -  Statistically Ranking Teams in the English Premier League
• Xinyi Xie, Statistics and Mathematics -  Logistic Regression With Log-Contrast Transformation
• Yiling Huang, Statistics and Mathematics -  Balance Assessment of Matched Data with Multiple Treatment Levels
• Chenxi Fan, Statistics - An evaluation of information criteria for model selection in quasi-likelihood regression, with application to modeling COVID mortality and case incidence in the United States
• Siqi Li, Statistics - Local False Discovery Rates in the Multi-Parameter Case, with Application to Epigenetics of Human Growth
• Wanqi Liang, Data Science - An Applet and Tutorial for Calculating the Sample Size (and Power) for a Clustered Sequential, Multiple Assignment Randomized Trial
• Juejue Wang, Statistics - Comparison of Document Co-clustering aslgorithms and Application of Single-cell RNA-seq Data Clustering to Twitter Data
• Chao Peter Yang, Data Science - The Classical-Romantic Dichotomy: A Machine Learning Approach
• Ziyang Shao, Statistics - College Ranking Based on Pairwise Preferences
• Haoyu Chen, Statistics -  Kernel Methods for Activation Energy Prediction
• We Han, Statistics -  Argo Data Mean Field Modeling
• Jiahui Ji, Statistics -  NYC Optimal Transport and Ridesharing
• Xiaotong Yang, Statistics -  Fitting mechanistic models to Daphnia panel data within a panelPOMP framework
• Shuaiji Li, Statistics - Auto Sales Prediction with attention to the Parable of the boiled frog: Functional Data Analysis and Time Series Forecasting
• Zifan Li, Statistics - Perturbation Algorithms for Adversarial Online Learning
• Tianwen Ma, Statistics - A Functional Data Analysis Approach to Looking at Handwriting Data
• Xige Zhang, Statistics - Robustness of the Contextual Bandit Algorithm to A Physical Activity Motivation Effect
• Rong Zhou, Statistics - The Comparison of ACI and MCB Methods for Choosing a Set that Contains the Optimal Dynamic Treatment Regime
• Xinyan Han, Statistics - An Empirical Comparison of Various Online Binary Classification Algorithms
• Hwanwoo Kim, Statistics - A Sample Size Calculator for SMART Pilot Studies
• Yuchen Lin, Statistics - Auto Car Sales Prediction: A Statistical Study Using Functional Data Analysis and Time Series 
• Kelsey Pakkala, Statistics - A Functional Data Analysis Approach to Women’s Health Screening Adherence for Breast Cancer and Cervical Cancer  
• Emily Slade, Statistics - Functional Data Analysis in Cephalometric Tracing and Mandibular Examination
• Ben Charoenwong, Statistics - An Exploration of Simple Optimized Technical Trading Strategies
• Matthew Lomont, Statistics - Detecting Active Pathways in Gene Sets
• Xuanzhong Wang, Statistics - An Exploration of Influential Observations in the Panel Study of Income Dynamics  - An Exploration of Gender Gap in Labor Market; Money Resource Allocation to Children in PSID
• Christopher Worsham, Statistics - A Stochastic Model of Retinal Development in Zebrafish

Faculty Supervising Undergraduate Research

• Danny Almiral l supervises undergraduate researchers with an interest in applied issues in causal inference, dynamic treatment regimens and sequential multiple assignment randomized trials (SMART). Projects include: o Topics in design and analysis of clinical trials for adaptive treatment plans, by Hwanwoo Kim. Co-advised with Ed Ionides. 2nd prize winner in the national Undergraduate Statistics Project Competition. o Adaptive intervention designs in substance use prevention. o An Investigation of Predictor for Tailoring Ecological momentary Assessment and Contextual Recall. o Introduction to Sequential Multiple Assignment Randomized Trials (SMARTs) with Zero Inflated Count Outcomes for the Development of Dynamic Treatment Regimens (DTRs): with application to substance use research.

If you are interested in working with Dr. Almirall, please visit his web page first to see if he is currently accepting new students: http://www-personal.umich.edu/~dalmiral/ .

• Moulinath Banerjee has supervised undergraduate projects including: o Detecting Active Pathways in Gene Sets.

• Ben Hansen has supervised undergraduate projects including: o Proposals for Generating and Utilizing Well Informed Initialization Values to Improve the Computational Efficiency of Optmatch.

