This page serves as the Course Frequenty Asked Questions (FAQ) page and syllabus for Neil's section (Sec. 1) of STAT 184: Introduction to R course in Fall 2026. Feel free to scroll through the page and/or use the navigation links I've provided. If you find something that doesn't work, please let me know so I can fix it.
Highlighted/marked text such as TBD indicates a place where the class (you) will have a say in the creation of a course policy. After the first week, we'll have these sections filled out.
Last updated: 8/19/2026
From the PSU
Bulletin:
R is a powerful, open-source programming language used widely for applications in statistics and data science. It is easily extendible, and thousands of user-created packages are publicly available to extend its capabilities. This course will introduce students to data computing fundamentals and reproducible workflow using the R programming language and related tools. Students will be expected to access, join, wrangle, clean, and visualize real data from various sources (e.g., CSV, HTML scraping, web URL, R packages). The course will emphasize use of "tidyverse" R packages (e.g., dplyr, ggplot2), although students will also be exposed to Base R and other packages. In addition, students will be exposed to one or more integrated development environments (e.g., RStudio) and will be expected to write well-documented code using a reproducible workflow (e.g., RMarkdown, Git/GitHub). The course focuses on descriptive and graphical summary techniques rather than inferential statistical techniques.
In essence, STAT 184 is an opportunity for students majoring in Statistics and Data Science (along with others interested in working with data) to gain familiarity with the statistical programming language R. Further, this class provides you an opportunity to develop ways of thinking that will assist you in using R (or another programming language) to carry out statistical analysis and communicate your findings.
This course section is offered by the Department of Statistics within the Eberly College of Science.
I have one section of the course this semester that meets three times a week, in person.
When the university closes for holidays, weather, or other unexpected events, we will not meet. Be sure to check your PSU emails/Canvas messages for additional information.
Hi! I'm Neil J. Hatfield and I'm teaching Section 01 of STAT 184 for the Spring 2026 semester. You may call me Neil, Dr. Hatfield, Professor Hatfield, Dr. Neil, etc. I use he/him/his pronouns and am readily reachable via Penn State email. You can also connect with me through Microsoft Teams and by phone--(814) 863-7664.
I also encourage students to come visit with me in person when possible. My office is Thomas 425A. I have an open door policy meaning that if my door is open and I'm there, you can talk with me.
I have yet to set my Student Hours for Fall 2026; check Canvas for a poll. My student hours will be in Thomas 424/425 or Thomas 425A.
There are several different types of materials that you will need. Please review the list carefully.
If you are using a Penn State owned computer (physical or virtual), a version of both R and RStudio Desktop are already installed.
Beyond the above elements, I've done what I can to minimize additional costs to you. You should not need to purchase any other items or materials for the course. If you are asked to, please reach out to me before you do so to get clarification.
The overarching goals for this course are to provide students with opportunities and experiences with statistical software so that they may develop their programming skills, capabilities to use software in data analysis, and productive ways of thinking for data analysis and problem solving.
To achieve these goals, we've established the following learning objectives--themes/categories for your development and growth.
Each of the learning objectives are broken down into smaller learning outcomes that we have tied directly to all assessment items in the course (homework, readings, quizzes, projects, etc.). You can view the current learning outcomes (and objectives) by examining this shared document: Stat 184 Learning Outcomes PDF. You can also find these in the Standards Based Grading Progress Checker app that will be linked in Canvas.
All members of our class community have responsibilities.
All members of our class community should follow these responsibilities.
TBD: Students will have an opportunity to put together a list of their responsibilities. We will update this after the class has an opportunity to propose and vote on suggestions.
Here's a plast class's list of student responsibilities
TBD: Students will have an opportunity to put together a list of instructor responsibilities. We will update this after the class has an opportunity to propose and vote on suggestions.
Here's what a past class came up with:
Within the Eberly College of Science we have a set of 12 principles meant to capture and convey the values we hope that all members of our community will choose to embody and make the college a rewarding community for all. Please take a moment to look through The Eberly College of Science Code of Mutual Respect and Cooperation.
