STAT 155: Introduction to Statistical Modeling
Macalester College, Spring 2023
Section 01: MWF 9:40 am – 10:40 am, OLRI 254
Section 02: MWF 10:50 am – 11:50 am, OLRI 254
This course provides an introduction to statistical modeling. In other words, it’s a crash course on how to turn data into knowledge. Being able to summarize, interpret, and communicate about data are crucial for any career, and these are precisely the skills that we’ll build in this class. Throughout the semester, we’ll study the fundamental methods that statisticians use to extract knowledge from data, emphasizing statistical literacy, real data applications, and modern computing over memorizing facts and formulas. If you go on to study more statistics at Macalester, you'll dive into theory in our upper-level courses: in this course, we'll focus on application, interpretation, and intuition.
By actively participating in this course, you will develop and/or strengthen your abilities to:
Learning Goals
Course Philosophy
Learn by doing. The best way to learn statistics is to do statistics. This course is designed to give you opportunities to practice applying statistical concepts to real data. The activities will require access to a computer. If you do not have one, or if you have unreliable internet access, fill out the form here; ITS and Financial Aid will work with you to get you the technology you need. Reach out to me if you have any concerns.
Learn by making mistakes. Learning by doing will entail making mistakes. This is ok! Learning from those mistakes will form some of your most valuable learning experiences. I have designed the grading system for this course with this growth mindset in mind—more info on page 3.
Learn by collaborating. Working effectively in a group setting is an essential skill in statistical modeling—and life—and improves your learning (evidence), but building this skill requires practice. We will spend most of our class time working in randomly-assigned small groups. If working with someone else enrolled in our class would be a barrier to your learning, please let me know (no reason necessary!).
Learn by reflecting. Self-reflection and self-assessment are crucial to becoming a lifelong learner. To help you practice these important skills and guide your learning in this class, you will engage in multiple structured opportunities for reflection throughout the semester.
Course Overview
We are very lucky to have a team of ten (!) preceptors that will be helping out with STAT 155 this semester. You are welcome and encouraged to attend office hours for any of the STAT 155 preceptors, not just the ones who are grading for our sections. See the Stat 155 Calendar for office hours times and locations.
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Dr. Kelsey E. Grinde
Pronouns: she/her/hers
Pronunciation: listen here
Office: OLRI 226
Email: kgrinde@macalester.edu
STAT 155 | Spring 2023
Your Instructor
A Letter from Your Professor
Hello, and welcome to Stat 155!
I'm excited to spend the next 15 weeks sharing statistics with all of you. This is a field that I ended up in somewhat by accident—I actually hated the first stats course that I took in high school. But, in my sophomore year of college (down the road at St. Olaf College), I decided to give statistics one more chance and signed up to take Statistical Modeling. I'm so glad that I did! That class changed my mind about how interesting and impactful statistics can be, and I've been studying statistics ever since.
If you’re starting this class as hesitantly as I was so many years ago, I hope that this course will change your mind about statistics just like it did mine. And for those of you who are already excited about statistics—welcome! I'm looking forward to a great semester with all of you.
Kelsey
How to contact me:
I do my best to respond to all messages quickly, but I also try to maintain a healthy work/life balance. With this in mind, please allow extra time for a response on evenings and weekends.
Call me Kelsey
Students sometimes wonder what to call their professors. I prefer to be called by my first name, Kelsey (KELL-see), but I am also okay with Professor Grinde (GRIN-dee). Please note that I prefer not to be called Professor (without my last name attached) or Ms./Mrs. Grinde.
Please help me make sure that I call you by your preferred name—with correct pronunciation—and pronouns, too!
Preceptors
Aidan
(he/him)
Statistics + Economics
STAT 155 | Spring 2023
Before Class. Before class each day, you will watch short lecture videos, read from our free online textbook, and then complete a short Moodle checkpoint to assess your initial understanding of the terms and concepts from the videos and reading. Checkpoints can be taken more than once and only your highest score will be recorded.
