About

This is a document that contains syllabi for the courses taught by Hannah Lunkenheimer. Please reference this doc any time you have questions about your course. If you can’t find an answer, please try troubleshooting, checking your e-mail, Canvas, Slack, or e-mail me your question. Also, if you find any mistakes, please let me know.

Cheers!

Makale, Tana Toraja, Indonesia 2023

Hello students!

I am a cross-cultural researcher studying how people explain and cope with significant misfortune, such as death and illness. (e.g. death, illness, natural disasters). My research focuses on using cognitive, social, and evolutionary theories to explain how beliefs and rituals are cross-culturally recurrent and how those beliefs and rituals impact grief, coping, and psychological well-being over the lifespan.

Tallin, Estonia 2022

A little about me

I’m from San Antonio, Texas and got my undergraduate degree from UT Austin in 2017. In 2018 I began work as a social worker in Tarrant County and began graduate school in 2020. In 2022, I completed my master’s thesis which examined risk perceptions of COVID-19 in 11 countries.

When I’m not at school, I’m probably hanging with my dogs, Avery and Cholula, geocaching, traveling, doing yoga, or making funky earrings.

I’m excited to get to know a little about each and every one of you!

Statistics

Basic course info

Hi. My name is Hannah Lunkenheimer (she/her) and I’ll be your course instructor for stats this semester. Woohoo! If you have any questions or need to contact me immediately, please email me and I will do my best to respond within 48 hours. Please check your Canvas inbox for important announcements and helpful materials throughout the semester.

  • Drop-in hours for this course are Fridays at 9AM via my Zoom link here: https://utexas.zoom.us/my/hglunk

  • Our class meets in John Brooks Williams South (JBWS) Room 363 on T/TH 12:30pm-1:45pm (CRN 40236).

  • The prerequisite for this course is MATH 0309.

  • The textbook that you’re required to read for this class is freely available to you online here. If you’d like another perspective on class material or need more help, please see this supplementary textbook.

  • There is a required program that you’ll need on your computer called R, which you can download here. If you have questions about downloading R and RStudio, please review this text. You can use the cloud version of RStudio, called RCloud if that works best for your learning and/or machine. I do not recommend this option, but if this is the only option that will work for you, I recommend purchasing the student package at $5 a month because you’re only allowed a certain number of hours in the free version.

Course Objectives

  1. This course aims to provide students with a solid grasp of fundamental statistical concepts and their application in real-world data analysis using R Studio.

  2. Through hands-on exercises, students will gain practical skills in data manipulation, exploratory analysis, and visualization using R, empowering them to conduct statistical analyses effectively.

  3. Students will develop the ability to think critically, design experiments, and interpret statistical results in the context of research questions, while effectively communicating findings to diverse audiences.

Course Description

This course is all about quantitative reasoning and fulfills the “Quantitative Reasoning” Learning Outcome in the General Education Curriculum! You’ll learn the logic behind statistics and get practice with many of the statistical techniques that social scientists use in their research. This includes choosing the appropriate statistic, calculating statistics from data, visualizing the data, and interpreting its meaning. You’ll be better able to read and understand statistical information that you read in research articles and in everyday life. We will do all calculations, analyses, and data visualization in RStudio. If you are willing to put in the effort, it will pay off. You can achieve this, and I’m here to support you!

Do I really need to come to class?

Yes. Please bring a charged laptop and any other materials you may find helpful to access online materials and participate in class labs and activities. Remember, you must have access to RStudio to be in this course.

Attendance

To succeed in this course, you’ll need to attend every class and actively engage with course material. Learning statistics is a skill that requires repeated exposure and practice (just like a sport or language); class sessions provide structured practice and a way to ask questions as they come up. This content builds upon itself, so you will need to quickly catch up on any missed material (which becomes more challenging the more that is missed!). I take attendance every class period which makes up part of your grade.

  • Success tip: to get the most out of class sessions, arrive on-time and prepared (having read the next ~10 pages of the chapter and completed any homework), stay engaged with the course material and take notes, AND stay for the full session duration. Class sessions will meet in person in our designated classroom. Class slides will be posted to Canvas once the topic has been introduced.

Participation

Participation is an important component for succeeding in this class. Engagement in class sessions includes taking notes, discussing the material, participating in and working through the practice problems and in-class experiments, and asking questions as you have them. Students should be fully prepared, having completed readings prior to class and turning in assignments on time. This course will include in-class activities to collect data so we can practice the computational content together. Therefore, student participation is strongly encouraged. Please also feel free to ask questions and discuss the topics at the moment. If you have to miss class, these are ways in which you can make up participation points.