Attendance and participation are vitally important for our class community. Attending each class session is an important part of becoming a professional member of our community. However, attendance alone will not guarantee that each person will get the most they can out of the course. This is where your participation comes into play. I will do what I can to provide a variety of ways for people to participate.
Attending class is an expectation that the University has of all students for all courses, regardless of modality (in-person, hybrid, or online). Therefore, you will need to attend each class session baring illness, participation in a University sanctioned event, religious observance/practice, or other legitimate circumstances (e.g., governmental elections). If you need to miss class, please let me know by sending me an email or message via Canvas.
We know from past education research that absences can negatively affect students' success. As we want you to succeed, we will track your attendance each class session. Your attendance will contribute to your Professionalism 5 score for the semester. Treat attending this class like you would a statistics/data science job.
Physically attending class is not sufficient to learn the material. You need to actively take part in class; that is, participate
TBD: Students will have an opportunity to put together a list of what it means to participate. We will update this after the class has an opportunity to propose and vote on suggestions.Here's what a past class felt were good indicators of participating.
I believe that assessments are a key way for us to grow and learn together. I strive to create assessments which provide you with opportunities to practice what you've been learning as well as push you to continue to grow. I encourage you to view any assignments as an opportunity to engage in self-reflection.
Throughout the semester, we'll have a variety of assignments for you to complete either individually or as part of a group.
Assignments that are part of MyOpenMath (MOM) will allow each student to use a Late Pass to given themselves additional time to complete the assignment.
The class will vote on 1) how much time each Late Pass is worth, and 2) how many Late Passes students can use on an individual assignment.
Each late pass will extend the due date for the assignment by TBD and students may use up to TBD late passes on each eligible assignment.
There are several important things to keep in mind related to Late Passes:
Separate from and in addition to Late Passes, you may also contact me about getting a limited extension. This is particularly useful if you are out of late passes, need more time than the late pass period hours, or are dealing with an assignment not eligible for late passes. The process to request an extension is the following:
I will review each request on a case-by-case basis and get back to you with the extended due date that I grant you, which might not be the date you propose. Until you hear back from me, please do not assume that you have the extension. You may only ask for one extension per assignment.
Life happens and things can suddenly go sideways. In such an event, please reach out to me as soon as you can so that we can work together to get you back on track.
If you find yourself asking for multiple extensions, please reach out to me to discuss what's going on. I'll do the same if I feel that you've made a large number of extension requests.
Due to the existence of Late Passes and extensions, I will not make full answer keys available to students until after all assignments are submitted. Many detailed solutions (including grading rubrics) will be available in the homework system (MOM) once you've submitted the assignment and the Late Pass Period has passed. Keep in mind that if you opt to view answers after the due date, the system will bar you from using a Late Pass.
TBD: The class will have an opportunity to help shape testing policies.
We use a Standards-Based Grading System in this course. This means that we live and breath the learning outcomes when thinking about assessing each one of you. Throughout each assignment (homework, quizzes, tests, coding interview, final exam, and course project), every question connects to at least one of the learning outcomes. Each time you answer a question, you are adding to the body of evidence about your understanding for each outcome. We use that entire body of evidence to evaluate where you end up for each learning outcome.
In an ideal world, we would report multiple grades to the Registrar; one for each of the Learning Outcome. However, we can only report a single letter grade. Thus, at the end of the semester, we are tasked with determining the most appropriate letter grade based upon the semester's worth of data on the Learning Outcomes and Learning Objectives for each of you.
To determine grades, we work in a data informed and principled/structured way. This allows us to account for the unique elements of each semester (i.e., the broader context) and the students in the course. Thus, each semester is a little bit different.
We begin by pulling the entire body of evidence from the Standards-Based grading system. Using data wrangling techniques like what we learn in class, we'll generate counts for each student that answer the following questions.
Once we have these counts, we hide student names to explore the data, looking to see if there are any natural groupings/clusters (to ensure equal treatment of students) as well as any natural breaks/gaps between groupings.