• Al Hero has supervised undergraduate projects including: o Dynamic distributed multidimensional scaling (MDS) for data visualization. o Spatio-temporal network anomaly detection in Abilene data streams. o Canonical correlation analysis for sunspot and coronal mass ejection image representation.

• Tailen Hsing has supervised undergraduate projects including: o Analyzing Argo Data Co-advised with Stilian Stoev o Argo Data Mean Field Modeling Co-advised with Stilian Stoev

• Ed Ionides has supervised undergraduate projects including: o Topics in design and analysis of clinical trials for adaptive treatment plans. Co-advised with Danny Almirall. 2nd prize winner in the national Undergraduate Statistics Project Competition. o Modeling cholera as a stochastic process. o Building POMP objects in R for a dynamic general stochastic equilibrium model.. o Investigating sequential Monte Carlo methods for time series analysis. o Identification of insurance companies at risk of insolvency. Co-advised with Kristen Moore.

• Long Nguyen has supervised undergraduate projects including: o Traffic Flow and Density Analysis of NYC TLC Taxi Data. o NYC Optimal Transport and Ridesharing.

• Kerby Shedden supervises undergraduate research with an emphasis on bioinformatics. Examples include: o Statistical analysis of high frequency motion capture and muscle activity data: applications to assessing development of trunk postural control. o Sparsity in the distribution of correlation coefficients in molecular screening data. Co-advised with Ji Zhu. o Individual-specific and disease-specific factors in acquired copy number variations in cancer. o Detection of DNA lesions in acute myelogenous leukemia. o Two-tiered false discovery rates. o Selective targeting of stem-cell-like cancer cell lines. Co-advised with Gus Rosania.

• Ambuj Tewari has supervised undergraduate research projects and an honors theses. Former projects include: o Development of an Android app for mobile health. o Simulations comparing bandit algorithms. o Development of HeartSteps, an Android app for encouraging physical activity. Co-advised with Predrag Klasnja o Empirical evaluation of online learning algorithms (honors thesis). o Numerical experiments with Lasso in high dimensional VAR models.

• Ji Zhu has supervised undergraduate research projects and honors theses. Projects include: o Forecasting Stock Returns in the Chinese Market with Convolutional Neural Networks. o Medical Image Classification Building Upon Pre-trained Neural Networks: An Application on Diabetic Retinopathy Detection.

Undergraduate Research Opportunity Program (UROP)

UROP is a great way to get an introduction to research during the first two years at University of Michigan. See the  UROP website  for more information. For the most part, Statistics and Data Science research projects require foundational preparation in statistics, mathematics and computer programming. Sometimes, first year students have sufficient preparation through AP courses and other experiences. Otherwise, it may be appropriate to take introductory statistics, computer programming and calculus courses in the first year to be ready for a second year UROP project.

Other Opportunities for Undergraduate Research

It is possible to conduct undergraduate research that does not fall into either the honors program or UROP. If you find yourself interested in the research agenda of a Statistics faculty member, you can email to enquire about available options. This research can be carried out as part of Stats 489 [Independent Study in Statistics], as a paid position if one is available, or as an informal arrangement for neither course credit nor payment. Arrangements must be made on a case-by-case basis with the potential faculty superviser.

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Research and Discovery

Engaging in undergraduate research and other enrichment experiences can help students discover their passions, explore potential careers paths, enhance their learning experience at Cal, create new knowledge, and contribute to society.

Review the  statistics major map and berkeley discovery student resources to explore some possibilities..

• Statistics Department Opportunities
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The Statistics Department at Berkeley offers opportunities for undergraduate students to gain research experience through projects mentored by PhD students, postdocs, or faculty.

Undergraduate researchers meet with a mentor for one hour every week throughout the term and present their work at a poster session during RRR week. In addition, a faculty sponsor meets with them at least twice during the term.

Participants have the option to receive payment or up to 3 Stat 199 course credits, which count toward graduation but not toward satisfying your major requirements.

Students who have an idea for a research project may earn Stat 199 credit provided they find a faculty member in the Statistics Department to supervise their research.

To graduate with honors, Statistics students must have a 3.3 GPA or higher in the major, in upper division major courses, and overall; and they must enroll in Stat H195 for a letter grade and write a satisfactory honors thesis under the direction of a Statistics faculty member. An honors thesis can be completed in one or two semesters, depending on the scope of the project. In total, the honors thesis should require at least 3 units worth of work.