  • Success tip: taking notes during class is crucial because we work through practice calculations during class. I suggest focusing on writing down the functions we perform in class and what their purpose and uses are. I highly recommend taking notes in RMarkdown files.

  • Class participation is expected to be professional, responsible, and respectful (see student policies page). Participation can also include attending my office hours or emailing relevant questions or thoughts to me. At my discretion, there may be opportunities for extra credit throughout the semester. Any extra credit opportunity will be offered to all students – under no circumstances will any student be allowed to complete an individual extra credit project. Extra credit opportunities will be announced in class. For those of you who are reading the syllabus as assigned: here’s your first extra credit opportunity! Email Hannah a photo of your dream vacation spot by September 1 and you’ll start off the semester with 3 free points added to Quiz 1 (please do not tell your classmates).

Stats and R help

Success tip: Talk to your professor! I care deeply about your well-being and your success in this class. Please talk to me about anything related to this class, personal issues that may affect your success as a student, or any career-related questions you may have. I genuinely enjoy talking with my students, so please reach out at any time.

Assessment and grades

Below please read all of the descriptions for each type of assessment this semester. All grades are final at the end of the semester, and I will not accept requests to bump up your grade. If you’re struggling with course material, please meet with me as soon as possible to discuss best practices for your learning and get you on track to learning statistics.

Assessment

  • Labs: Lab assignments are a low-stakes way to practice your stats skills with a group of your peers or by yourself. Labs give you the opportunity to learn from each other, teach each other, and collaborate in statistics. I will post solutions to lab assignments on Canvas 24 hours after you turn them in, and you are responsible for comparing your work with the solutions to learn from your mistakes. Because the solutions will be posted 24 hours after the due date, all labs turned in after the solutions are posted will not be graded. Labs will be graded for effort. You’ll get a 10 for turning in mostly-accurate work that shows you’re learning the material, a 7 for assignments that show a good-faith effort but reveal some misunderstandings of the material, a 3 for assignments that show minimal effort and a 0 for late/missing assignments. I will not give scores other than 0, 3, 7, or 10, and all members in the group will receive the same grade.

  • Homework: You can expect to have a homework assignment every week. Homework should be done individually, completed using R if applicable, and submitted electronically through Canvas. There are 11 total homework assignments, and 10 will count toward your final grade. This means you’re lowest homework assignment will be dropped (or if you decide not to do a homework assignment, forget to turn one in, or are having a bad week and need a break, don’t worry)!

  • Participation and attendance Participation and attendance count for 30 points. This will be evaluated primarily through attending and participating in class sessions. For each class, I will randomly take attendance for you to receive a point (in person). Students should arrive to class on time and be prepared to stay for 1 hour and 15 minutes. If you are absent, you do not need to notify me that you will miss class. These attendance grades are intended to help keep students accountable and to provide structure for completing the course material at the appropriate (and manageable) pace.

  • Quizzes Five quizzes will be given throughout the semester, each contributing equally to your final grade. Quiz material will be drawn from our scripts, textbook, and from the lectures. The quizzes are NOT cumulative; however, the course material does build upon previous content. All quizzes will be administered online through Canvas and completed during scheduled class days in RStudio. Quizzes will be timed, and you have 60 minutes to complete them (timing adjusted as needed for students with 504 accommodations). Quizzes are open-source, so you may reference your scripts, our course slides, and your readings during the quiz. Do not reference your classmates (or their screens!). Even though the quizzes are open-source, they are still timed and rigorous, so to succeed, you will still need to study as you would for closed-book quizzes or exams. You will need your computer with RStudio downloaded for each quiz. You will submit your scripts in addition to submitting your quiz responses on Canvas. In order for me to give an quiz grade, you must turn in your R scripts. Otherwise your quiz will not be graded.

Grading breakdown

  • Labs: 10 lab assignments will be graded. Each lab is worth 10 points, for a total of 100 points.

  • Homework: Your top 10 homework assignments will be graded. Each homework assignment is worth 12 points, for a total of 120 points.

  • Quizzes: 5 quizzes will be graded. You have the option to take a quiz during finals week to replace your lowest quiz grade. Each quiz is worth 50 points, for a total of 250 points.

  • Attendance: Each day you show up to class, you get a point for attendance, for a total of 30 points.