Learning Assessments
Many of the assignments in this class (e.g., checkpoints, in-class activities, practice problems) are designed to be formative, providing you with opportunities to practice material and get feedback to further guide your learning, with grades based primarily on effort/completion rather than correctness. To assess your progress toward course learning goals, you will also complete the following learning assessments:
Quizzes. We will have three quizzes spaced throughout the semester: February 20, March 24, and April 17. Quizzes will be completed during class time and will be closed notes except for a small (3 x 5 inch) index card. Each quiz will involve an individual portion (30 min), followed by a group portion (30 min). The group portion will provide an opportunity to revise your answers to a subset of the quiz questions, in collaboration with a small group.
Data Analysis Project. During the second half of the semester, you will work in small groups to explore and analyze a dataset of your choosing. There will be multiple project checkpoints, allowing ample opportunities for feedback and revision. Projects will culminate in a Final Report due May 5 and a Final Presentation during your assigned final exam period (instead of taking a final exam). Additional details will be provided later in the semester.
Learning Reflections. Throughout the semester, I would like you to track feedback you receive on assignments and reflect on your progress and learning. You will write and submit three major learning reflections: the initial reflection (due February 10), the midterm reflection (March 10), and the final reflection (May 6). Submitting a midterm and final learning reflection is required to receive a passing grade in this course.
Course Structure
During Class. During class time, you will work in small groups on activities that build upon the pre-class work. Please bring your laptop to class every day. These in-class activities will serve as your personal reference for R code and concept illustrations. We will reflect on effective strategies for group work throughout the term.
After Class. After class, you will complete any remaining parts of the in-class activity, review material, and prepare for the next class. Each week, you will submit a set of practice problems including questions from the in-class activities, with the goals of synthesizing material and providing an opportunity for feedback to further guide your learning.
Grading System
This course uses a non-traditional grading system, designed with the goals of aligning your grades with our course learning objectives, allowing space to make and learn from mistakes, and encouraging self-reflection.
To earn an A in this course, you must consistently meet all of these criteria:
To earn a B: frequently meet almost all of these criteria (missing 1–2) and show meaningful progress on the others.
To earn a C: frequently meet some of these criteria, or meet many of the criteria but less often, and show meaningful progress toward a few others. This must also include submitting the required midterm and final learning reflections.
(+ and - grades will be awarded in intermediate cases)
It make take time to get used to this system. I'll provide feedback and resources to help you track your progress throughout the semester. If you're ever concerned about your learning (or grade), set up an appointment with me to discuss!
STAT 155 | Spring 2023
Ask questions. When you have questions, please stop me during class, ask your neighbor, post on Slack, and come to office hours. Saying "I don't understand" is an important part of learning and it helps others around you. See the #help-r channel on Slack for some tips specific to asking questions about R.
Come to office hours. Office hours are a great time to talk about course material and assignments, study strategies, selecting courses, declaring a major, grad school and/or career planning, or life in general. You don't need to have a specific question in order to attend office hours: it can also be a great space to review concepts, talk through examples, or just chat! The Macalester Academic Excellence (MAX) Center also provides tutoring for STAT 155: check out their website for more information and their tutoring schedule.
Make time. Performing a thoughtful statistical analysis requires time: to plan, to implement, to interpret, and to revise. Start your assignments early. It is very hard to be creative or to debug R code when you are in a rush. In addition to the 3 hours we spend together during class, expect to spend about 7 hours per week on this class. If you're spending much more (or less!) time than that, please let me know.
Attend class. Active participation in this class will be key to your learning. We'll use class time to ask and answer questions, review material, and practice concepts in a collaborative environment. To ensure the best learning experience for you and your classmates, come prepared, engage in class, and make full use of the entire class period. There may be times you are unable to attend class: in those cases, it's your responsibility to check Moodle to see what you missed, review the material, complete the in-class activity on your own, get notes from your classmates, and (after doing all of the above) come to office hours with specific questions.
Prioritize your well-being. Investing time into taking care of yourself will help you engage more fully in your academic experience. Remember that beyond being a student, you are a human being carrying your own experiences, thoughts, emotions, and identities with you. If you are having difficulties maintaining your well-being, please contact me and/or check out these resources. As part of prioritizing your well-being (and others around you), it is important that you stay home if you are are feeling sick. See the recommendations above (Attend class) and below (Communicate) if you miss class or need extra time on an assignment.