Notice that we focus on Learning Outcomes and Objectives; not necessarily your assignment scores or points. The homework/assessment scores are a function of learning outcomes but can create confusion. For example, if you demonstrate Adept Proficiency on one Learning Objective but Not Yet, Not Shown on another--and the assignment is just those two questions--the assignment score looks like a 50%; you don't get the credit for the outcome you have a great understanding of.
Given the above data-informed process, the following thresholds are starting points for the process. These thresholds will change as a result of the process. Students must satisify all elements of a row to be eligible for the given letter/quality grade.
| Letter Grade | Objectives at Skillful+ | Outcomes at Highly Developed+ | Outcomes at Skillful+ | Code Interview |
|---|---|---|---|---|
| A | All 6 Objectives | At least 75% of outcomes | At least 75% of outcomes | At least Skillful Proficiency |
| A- | 5 of 6 Objectives | At least 65% of outcomes | At least 65% of outcomes | At least Skillful Proficiency |
| B+ | 5 of 6 Objectives | At least 56% of outcomes | At least 56% of outcomes | At least Skillful Proficiency |
| B | 4 of 6 Objectives | At least 42% of outcomes | At least 75% of outcomes | At least Skillful Proficiency |
| B- | 3 of 6 Objectives | At least 30% of outcomes | At least 66% of outcomes | At least Skillful Proficiency |
| C+ | 2 of 6 Objectives | At least 30% of outcomes | At least 50% of outcomes | At least Skillful Proficiency |
| C | As many as possible | As many as possible | At least 50% of outcomes | At least Not Yet-Progressing |
| D | As many as possible | As many as possible | At least 30% of outcomes | At least Not Yet-Progressing |
| F | As many as possible | As many as possible | As many as possible | Not Yet-Beginning or Not Yet-Not Shown |
To help students track their progess over the course of the semester, I've created an app for students to use. This will be linked in Canvas and will require you to log in via your Penn State email account. Once in, you'll be able to see how you are doing on all of the course learning objectives and outcomes. I will update this app whenever we have new data; roughly, after we finish grading each assignment. There will be additional information in Canvas for how to get the most out of the app.
You may view the tentative course schedule online through a shared Excel workbook: Tentative Stat 184 Fall 2026 Schedule.
Keep in mind that this calendar may change at any time to best meet the needs of the class.
I believe that in order for all students find their version of success, we must form a supportive and inclusive class community. This starts with every member being respectful and welcoming from Day One. All of the following resources are part of the Penn State's extensive network to help everyone find success.
One of the greatest things about being human is that we are each our own unique person. As such, there is a whole realm of neurodiveristy in any classroom. What some people need to have comfort and success in our class will be different from those of others. We welcome all individuals from across the neurodiviersity spectrum. I ask that we provide grace and space for all people to be themselves.
If you are feel like you're having problems in the course, please come see me and let's see what we can do to help you. This might include reaching out the Student Disability Resources office (or other offices on campus).
If you currently have academic accommodations, please make sure to talk with me as soon as possible so that we can get everything in place.
If you've had academic accommodations in the past but haven't registered with the Student Disability Resources office, I encourage you to do so. Having the accommodations does not mean that you have to use them but they do provide you with an additional support system. In order to receive consideration for reasonable accommodations, you must contact the appropriate disability services office at the campus where you are officially enrolled, participate in an intake interview, and provide documentation (see documentation guidelines). To start the process, please reach out through the Student Disability Resources (SDR) website, which provides contact informaiton for every Penn State campus.
Many students at Penn State face personal challenges or have psychological needs that may interfere with their academic progress, social development, or emotional well-being. The university offers a variety of confidential services to help you through difficult times, including individual and group counseling, crisis intervention, consultations, online chats, and mental health screenings. These services are provided by staff who welcome all students and embrace a philosophy respectful of clients' cultural and religious backgrounds, and sensitive to differences in race, ability, gender identity, and sexual orientation.