Grade calculator

Simply add up all of the points you’ve earned at the end of the semester to determine your final grade. If you don’t know whether or not you’d like to take the optional final, please come talk to me to help figure out what would be best for your learning.

Grade distribution

A+ = 485-500 points
A = 465-484 points
A- = 450-464 points
B+ = 435-449 points
B = 415-434 points
B- = 400-414 points
C+ = 385-399 points
C = 365-384 points
C- = 350-364 points
D+ = 335-349 points
D = 315-334 points
D- = 300-314 points
F = Under 300 points

  • Success tip: Check the grade book regularly so that you know where you stand and can plan accordingly.

Late policy

  • If you miss a deadline, you may turn the lab or homework assignment in within 24 hours of the deadline and receive up to 70% of credit (instead of 100%).
  • Make-up quizzes will be provided only in special circumstances if you communicate with me beforehand. Examples of unacceptable reasons for missing an exam: oversleeping, early tickets for travel, being hungover, etc.
  • You have the opportunity to make up a missed quiz during the finals period.

Health and well-being resources

Significant stress, mood changes, excessive worry, substance/alcohol misuse or interference in eating or sleep can have an impact on your well-being, studies, and development. St. Edward’s offers a variety of services to help you with these concerns. If you or someone you know experiences any of the mental health concerns above, I strongly encourage you to contact or visit any of the University’s resources provided below. Getting help can be difficult and is a courageous thing to do – for yourself and for those who care about you.

  • St. Edwards Health and Counseling Center: All of us benefit from support during times of struggle. Know you are not alone. If you or anyone you know is experiencing symptoms of stress, anxiety, depression, academic concerns, loneliness, difficulty sleeping, or any other concern impacting your wellbeing – I strongly encourage you to connect with HCC. HCC provides a wide variety of mental health services to all students, including counseling services with immediate support and student support groups.

  • Hilltopper Helpline: If you have concerns about the safety or behavior of fellow students, TAs or professors, contact the Hilltopper Helpline at (833) 434-1217. Licensed counselors will be available 24/7/365 to provide immediate support for student concerns and refer any student who needs regular counseling to the HCC.

  • Hilltopper Emergency Assistance: If you face challenges to securing your food or housing and you believe this may affect your performance in the course, please fill out the Hilltopper Emergency Assistance Request or the Student of Concern Form and the Dean of Students Office will be in contact to assist you.

Student Policies

  1. Student Rights
  • You have the right to a learning environment that supports wellness.
  • You have a right to be assessed and graded fairly.
  • You have a right to respect, privacy, and confidentiality.
  • You have a right to meaningful and equal participation.
  • You have a right to learn in an environment that is welcoming to you.
  1. Student Responsibilities
  • You are responsible for managing your time, completing assignments and readings, and communicating with the me if things start to feel out of control or overwhelming. Know that I am here for you!
  • You are responsible for acting in a way that is worthy of respect and is always respectful to others. Your experience with this course is directly related to the quality of your engagement.
  • You are responsible for creating an inclusive environment.
  1. Student Learning Success
  • If there are aspects of this course that prevent or exclude you from learning, please let me know as soon as possible. Together, we’ll develop strategies to meet your needs and the requirements of this course. I am happy to connect you with someone who can assist you and your needs.
  • This class respects and welcomes students of all backgrounds, identities, and abilities. I am committed to creating a fun and effective learning environment for all students, but can only do so if you discuss your needs with me as early as possible. I promise to maintain the confidentiality of these discussions.
  1. When Life Happens
  • You are an adult and are expected to attend every class meeting on time. If you cannot attend class due to illness or other reasons, please communicate with me as early as possible to address the missed content. This helps me make sure you have a plan to stay on track with the material. Healthy Hilltop has resources for those testing quarantining. I’m willing to work with students regarding attendance, but since statistical skills are learned through repeated practice, attendance is still a high priority. If you are absent, it is highly recommended that you obtain class notes from a classmate.

Course and Campus Policies

Academic Integrity
Don’t be dishonest, plagiarize, or cheat. Seriously. It’s not worth it and can lead you to be suspended or expelled from the University for Scholastic Dishonesty. Examples of plagiarism include copying a writer’s work (including scripts) exactly and representing it as your own, submitting something without credit to the original author, and submitting materials (scripts) written by another student. This list is not exhaustive. You are expected to uphold and reflect the Academic Integrity Code of the University.