Communicate. I will do my best to clearly communicate changes to expectations, deadlines, office hours, or class meetings due to instructor illness or unexpected life issues. Please make sure to check Moodle and Slack regularly so you don't miss any important announcements. I know that you may also have issues come up: if so, please get in touch with me to discuss solutions. In particular, I ask that you please check in with me, as soon as possible, if:
Advice for Success in STAT 155
Data Principles | Jan. 20 – Jan. 25 |
Data Visualization | Jan. 27 – Feb. 3 |
Linear Regression | Feb. 6 – Mar. 3 |
Logistic Regression | Mar. 6 – Mar. 24 |
Quantifying Uncertainty | Mar. 27 – Apr. 3 |
Hypothesis Testing | Apr. 5 – Apr. 17 |
Model Evaluation | Apr. 19 – Apr. 24 |
Project Work | Apr. 26 – May 1 |
Tentative Course Schedule
Late Work & Extensions
STAT 155 | Spring 2023
I expect all of you to be familiar with the college standards on academic integrity. Please take time to review this policy if you have not done so recently. I encourage you to work with your classmates to discuss material and ideas for your assignments, but in order for you to receive feedback on YOUR learning, all submitted work (including code!) must be written in your own words. I take academic integrity very seriously and will schedule a meeting with you if I have any concerns that this policy has been violated.
Academic Integrity
I expect you to adhere to the MSCS Community Guidelines in all of your interactions with classmates, preceptors, and instructors. This will include:
If you witness or experience any violations of these guidelines, I encourage you to come chat with me and/or follow the suggestions in the Community Guidelines document to report the issue.
I set deadlines so that preceptors and I can get feedback to you quickly, and because the material in this course builds from week to week. That said, I will accept late work, without any penalty to your grade, provided that it is submitted before grading begins (typically within 1–2 days of the deadline). If you get in touch with me to request an extension before the deadline, preceptors and I can plan our grading accordingly and make sure that you get feedback on your work. I cannot guarantee that I will be able to accommodate extension requests that are made after a deadline has passed—or shortly (e.g., less than 24 hours) before something is due—so please plan accordingly. In particular, all requests related to major learning assessments (quizzes, projects, and learning reflections) need to be communicated at least one week in advance for full consideration.
I am committed to creating an accessible and inclusive classroom for all students. If you need any accommodations, please contact Disability Services (visit their website, call 651-696-6748, or email disabilityservices@macalester.edu) to make an appointment to discuss your needs. Once you’ve met with Disability Services, please then set a time to meet with me to discuss your accommodation plan for this course. It is important to arrange this meeting as early in the semester as possible (ideally within the first week), in order to ensure that your accommodations can be implemented early on. It is your responsibility to make sure you are registered with Disability Services. If you wait until later in the course, I will not be able to accommodate you retroactively.
Accommodations
Title IX. If you or anyone you know has experienced harassment or discrimination on the basis of sex or gender, know that you are not alone. Macalester provides staff and resources to help you and support you. More information is available on the Title IX website. Please be aware that all Macalester faculty and preceptors are mandatory reporters, which means that if we become aware of incidents or allegations of sexual misconduct, we are required to share the matter with the Title IX Coordinator. Although we have to make that notification, you control how your case is handled, including whether or not you wish to pursue a formal complaint. If you would like to speak to someone confidentially, contact the Hamre Center (651-696-6275), chaplains (651-696-6298), or other local and national resources listed here.
Religious Observance. Students may wish to take part in religious observances that occur during this semester. I've done my best to schedule deadlines around major holidays, but if you have a religious observance/practice that conflicts with class or an assignment deadline, please let me know and we can discuss appropriate accommodations.
Masking Policy. We all have a role to play in keeping each other safe. I expect you to follow the practices outlined in the Shared Community Commitment. This includes wearing a mask in class and office hours if you have symptoms or a known exposure. I'll communicate updates to our masking policy as campus and public health guidelines change.
Important Course Policies