Penn State is committed to supporting students' well-being and success. Resources are available for students who may be experiencing challenges meeting basic needs such as food, housing, or healthcare. Students at any Penn State campus may request support by completing the Basic Needs Request Form. After submitting the form, a case manager from the student's campus will reach out to offer support, guidance, and connections to helpful campus and community resources.
Our institution's official policy states that "The Pennsylvania State University recognizes the need or preference for members of the University community to refer to themselves by a first name other than their legal first name as well as self-assert a gender other than their legal gender or their gender at the time of birth (AD 84)." One way we can support self-identification is by honoring the name and pronouns that each of us go by.
Many people (e.g., international students, performers/writers, trans & non-binary people, and others) might go by a name in daily life that is different from their legal name. In this classroom, we seek to refer to people by the names that they go by.
Pronouns can be a way to affirm someone's gender identity, but they can also be unrelated to a person's identity. They are simply a public way in which people are referred to in place of their name (e.g., "he" or "she" or "they" or "ze" or something else). In this classroom, you are invited (if you want to) to share what pronouns you go by, and we seek to refer to people using the pronouns that they share. The pronouns someone indicates are not necessarily indicative of their gender identity.
Visit Sexual and Gender Diverse Community to learn more.
Penn State University has adopted a Protocol for Responding to Bias Motivated Incidents that is grounded in the policy that the "University is committed to creating an educational environment which is free from intolerance directed toward individuals or groups and strives to create and maintain an environment that fosters respect for others." That policy is embedded within an institution traditionally committed to academic freedom.
Bias motivated incidents include conduct that is defined in University Policy AD 91: Discrimination and Harassment, and Related Inappropriate Conduct. Students, faculty, or staff who experience or witness a possible bias motivated incident are urged to report the incident immediately by doing one of the following:
Veterans and currently serving military personnel and/or spouses with unique circumstances (e.g., upcoming deployments, drill/duty requirements, disabilities, VA appointments, etc.) are welcome and encouraged to communicate these, in advance if possible, to the instructor in the case that special arrangements need to be made. Check out Penn State's Veterans Affairs and Services website for more information.
The Pennsylvania State University campuses are located on the original homelands of the Erie, Haudenosaunee (Seneca, Cayuga, Onondaga, Oneida, Mohawk, and Tuscarora), Lenape (Delaware Nation, Delaware Tribe, Stockbridge-Munsee), Monongahela, Shawnee (Absentee, Eastern, and Oklahoma), Susquehannock, and Wahzhazhe (Osage) Nations. As a land grant institution, we acknowledge and honor the traditional caretakers of these lands and strive to understand and model their responsible stewardship. We also acknowledge the longer history of these lands and our place in that history.
A central aspect of education is that you build your knowledge and develop ways of thinking that will support you in your life and career. As one of your educators, part of my role is to assess your learning so that I can help you build the most productive ways of thinking. In order for me to best help you, I need the most accurate and reliable data about your thinking and learning. Academic integrity is a key to this process.
A person demonstrates academic integrity when they engage in any scholarly/educational activity in an open, honest, and responsible manner. This is part of our Shared Responsibilities.
Part of learning involves running into situations where you don't instantly have a solution. Rather, you have to think about the problem, try a few things, and then pieces fall into place. You do not have to engage in such struggles alone. Getting help is a great way to help you engage in productive struggle that leads to better learning. However, not all sources of help will actually support your learning and growth. Here are my suggestions for places to seek help.
You'll notice that on the last two I've placed the phrase "Use caution." While you might learn how to handle the specific problem you ask about, there's no guarantee that what you get from these will help you later on in the course. Additionally, there may be differences in approaches that might cause you more problems. For example, online resources (e.g., Stack Overflow, genAI, etc.) may show solutions that are 1) out of date/not recommended anymore, 2) rely on packages that are no longer available, 3) use techniques that are well-beyond what we're trying to do, 4) and/or cause new problems when you attempt to incorporate them into your work. If you find a solution online or got from someone not associated with our course, feel free to come talk to me about it. We can go over it together and I can show you how we can evaluate such advice.
When you are getting help be sure that you are not crossing the line and having someone else do your learning for you.