Generative Artificial Intelligence (AI) Tools
In this course, you may use generative AI programs, e.g. ChatGPT, to help troubleshoot your errors in R for labs and homework assignments. Other uses of ChatGPT is not permitted in this course. The use of ChatGPT will not be permitted for quizzes. If ChatGPT is used during a quiz, the student will receive an automatic 0 for the quiz and a file will be written to the Dean of Students. Please remember that the material generated by ChatGPT isn’t always accurate, may be missing some things, or cause problems. The use of these tools may also hinder your independent learning of statistics and programming languages.

For all labs and assignments, if you decide to use ChatGPT or another AI program, please add a #note and clarify where in the assignment you used AI, why you needed to use it, and which platform you used. If you find yourself needing to cite ChatGPT, here’s a link that shows you how to cite ChatGPT.

Accessibility, Inclusivity, and Compliance Statement
The university is committed to creating an accessible and inclusive learning environment consistent with university policy and federal and state law. Please let me know if you experience any barriers to learning so I can work with you to ensure you have an equal opportunity to participate fully in this course. While I have done my best to make this course accessible, I am aware that I can always improve as a teacher. If you are a student with a disability or think you may have a disability and need accommodations, please contact Student Disability Services online or at (512-448-8561). They will coordinate reasonable accommodations for students with documented disabilities (medical, learning or psychological). If you are already registered with SDS, please deliver your Accommodation Letter to me as early as possible in the semester so we can discuss your approved accommodations and needs in this course.

Required Devices
Access to a laptop, computer, or tablet is critical for your learning in this course. Your assigned textbook and resources are available to you online, and we work in RStudio. If you have any concerns about your technology needs this semester, please contact the Dean of Students for help right away.

Sharing of Course Materials is Not Permitted
The materials used in this class including, but not limited to, lectures, assessments (quizzes, scripts, papers, labs, homework assignments), or in-class materials, may not be shared online or with anyone outside of the class unless you have my explicit, written permission. Any suspected behavior of this sort will be reported to Student Conduct and Academic Integrity in the Dean of Students Office. Please visit St. Edward’s University’s Copyright and File Sharing Policy.

Land Acknowledgment
I would like to acknowledge that we are meeting on the Indigenous lands of Turtle Island, the ancestral name for what now is called North America. Moreover, I would like to acknowledge the Alabama-Coushatta, Caddo, Carrizo/Comecrudo, Coahuiltecan, Comanche, Kickapoo, Lipan Apache, Tonkawa and Ysleta Del Sur Pueblo, and all the American Indian and Indigenous Peoples and communities who have been or have become a part of these lands and territories in Texas.

Religious Holy Days
If you need to miss a class or required activity, such as a benchmark, for the observance of a religious holy day please let me know as far in advance of the absence as possible so that I can make arrangements for your completion of the assignment.

Campus Safety
Here are a few recommendations for campus emergencies from the Office of Campus Safety: - Call the University Police Department at (512) 448-8444, - Complete a SEU Crime Incident Report Form, or Submit an Anonymous Tip. - Evacuate buildings when a fire alarm is activated. If this happens, the rest of the class will be canceled. - Familiarize yourself with all exit doors in our classroom and building. - If you require assistance in evacuation, please let me know during the first week of class. - In the event of an evacuation, follow my instruction. We won’t re-enter the building unless we receive instruction from the Austin Fire Department, The St. Edward’s University Police Department, or Fire Prevention Services office.

SEU Campus Firearm Policy
The bringing of weapons or firearms of any kind on university premises, including university parking lots, or while conducting university business, and the possession of firearms, is prohibited while on campus and at all campus related activities.

Title IX - I am a mandatory reporter!
As a faculty member, I am a mandatory reporter and required by our university, federal and state laws to report incidents of sexual misconduct and thus cannot guarantee confidentiality. I must provide our Title IX coordinator with relevant details including the names of those involved in the incident. Please know that you can seek confidential resources at the Health & Counseling Center in Johnson Hall, 512-448-8538 or with one our 24/7 off-campus partners, Hilltopper Helpline at (833) 434-1217 or SAFE Alliance at (512) 267-7233. To make a formal report, you can contact the Dean of Students Office in Main Building, G 16, (512) 448-8408, or file the report online. You can also make a police report to the St. Edward’s University Police by calling (512) 448-8444.

Semester topics

  • Introduction to R
  • R syntax
  • R data carpentry
  • R data visualization
  • Descriptive statistics
  • Understanding distributions
  • Confidence intervals
  • Hypothesis testing
  • One sample inferential statistics
  • Two sample inferential statistics
  • Correlation
  • Linear regression