The Office of Undergraduate Research & Scholarships is Cal's hub for undergraduate research and prestigious scholarships. This office runs programs such as the Undergraduate Research and Apprentice (URAP) , Haas Scholars Senior Capstone Experience for All Majors , Summer Undergraduate Research Fellowships (SURF) , Underrepresented Researchers of Color (UROC) , and provides a database for Research Programs and Scholarships .

BIDS is a central hub of data-intensive research, open source software, and data science training programs at UC Berkeley.

The Cal NERDS Program is comprised of a suite of programs and initiatives that provide faculty mentored research opportunities, specialized tech training, graduate school preparation, career coaching, community building, and professional development to high achieving STEM undergraduates and graduate students.

The Data Science Discovery Program connects undergraduates with hands-on, team-based opportunities in cutting-edge data research projects at UC Berkeley, government agencies, community groups, and entrepreneurial ventures.

• Participate in a Data Competition like DataFest
• American Statistical Association (AMSTAT)
• National Science Foundation (NSF) Research Experiences for Undergraduates (REUs)
• Research in Industrial Projects for Students (RIPS)
• US Census Bureau Student and Research Opportunities
• Virtual Student Federal Service
• Advances of Machine Learning in Theory & Applications (AMALTHEA) REU

How to find a Faculty Member to Supervise Your Research

Students should explore the Statistics faculty research interests to find out which faculty members specialize in a topic related to their research topic. Contact potential faculty advisors to see if they can meet with you to discuss your interests and the possibility of them advising you on an independent research. If a faculty member has agreed, they will need to confirm with an Undergraduate Student Services Advisor in order to set up the Stat 199 or Stat H195 course. Students will be provided with the enrollment information needed to register for the course after it is set up.

The Office of Undergraduate Research also has great advice on how to find faculty mentors .

What does undergraduate research in Statistics look like?

Emeritus Professor David Aldous has examples of previous research projects and honors theses  he advised on.

Statistics & Data Science

Dietrich college of humanities and social sciences, statistics & data science dietrich honors thesis requirements, eligibility.

Eligibility is determined by Dietrich College. Students who are eligible will be notified prior to their senior year.

Dietrich Requirements : 

• Students must have a major in Dietrich College , either as a primary or an additional major; or be in the BHA program.
• Cumulative QPA through the end of the junior year of at least 3.25 overall, and 3.50 in the Dietrich College major associated with the proposed project.
• Departmental sponsorship in the form of an agreement by a faculty member to serve as advisor for the 2-semester/18 unit Honors project (graduate students may not serve as advisors; adjunct faculty may do so, but only in collaboration with a regular faculty member), and approval by the department head.

Application

See the Dietrich College website for all application information .

Stat & DS Requirements Overview

The below guidelines apply to any Statistics & Data Science students who are doing an honors thesis that has been approved through the Stat & DS department (i.e. Stat & DS sign the thesis paperwork). If you are a Stat & DS student who is doing a Dietrich senior honors thesis through a different department (i.e. a different department than Stat & DS is signing off on it) then these guidelines do not apply to you.

In order to be approved for a thesis with the Stat & DS department the project needs to have a significant statistical component. This will be discussed and confirmed during the proposal approval phase of applying. 

Senior Year - Fall Semester

Progress Paper

The Dietrich College senior honors thesis is a year-long project. As such, after the fall semester of a student’s senior year a progress report will be due to Undergraduate Program Director, Peter Freeman , for review.

Requirements:

• Minimum length - 5 pages of text (not including graphs/figures/results)
• This paper should build substantially on the proposal, and lay out what work has been done up to this point, as well as an action plan for the spring semester. 
• Must be sent to Undergraduate Program Director, Peter Freeman , by the last day of classes for the fall semester (typically the first week of December).

Senior Year - Spring Semester

Final Thesis

In alignment with a typical advanced data analysis (ADA) project in the field of Statistics the minimum required length of the final thesis must be a minimum of 15 written pages, no more than 18 single-spaced pages, 12-point font. This does *not* include figures.

• Figures can be embedded within the text (so long as the overall text length requirement is met) but can also be provided as appendices after the main body of the text.
• Reports should be written in IMRaD format (Introduction, Methods, Results, and Discussion), where the "Introduction" can be a Background and Significance section followed by a Data section.
• All theses are due to the Undergraduate Program Director,  Peter Freeman , and Department Head,  Rebecca Nugent , at the end of the 12th week of class in spring semester (roughly the first week of April). 

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College of Liberal Arts and Sciences

Department of Statistics

Honors program.

UConn offers an honors track for students majoring in statistics or mathematics-statistics.