There are many different ways in which a person's actions may directly or indirectly lead to violating Academic Integrity. Keep in mind whether a person acts intentionally or accidentally, that action could still result in violating Academic Integrity. The best advice I can give is to always talk with your instructors before you submit the assignment. Here are a few of the broad categories of actions that lead to violation of academic integrity.
The best advice I can provide is to talk with your instructor before you submit any assignment. Once you submit, you've solidified your action and there isn't anything your instructor can except to report the violation.
A person violates academic integrity when they act in a way that either (dis-)advantages themselves or (dis-)advantages someone else that is not explicitly allowed ahead of time. While people have a variety of reasons for choosing to act in such ways (e.g., stress, lack of time, perssure to perform, etc.), we need to keep in mind that choosing to violate academic integrity impacts everyone. The person violating academic integrity weakens their own academic growth--they do not receive the feedback that is actually necessary for their growth. The class community suffers as such cases delay giving feedback, and erode the sense of trust in the community.
It is expected that any work submitted is your own. Class members may work on homework assignments and lab assignments in groups, but each student must write up answers in their own words and submit lab quizzes and homework assignments separately.
The major distinction between collusion, working together, and group work comes down to what has been explicitly allowed by the instructor. Collusion is never allowed.
I encourage students to work together on assignments. However, when students work together, each person is individually responsible for their own work. Having one person answer the questions, write the code, etc. and then pass the results to the other person is not working together. Rather, each person should be engaged in the problems, sharing ideas, thoughts, and approaches. The individual differences in how we each write and talk should be present in the answers and work each person submits. Working together can enrich the learning of all those who are actively participating.
Group work occurs when the instructor gives an activity or assignment that is meant to be completed by a group of students together with a single submission for the group. This is not a violation of academic integrity due to the specifications the instructor has set up for the assignment. When working in a group, keep in mind that all members are responsible for whatever the group submits. This means that if there is an academic integrity issue with the submission, all members are eligible for sanctions.
Chatbots such as OpenAI's ChatGPT, Google's Gemini, Perplexity AI, Anthropic's Claude, or Microsoft's Copilot appear confident in the answers they provide. However, their answers are not always logical nor stand up to scrutiny. If a person relies upon chatbots to do their work, they will miss out on critical opportunities to develop the ways of thinking necessary to detect problems with AI generated answers.
An important part aspect of this course is to help you develop foundational ways of thinking about teaching so that you can create your own lessons. Using tools such as generative AI to design, create, prepare lessons plans for you not only cheats yourself of an invaluable learning opportunity, but it also cheats your students. Therefore, unless explicit permission is given for a particular assignment, the entire class community (the instructor, the students, TAs, etc.) should actively refrain from using generative AI tools. When such use is explicitly authorized, that work should be properly documented. Direct usage of output from chatbots should be treated much like a direct quotation; derivations of such output should be treated as paraphrased text.
For Fall 2026, we will be exploring some aspects of generative artifical intelligence systems (e.g., Large Language Models, chatbots, and agents) and wrestling with ethical considerations. Keep in mind that every class will have their own policies and by being an enrolled member of that class you have a shared responsibility to make sure you understand and follow the policy. If you are ever not sure about something, asking your instructor is the best advice to follow.
With the advance of genAI-empowered devices such as Meta Glasses, Limitless Pendant, etc., many people are not necessarily aware of the ethical and legal risks they run by having and using such devices without permission and disclosure. To keep our class community a safe space for sharing thoughts, students may not use any device that records any part of class without explicit prior authorization from the course instructor. This also extends to students using phones, tablets, laptops, or other devices to record.
To minimize the risk of being mistakenly accused of cheating, wearable technology should be completely removed before undertaking any summative assessment such as a test. Failure to do may result in a failing grade on the assessment.
A critical skill to practice is recognizing what you can and cannot upload into different AI tools. Beyond school, many companies and organizations have polices governing what employees can upload into a chatbot or large-language model. Employees who violate this can be immediately fired. To help, ask yourself this question: "Did I make this [what you plan to upload] or did someone else?" If you did not make whatever you're about to upload, you need to take extra care and ask follow up questions including whether the creator gave permission and what limits, if any, they might have placed on their permission.
