Philosophy

This course is centered on the idea that you will better understand and retain important statistical concepts if you build your own knowledge and practice using it, rather than by memorizing and regurgitating a set of facts. In order to actively construct knowledge in statistics, you must:

• Engage in the material and think carefully about it; there are rarely rote, black and white solutions in statistics.

• Become skillful at using R, a software package for exploring, modeling, and making decisions with data. You’ll have opportunities to use R inside and outside of class.

• Expect small amounts of daily homework, decent-sized weekly homework sets, and longer projects which allow you to pull your knowledge together.

This is a 6 week course, there will be a lot of work over a short period of time. You will have to be self-motivated to stay on task, and you will need to ask me questions when you have them.

Class Preparation and Participation

My goal for this course is have it be both synchronous and asynchronous. We will meet for every morning session (10:00 - 11:30 AM) unless I inform otherwise. Afternoon sessions will sometimes be optional. I will send a weekly email with my plan for each class.

My expectations of you before each class:

1. Read the appropriate sections in the textbook (reading guides are available on Moodle, but I will not collect/grade them).

2. Complete any online tutorials assigned for that day.

3. Read any supplemental material posted.

4. Review the worksheet if it is your turn to lead discussion in your group.

I expect your participation in our classes. They will often include small and large group work. Occasionally you will be asked to lead a small group on a worksheet or task. This is not meant to intimidate you, put you on the spot, or force you to be the only contributor that day. It is meant to develop your leadership skills, promote interaction with classmates, and give me a chance to hear everyone’s voice. This will be a safe environment where mistakes and uncertainty are welcome!

Zoom behavior

Zoom is terrible… I’d much rather see you in person and watch your eyes roll at my terrible jokes. But, we’re doing the right thing this summer by not meeting in person. The hardest thing for me as a teacher is the mute button. Class is so much better when I can see and hear you. So I’m not requiring you to have your video on during class, but I highly encourage it (feel free to use a background if you’d like). And please unmute yourself when you have something to say.

Computing

This course will use R extensively. Course datasets and code are easily available on the R server which can be accessed by the link on Moodle. Supplemental materials will be provided on Moodle for learning to use R. Further instructions will be provided during class.

Learning R is necessary to do statistics. There is a learning curve and you will make mistakes, it just happens (and still happens to me). It is important that you take a breath, step back, and remember to seek help to resolve your issue. Come to my office hours, ask classmates for help, and ask me questions in class. Past students have found learning R to be ultimately very useful and even fun. R is freely downloadable for both Mac and PC at https://cran.r-project.org/, and it’s available on a St. Olaf server!

Often during our classes, I will ask you to share your screen and code. That means you may have to split your screen to watch and type at the same time. Keep up with the class or your group and be prepared to talk through your code or output.

Homework

There will be weekly homework assignments. Homework assignments are designed to give you practice applying new statistical concepts to new data contexts. Homework will be drawn from the exercises at the end of each chapter as well as additional questions. The homework assignments are long, so you should work through them as we go along. Many of the problems require computation. Code snippets in these cases will usually be provided.

• You are encouraged to discuss problems together, but each person must hand in their own work.

• You must show your work for full credit.

• Homework is ALWAYS due by 11:59 PM each Friday. Anything after this will be assessed a late penalty. This includes late assignments due to technical issues. Plan ahead.

• I expect that you will start soon after receiving the assignment. The assignments are definitely not designed to be one-night jobs.

• Homework is completed using RMarkdown and you are required to upload both the RMarkdown (.Rmd) file and knitted pdf file to Moodle.

Quizzes

We will have several short Moodle quizzes each week. You will have 1 hour to complete the quiz. You must complete the quiz independently. You may use the textbook, notes, slides, worksheets, tutorials, or any other materials when taking the quizzes. All weekly quizzes must be completed by 11:59 PM each Friday.

Exams

The midterm and final exams will focus on your abilities to use the statistical software, to interpret results, to express an understanding of statistical concepts, and to engage in statistical thinking on open-ended questions. They will not focus on plug-and-chug mathematics or hairy mathematical proofs. Make-up exams will be granted only under very special circumstances, and only if arranged in advance.

Data Analysis Reports

Statistics is best learned by getting hands-on with real data. And while learning the correct analysis is a part of this course, communicating and reading statistical analysis is another large part. You will complete 2 Data Analysis Reports for this class. These are short (2-3 page) summaries of the entire statistical process for a research question of your choosing. More information will be provided around the 2nd week of class.

Special Project and Participation

We have a special client during this semester. The Twin Cities Berry Company has asked for some help analyzing data for their farm. Throughout the semester we will use this data in examples and meet with the growers to eventually create a final statistical report (as an entire class) to present the results of some experiments. Your ideas and participation for this aspect of the class will be recorded in addition to your regular participation in class.

Note about Disabilities

I am committed to supporting the learning of all students in my class. If you have already registered with Disability and Access (DAC) and have your letter of accommodations, please meet with me as soon as possible to discuss, plan, and implement your accommodations in the course. If you have or think you have a disability (learning, sensory, physical, chronic health, mental health or attention), please contact Disability and Access staff at 507-786-3288 or by visiting wp.stolaf.edu/academic-support/dac.

Statement of Inclusivity

In keeping with St. Olaf College’s mission statement, this class strives to be an inclusive learning community, respecting those of differing backgrounds and beliefs. As a community, we aim to be respectful to all citizens in this class, regardless of race, ethnicity, religion, gender or sexual Orientation.

I am committed to making course content accessible to all students. If English is not your first language and this causes you concern about the course, please speak with me.

Note about Academic Integrity

Plagiarism, the unacknowledged appropriation of another person’s words or ideas, is a serious academic offense. It is imperative that you hand in work that is your own, and that cites or gives credit to others whenever you draw from their work. Please see St. Olaf’s statements on academic integrity and plagiarism at: https://wp.stolaf.edu/thebook/academic/integrity/. See also the description of St. Olaf’s honor system at: https://wp.stolaf.edu/honorcouncil/

St. Olaf’s Academic Integrity Policy, including the Honor System, is an integral part of your academic experience. I consider any violation of this code to be extremely serious and will handle each case appropriately. Here are some guidelines for this class. They do not cover all eventualities so if you have any doubts about a course of action you can ask me.

• Homework assignments may be done in collaboration with other students (this is highly encouraged). However, the final product must written by you, in your own words, unless group assignments have been specifically allowed.

• In no event can you copy answers from another student, a website, solutions manuals, or elsewhere.

• When you sign your pledge on an exam that you have “neither given nor received assistance, and seen no dishonest work” I treat your signature as your solemn pledge that all your actions have been honorable. For example, if we have a take-home exam, you are assuring me that you shared no information with others, that you did not solicit or receive help from anyone besides me, etc.

• Don’t treat the honor code lightly; if you’re in doubt about a possible violation, ask me.