Administered through the Honors Program , these tracks provide highly-motivated and mathematically-talented students with opportunities like advanced course work, in-depth research opportunities, and professional development experiences. These programs enable students to obtain an undergraduate statistics education of the highest level, preparing them for graduate study or a career in industry, education, or government.

The Department of Statistics offers honors conversions of courses at various levels of sophistication for honors students interested in statistics.

Honors Thesis

Students in the honors program in statistics must complete an honors thesis under the supervision of statistics faculty through STAT 4389. Students in the honors program in mathematics-statistics must also complete an honors thesis, but may do so under the supervision of statistics faculty through STAT 4389 or mathematics faculty through an appropriate MATH thesis course.

Planning a Thesis

A senior thesis in statistics can be either a research project or a deeper study of an important statistical topic that goes beyond what is covered in undergraduate courses. Some faculty who advise a senior thesis will expect the student to begin work on the thesis at the start of the senior year, or during the summer before the senior year, and thereby spend two semesters plus perhaps the preceding summer on the thesis. Other faculty who advise a senior thesis only require one semester of work.

We strongly urge students to finalize their thesis advisor and topic by the spring of junior year. The student and thesis advisor will determine the scope of the thesis and how much work needs to be done in the summer and fall, subject to the approval of the student’s honors advisor.

Courses and Credits

If a student spends more than one semester working on a statistics thesis, then each semester of thesis work before the last semester should be taken as a section of either STAT 4299 or STAT 4389, both of which can be repeated for credit and converted to an honors course. STAT 4299 is typically more appropriate than STAT4389 if the student is learning a new topic related to their research, rather than conducting the research itself. The final semester of thesis work should be taken as STAT 4389 with honors conversion.

Note: a maximum of three credits of STAT 4299 and a maximum of three credits of STAT 4389 can be counted toward the requirement of at least 15 honors credits in or related to the major.

Registration for both STAT 4299 or STAT 4389 may be accomplished through the Student Administration System with a permission number from the supervising faculty during open enrollment periods or can be added using the Student Enrollment Request form . If the section number of the course is not set up yet in Student Admin, contact the statistics undergraduate program director, who will work with the Department’s administration and the Registrar to assign you an appropriate section number for the course.

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Undergraduate Honors Theses - Mathematics and Statistics

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Home > Mathematics and Statistics > Math Honors

Honors Theses in Mathematics and Statistics

Honors theses from 2023 2023.

Elliptic Curves Over Finite Fields , Christopher S. Calger

Honors Theses from 2022 2022

Representation Theory and its Applications in Physics , Jakub Bystrický

Decoding Cyclic Codes via Gröbner Bases , Eduardo Sosa

Decomposing Manifolds in Low-dimensions: from Heegaard Splittings to Trisections , Suixin "Cindy" Zhang

Honors Theses from 2021 2021

A Generalized Polar-coordinate Integration Formula, Oscillatory Integral Techniques, and Applications to Convolution Powers of Complex-valued Functions on $\mathbb{Z}^d$ , Huan Q. Bui

Counting Conjugacy Classes of Elements of Finite Order in Compact Exceptional Groups , Qidong He

Honors Theses from 2019 2019

Basis Reduction in Lattice Cryptography , Raj Kane

Primes in Arithmetical Progression , Edward C. Wessel

Honors Theses from 2018 2018

Parametric Polynomials for Small Galois Groups , Claire Huang

Algebraic Number Theory and Simplest Cubic Fields , Jianing Yang

On Spectral Theorem , Muyuan Zhang

Honors Theses from 2017 2017

Chow's Theorem , Yohannes D. Asega

Tying the Knot: Applications of Topology to Chemistry , Tarini S. Hardikar

Normal Surfaces and 3-Manifold Algorithms , Josh D. Hews

Some Examples of the Interplay Between Algebra and Topology , Joseph D. Malionek

Honors Theses from 2015 2015

The Central Hankel Transform , Matthew J. Levine

Quantization of Analysis , Kelvin K. Lui

Honors Theses from 2013 2013

The Eichler-Selberg Trace Formula for Level-One Hecke Operators , Alex Barron

A Monte Carlo Simulation Study of the Performance of Hypothesis Tests Under Assumption Violations , Gareth Cleveland

Unknotting Number and Combinatorial Sutured Manifold Theory , Alexander Rasmussen

Honors Theses from 2012 2012

The Radon Transform and the Mathematics of Medical Imaging , Jen Beatty

Recurrence Relations, Fractals, and Chaos: Implications for Analyzing Gene Structure , Sarah. M. Harmon