Recognize that the course materials I share with you are the result of my hardwork, time, energy, and care for student learning. To this end, no student may upload any materials that I post related to this course to any chatbot or LLM, including Penn State's AI Studio without express, written, prior permission. This includes any handouts, websites, eBooks, slide decks, Keynotes/PowerPoints, example code files, rubrics, homework prompts, assessment items (homework problems, quiz/test questions), project specifications, etc.
I will do my best to clearly signal when and how genAI tools may or may not be used. Be sure to look out for the following signals on assignments.
Any time you see these signals, please make sure you take a few moments to read any additional information provided; there will always be additional information. For both Limited and Allowed usages, keep in mind that you must disclose and properly cite/document all of your usage of genAI tools.
Any use case of genAI not explictily mention should be handled under the philosophy of "Ask First". Using genAI tools during the course in ways that are inconsistent with this policy shall be violations of Academic Integrity. Students should be prepared to explain any of their submitted work at any time.
Any instances of academic dishonesty will be pursued under the University and Eberly College of Science regulations concerning academic integrity. In the event that a violation of these Academic Integrity policies occurs within the context of a group assignment, all members of the group will face consequences.
TBD: Students will have the opportunity to come up with and vote upon suggested consequences for violating Academic Integrity for the course.
| Severity | Description | First Offense | Subsequent Offenses |
|---|---|---|---|
| Minor | Violation consists of a single instance in an assignment and does not directly impact another student | TBD | Treat as a Moderate violation |
| Moderate | Violation consists of multiple instances in an assignment and does not directly impact another student | TBD | TBD |
| Major | Violation consists of extensive instances in a single assignment, spans multiple assignments, and/or directly impacts another student | TBD | TBD |
We will use the above table for recommending a proposed sancation. Keep in mind the the Eberly Committee on Academic Integrity as well as the Office of Student Conduct may choose alter the consequences, including increasing them.
Issues involving violations copyright law (e.g., posting assignments to websites such as Chegg, CourseHero, etc.) will not only constitute a Major violation of the Academic Integrity policies of this course, but will also entail a separate violation of the Penn State Student Code of Conduct.
Should the university close due to weather or campus emergencies, please be sure to follow any directions included in the University's official announcement. You can stay up to date on such announcements by signing up for PSUAlert (https://psualert.psu.edu/psualert) and/or following Penn State on social media.
In the event of university closure, we will not meet in person. Please check your PSU email and Canvas for further course announcements.
If you are prevented from completing this course within the prescribed amount of time for reasons that are beyond your control, it is possible to have the grade deferred with the concurrence of the instructor, following Penn State Deferred Grade Policy 48-40. To seek a deferred grade, you must submit a written request (by e-mail or U.S. post) to the instructor describing the reason(s) for the request. Non-emergency permission for filing a deferred grade must be requested before the beginning of the final examination period. It is up to the instructor to determine whether or not you will be permitted to receive a deferred grade. If permission is granted, you will work with the instructor to establish a communication plan and a clear schedule for completion within policy. If, for any reason, the coursework for the deferred grade is not complete by the assigned time, a grade of "F" will be automatically entered on your transcript.
In the event that I'm not able to attend class, I will announce for what the plan will be. This may include having a guest speaker/instructor (a substitute), for work time (independent or in groups), or cancel the session. Such information will be announced as needed via PSU email/Canvas.
If I have missed class and no one in class has heard from me, please reach out to the Statistics Department Offices. Key people to talk to include Catelyn Way and Jessica Bickle in Thomas 323 as well as Terra Deyo and Lydia Myers in Thomas 326.
The syllabus for this course (and all other course syllabi) does not constitute a legal contract. Further, I intend for this syllabus to change to reflect the decisions we make as a community on several areas listed above as well as adapting to our needs throughout the semester. Changes to the syllabus will be announced in class and updated here.