Odd or Even: Uncovering Parity of Rank in a Family of Rational Elliptic Curves , Anika Lindemann

Honors Theses from 2010 2010

Describing Gray Wolf Movement Using Brownian Motion and PDEs , Ashley M. Blum

No, I’m really, really bad at math: Competition for self-verification , Alexandra E. Wesnousky

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Honors in the Statistics Major

To be considered for acceptance into Honors in the Major in Statistics, a student must have declared Statistics, must have a 3.3 University GPA, and must have completed and an Introductory Statistics Course ( STAT 240 ,  STAT 301 ,  STAT 324  or  STAT 371 ),   STAT/​MATH  309 , and  STAT 333  or  STAT 340 (or other courses with the approval of the advisor) with a GPA of 3.500 or higher in these three classes. Please see an advisor for admission.

Guidance for Honors in the Statistics Major

See  The Guide  for all requirements. In short:

• At the time of graduation, the student must have a grade point average of 3.5 or higher in Statistics Department courses and also in all courses taken at UW-Madison.
• Complete 2 statistics courses (other than intro stat or Stat 699) for  “Honors”  or take an additional 3-credit statistics elective. Again, see  The Guide  for exact details. To see which courses are offered for Honors credit (which may vary from one semester to the next and from one section to the next), check  UW course search & enroll , click on “Honors” then check “Honors optional”.
• Complete the Stat 681-682 sequence (6 cr.) and produce a  Senior Honors Project under the supervision of a participating faculty member of the Department of Statistics or 6 credits of pre-approved research credits outside of the Statistics Department.

Note:  Prior to enrollment in the Stat 681-682 senior honors project, students must complete the  Honors Project Application Form and have it signed by both academic advisor and honors project faculty mentor. All students seeking to earn Honors in the Major must find a participating faculty member who is willing to serve as the honors project mentor .

Senior Honors projects with a non-Statistics faculty mentor

Students seeking Honors in Statistics may request to do their Senior Honors project (also called “capstone”) with a non-Statistics faculty mentor, so long as their project has high statistical content. Statistical methods are meant to be applied outside of Statistics. Many faculty outside of the Statistics department can provide opportunities to analyze large data sets and to apply statistical contributions to a domain area.

The student needs to enroll for the honors thesis course (681-682 or a substitute, such as 699) within the other department. After completion, these credits can be approved as satisfying Stat 681-682, provided that the thesis report is submitted to the Statistics Major advisor at the end of the project, and provided that the capstone experience is approved by the Statistics Undergraduate Committee. For this, the student must complete and submit the  Capstone Approval Form  in collaboration with his/her instructor, who will have direct oversight of the research experience and the responsibility to assign the final grade.

Expectations for Senior Honors Projects in Statistics

This is an accordion element with a series of buttons that open and close related content panels.

Each Honors student is encouraged to prepare a written report in which the main results of her/his project are presented. The writing of the project must be the work of the student. The report needs to be well-organized and well-written. The exact structure of the report will depend on the particular nature of the project and the advice of the project advisor. Roughly speaking, the main body of the report should contain on the order of 5000 words (or more). This does not include tables, plots, and, where appropriate, computer code. The number of pages devoted to such items may exceed the number of pages of text. It is strongly urged that the written report be prepared using LaTeX.

The report should be sent electronically to the project advisor and to [email protected], to be included in a “library” of all Honor’s reports. A hard copy of the report should also be given to the project advisor if s/he wishes to receive one.

In addition, each Honors student is encouraged to prepare a poster of their project for presentation at a Department Poster Session or at the Campus-wide Undergraduate Symposium , typically in mid April.

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Campus Address : University of New Mexico Department of Mathematics and Statistics 1 University of New Mexico, MSC01 1115 Albuquerque, NM 87131

Physical Address : University of New Mexico Department of Mathematics and Statistics 311 Terrace Street NE, Room 389 Albuquerque, NM  87106

Phone: (505) 277-4613 Fax: (505) 277-0988

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Undergraduate Honors Program

The Mathematics and Statistics Undergraduate Honors Program is designed to provide intensive and personal instruction for selected students. For those who intend to pursue graduate or professional study, it provides extra guidance and leads to graduating with departmental honors at commencement. Please see the Department of Mathematics and Statistics Undergraduate Honors Thesis fact sheet for more details. Email your completed Application for Dept. Honors form to [email protected]

Intensify and deepen the student's knowledge within the fields of Mathematics and Statistics

Put this specialized knowledge into better relationship with the larger area of the student's specialization and related fields

Bring the student under closer guidance of, and acquaintance with, faculty in the Department of Mathematics and Statistics

Graduation with Departmental Honors with cum laude, magna cum laude, or summa cum laude mention from the Department. The departmental honors designation will be reflected on the student's diploma

Opportunity for mentored research at the undergraduate level and completion of an Undergraduate Honors thesis

Requirements:

    The following requirements for departmental honors are in addition to the requirements for the undergraduate major in the Department of Mathematics and Statistics:

Grade point average of 3.5 in the Mathematics or Statistics major and overall GPA of 3.2 at UNM

Finding a Mathematics or Statistics faculty to mentor the student in the Undergraduate Honors thesis project

Completion of the Department of Mathematics and Statistics Honors form and submission to the Department Advisor no later than two full semesters before graduation

Approval of the Undergraduate Honors thesis research project by the Undergraduate Honors Committee

Successful completion of six credit hours of independent study under either Math 499 or Stat 495

Submission of the Undergraduate Honors thesis to the faculty mentor and the Undergraduate Honors Committee no later than ten days before the thesis defense

Oral presentation and defense of the Undergraduate Honors thesis. In cases where the Undergraduate Honors Committee requests additional changes to the thesis, the student will be allowed one week to submit a final corrected version of the Undergraduate Honors thesis.

Funding Information

The department may have limited funds for the purchase of materials and supplies, conference travel to disseminate the results of the undergraduate research, or purchase of Honors cords for commencement. These funds are awarded by the Undergraduate Honors Committee on a competitive basis. For more information please contact the Department Advisor.

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Honors Theses

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Home > STUDENT-WORKS > DEPT-HONORS > MATH-HONORS

Mathematics and Statistics Honors Theses

This series contains undergraduate honors theses based on the thesis professor’s department.

If you are an undergraduate student submitting your honors thesis, please click here to access the submission form.

Theses/Dissertations from 2023 2023

Exploration and Statistical Modeling of Profit , Caleb Gibson

Theses/Dissertations from 2021 2021

Peg Solitaire on Graphs In Which We Allow Merging and Jumping , Amanda L. McKinney

Theses/Dissertations from 2019 2019

Unifications of Pythagorean Triple Schema , Emily Hammes

Investigation of optimal dosing strategies for Ertapenem for varying BMI using mathematical modeling , Bethany Jewett

Theses/Dissertations from 2018 2018

Covering Arrays for Equivalence Classes of Words , Joshua Cassels and Anant Godbole

Classifying textual fast food restaurant reviews quantitatively using text mining and supervised machine learning algorithms , Lindsey Wright

Theses/Dissertations from 2016 2016

A Physiologically-Based Pharmacokinetic Model for the Antibiotic Levofloxacin , Paezha M. McCartt

Theses/Dissertations from 2015 2015

Modeling Enrollment at a Regional University using a Discrete-Time Markov Chain , Zachary T. Helbert

A Physiologically-Based Pharmacokinetic Model for Vancomycin , Rebekah White

Theses/Dissertations from 2013 2013

Uphill & Downhill Domination in Graphs and Related Graph Parameters. , Jessie Deering

Numerical study of the effect of blood vessel geometry on plaque formation. , Lindsey Fox

General Bounds on the Downhill Domination Number in Graphs. , William Jamieson

Soliton Solutions of the Nonlinear Schrödinger Equation. , Erin Middlemas

Theses/Dissertations from 2012 2012

Modeling Antibiotic Resistance when Adding a New Antibiotic to a Hospital Setting. , Brandi N. Canter

A Methodology for the Analysis of Fly Activity Data. , Ruoying Wang

Theses/Dissertations from 2011 2011

A Singular Perturbation Approach to the Fitzhugh-Nagumo PDE for Modeling Cardiac Action Potentials. , Jeremy Brooks

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• Undergraduate Program
• Statistics B.S.

Honors program

The goal of the Honors Program is to provide students with the opportunity to generate new and deeper learning either by performing independent research or completing graduate-level coursework. It represents a valuable opportunity for students who do and do not intend to apply for graduate school by letting them be mentored by faculty and allowing them to demonstrate commitment and discipline. T he honors program is a gateway to a more profound understanding of statistical concepts and preparing students for leadership roles in academia and in industry.  

Important dates  

T he first cycle of admissions will be in Spring 2024. Admissions open the first Friday of May and close the third Friday of May. No extensions will be given.

Click here to apply.

Applicants must be enrolled in STAT 342 or must have completed STAT 342 at the time of application.

Admission requirements  

This is a constrained capacity program and satisfying the minimum admission requirements does not guarantee acceptance. The Department of Statistics will only accept a small proportion of each cohort into the honors program. The minimum requirements are the following:  

Minimum cum ulative UW GPA of 3.3  

Minimum cum ulative GPA of 3.7 in the statistics, computer science and mathematics major requirements completed through the junior year.  

Students must be declared STAT majors   and must be enrolled in STAT 342 or must have completed STAT 342 at the point of application.

Requirements to earn Departmental Honors  

Students can choose between the following two options:  

Option 1: Coursework plus ePortfolio option (9 – 11 credits):  

One two - course graduate sequence to be chosen from (a) STAT 512 + STAT 513 or (b) STAT 516 + STAT 517 or (c) STAT 535 and either STAT 538 or STAT 548/CSE 547.  

Students will be r equired to m aintain a 2.7 GPA in each of the two courses corresponding to their chosen graduate sequence.  

At least 3 credits of STAT 499 (independent study) or STAT 495 (service learning)  

An ePortfolio of their course-related projects. The ePortfolio will be reviewed and approved by statistics faculty.  

For more information on the ePortfolio , please click here .

Option 2: Thesis option (9 credits):  

Nine credits of STAT 499. These must extend over at least 2 consecutive quarters (Summer, Autumn, Winter, Spring) . Most students will work on their thesis over the course of three quarters and take three credits of STAT 499 each quarter. The plan must be discussed with the ir faculty supervisor and is subject to their availability . This research will culminate in a senior paper and a presentation of that work in the Annual Undergraduate Research Symposium held each May, or another venue (such as a national or regional meeting) acceptable to the faculty.  

The student may receive up to five credit hours of W course credit for writing the thesis based upon the University of Washington guidelines for W credits and on the discretion of the faculty supervisor.  

For more information on the requirements of a thesis project , please click here .

How to apply  

As part of their application, students will be asked to submit :  

t heir transcript s ,   

a statement of purpose that discusses their career goals   

a list of relevant experiences (e.g., internships, projects)   

a detailed plan indicating which of the options they would like to pursue to obtain Departmental honors . In particular, according to the option chose n , the following will be needed:  

Coursework plus ePortfolio option : At the application stage, students must : (1) indicate which graduate classes they are planning to take and when ; (2) outline how they are planning to fulfill the research requirement. If the students plan to use DRP credits to complete the research requirement in this track, we expect them to have completed at least one credit before applying .  If, on the other hand, they are going to use a small project with a faculty member or STAT 495, the name and email of the sponsor/mentor a long with a brief description of the project must be submitted at this stage ; (3) I nclude a plan for the ePortfolio and include a a github page containing an initial draft of the ePortfolio with at least two completed projects.  

Thesis option : Students who choose the thesis option must already have an advisor when they apply to the Honors program. The student and their advisor must agree on a project and submit a title and a project proposal of 300-600 words as part of their application. Identifying an advisor and agreeing on a project with their advisor is the student’s responsibility.

Evaluation  

All applicants will be evaluated using the following criteria:  

Academic ability as measured by GPA, factoring in difficulty and breadth of courses completed, frequency of incomplete courses, and number of repeated courses

R elevant work and life experience.

M otivation.

Q uality and feasibility of the submitted plan .  

Honors Projects Archive (NA)

DEPARTMENT OF STATISTICS AND DATA SCIENCE

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• Major in Data Science

Honors in Data Science

Honors in Data Science gives outstanding senior majors an opportunity to design and carry out a research project of their choice, which forms the basis of the Honors Thesis. A research project in Data Science must constitute either an original contribution to theory or methodology, or an advanced data analysis project, and must consist substantially of independent research performed by the student.

Planning ahead is crucial for pursing honors. Prior to their junior year, students should prepare by reading Weinberg’s Honors in Your Major , which provides both a general overview of the honors process and general advice for students pursing honors.

To pursue honors in Data Science, a student should have an overall GPA of at least 3.5, a GPA of at least 3.5 in all courses required for the major and have made significant progress towards the major by the end of their junior year.

A departmental recommendation for honors requires that students take 2 quarters of independent study (STAT 399), through which they develop a research paper (senior thesis). These courses cannot be used to fulfill requirements for the major.

Prior to the fall of their senior year, students must

1) obtain agreement from a Department of Statistics and Data Science faculty member who will supervise the independent study and honors thesis

2) meet with the Director of Data Science for approval to pursue honors

The independent study courses are typically taken during the fall and winter quarters of the student’s senior year, with the Statistics and Data Science faculty member who has agreed to supervise your honors thesis.

For more information, contact the Director of Data Science.

Mathematics & Statistics Recent Theses in Statistics

Section navigation.

Students who write theses in statistics spend an entire academic year working on an in-depth study with the help and direction of a faculty member. In addition to writing a thesis, each student gives a seminar late in spring semester. The thesis seminar weeks are busy and exciting times around the department.

Copies of some past student theses are located in the Seeley Mudd library.

• Elizabeth Zhang worked with Prof. Amy Wagaman on "Flexible Bayesian regression models for complex interactions in exposure mixture studies"
• Justin Papagelis worked with Prof. Shu-Min Liao on "On the Analysis of Likert-Scale Data: Historical Debates and Newly Developed Approaches"
• Dasha Asienga worked with Prof. Kat Correia on "Algorithmic Bias, Statistical Notions of Fairness, and the Seldonian Framework"
• Kevin Jin worked with Prof. Shu-Min Liao on "Visualizing Simpson's Paradox in High-Dimensional Contingency Tables using Checkerboard Copula Regression"
• Clara Page worked with Prof.  Kat Correia on "Assessing the Robustness of Inverse Probability of Censoring Weighting"
• Michael Pitts worked with Prof. Nick Horton on "Impact of Missing Data on Clinical Trials: A Sensitivity Analysis Approach using Pattern-Mixture Models"
• Kenny Chen worked with Prof. Shu-Min Liao on "A model-free dependence measure for high-dimensional contingency tables and its potential as a goodness of fit measure"
• Andrej Pospisil worked with Prof. Amy Wagaman on "Evaluation of effectiveness of predictive mean matching in binary classification"
• Alex Ristic worked with Prof. Ryan McShane on "Engineering Social Network Features to Model a Stock Volatility Time Series"
• Cat Sarosi worked with Prof. Amy Wagaman on "Item Response Theory Models for the Quantitative Reasoning for College Science Assessment"
• Jessica Yu worked with Prof. Brittney Bailey on "Robustness of Degrees of Freedom Approximation in Linear Mixed Models with Nonnormal Distributions"
• Andrea Boskovic  worked with Prof. Amy Wagaman on "Imbalanced Data Classification with Neural Networks and Classifiers"
• Jasper Flint worked with Prof. Amy Wagaman on "Comparison of Image Feature Extraction and Classification Methods"
• Konstantin Larin worked with Prof. Amy Wagaman on "A Comparison of Effectiveness of Different Network Sampling Algorithms in Estimating Network Statistics"
• Tony Ni worked with Prof. Brittney Bailey on "Evaluation of Parameter Estimation Methods to Handle Left-Censored Missingness"
• Breanna Richards worked with Prof. Katharine Correia on "Classification of Lymphatic Cancer Types Using Random Forests and LASSO Regression"
• Margaret Chien worked with Prof. Katharine Correia on "Modeling Fatalities in Armed Conflict with Mixed Effects Models"
• Dahyun Jessica Jeong worked with Prof. Nicholas Horton on "Scaling Statistical Modeling and Analysis for Larger Datasets Using Sparklyr"
• Zachary Brown worked with Prof. Nicholas Horton on "An EM Approach to Solving Coarsened-Data Problems Caused by Lower Limits of Detection"
• Fengling Hu worked with Prof. Amy Wagaman on "Bayesian Inference and One-Shot Learning"
• Robert Zielinski worked with Prof. Amy Wagaman on "A Comparison of Bayesian Inference Algorithms for Hierarchical Mixture Models"
• Jonathan Che worked with Prof. Albert Kim on “Resampling Methods for Model Assessment and Selection with Extensions to Spatial Data”
• Brendan Seto worked with Prof. Nicholas Horton on “Causal Inference”
• Sarah Teichman worked with Prof. Amy Wagaman on “The Impact of Different Edge Weightings on Community Detection in Social Networks”
• Caleb Ki worked with Prof. Nicholas Horton on "Missing Data in Randomized Clinical Trials"
• Levi Lee worked with Prof. Amy Wagaman on "A Simulation Study Using Random Graph Models to Fit Social Networks" (technically, a thesis in mathematics)