Overview

Professor: Joe Roith

Office: My cozy house in St. Paul

Email: roith1@stolaf.edu

Note: I will respond to emails as quickly as possible during the week before 5 PM. I may respond to emails in the evenings or on weekends, but do not rely on it.

Virtual office hours: Refer to our shared Stat 110 Google Calendar

You may also schedule an appointment with me (check my calendar for availability) or drop by and talk if my door is open.

Class meetings: We will not have a scheduled meeting time. I will post reading assignments, chapter slides, short videos, and interactive tutorials/labs that you are expected to complete/watch. You should be devoting time each week for Stat 110.

Textbook: Seeing Through Statistics (4th edition), Jessica M. Utts

Companion website: www.cengage.com/UttsSTS4e

Link to the “real” syllabus: Shadow Syllabus for all your classes

Course computing: We will NOT use SPSS for the remainder of the semester. I will incorporate other free statistical analysis softwares into labs and assignments (R, CODAP, etc.)

Course description

This course is an introduction to the principles of statistical thinking in the spirit of the liberal arts. Students will learn the language, practical applications, and concepts involved in statistical reasoning. Statistics is the science of learning from data. By now you are aware that vast amounts of data are collected every moment in a variety of settings like political polls, clinical trials, stock markets, and social media user metrics to name just a few. Statistical methods are necessary to extract information, create predictions, and make evidence based decisions using data.

This is not a course in mathematics. Although we use mathematics, statistics is quite different. Be prepared to think and read critically in this class. In addition, there is a language and vocabulary of statistics that is important to use properly.

Course objectives

  1. To explore how statistics assists in understanding and reasoning with the vast amounts of data produced by society.

  2. To become a critical consumer of statistical data, scientific reports, and their conclusions.

  3. To make decisions under uncertainty.

  4. To design a data collection protocol, collect data, analyze the data to answer research questions, and summarize the conclusions using visualizations, summary statistics, and clear exposition.

  5. To learn how to perform the above using the software program SPSS.

Features of this course

Philosophy

This course and this textbook are 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.

  • Attend class Complete online lectures, participate in class, and complete pre-class preparations.

  • Attend labs Complete online labs/tutorials, develop skills using SPSS, develop skills using technology and transfer those skills to real data beyond homework and test situations.

  • Expect weekly homework sets, occasional table Moodle quizzes, and longer projects data analysis reports (see below) which allow you to pull your knowledge together.

Grades

Your course grade will be determined as follows:

Category Weight
Homework Assignments 15%
Lab Assignments and Participation 15%
Quizzes 10%
Midterm Exam 1 20%
Group Project Data Analysis Reports 20%
Final Exam 20%

College wide grading benchmarks can be found at: http://catalog.stolaf.edu/academic-regulations-procedures/grades/

All homework assignments, lab responses, and quizzes will be due each week by 11:59 PM Sunday night. This is Central MN time. If you are in a different time zone, I will allow a couple hours cushion. The best advice I can give is to just not wait until Sundat night to submit everything.

Homework

Weekly homework assignments will be assigned and submitted through Moodle as a PDF document. 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.

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

  • If you work with other students, you must note this fact (along with the students’ names) on your assignment.

  • You must show your work for full credit.

  • Homework is due by 11:59 PM each Sunday night. Late homework assignments will be accepted within reason (24 hrs) for the first offense, not accepted afterwards. (Contact me if the Sunday deadline is simply impossible for you). This includes late assignments due to technical issues. Plan ahead. The lowest 2 homework scores will be dropped.

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

  • Short reading reflections (less than one page) will occasionally be due, especially at the beginning of the semester. These will be graded on your ability to thoughtfully and concisely respond to a specific reading. Please keep to the length restrictions.

Lab Assignments

I will post interactive tutorials each week to walk you through examples using real world data and introduce you to some new technologies for analysis. At the end of each tutorial you will complete a Lab Response and submit it as a pdf to Moodle by 11:59 PM each Sunday night. I will drop the lowest 2 lab scores.

Moodle Quizzes

Short quizzes will be posted weekly on Moodle. You will have 30 mins and 2 attempts to complete each quiz. You are allowed to use slides, notes, textbook, and any other materials for these quizzes. I will drop the lowest 2 quiz scores.

Exams

There will be no second midterm exam. I do still plan to make an online final exam through Moodle (unless I can find a better option in the meantime).

Project Data Analysis Reports

There will no longer be a group project for this course. Instead, I will ask you to complete 2-3 Data Analysis Reports. In short, I will provide several data set options to choose from. Each data set will include variable lists, numeric summaries, plots and graphs. Your job will be to create your own research questions and use the summaries and plots to write a 1-2 page data analysis report about your research question.

You will be allowed to work in small groups (2-4) if you choose. All reports will be peer-evaluated by another student/group.

  • First DAR due Sunday, April 19

  • Second DAR due week of May 10

  • No Presentations

Computation

I understand that everyone’s computer and internet situation is drastically different now. Access to the internet, sharing devices with family, video conferencing quality, and your schedule may affect your ability to complete assignments. Please know that I get this and am willing to work with you individually on completing the content. You just need to let me know!

Class Preparation and Participation

We are online each in our own homes, but I still expect you to participate in this class! There are online forums on Moodle to ask and answer questions, I will have virtual office hours you can attend, and I will even try to set up some times for us to get together online and socialize if needed. Check your email and Moodle often to see more ways to participate in class.

Classroom behavior

Be sure to help out around the house, clean the dishes, do some laundry, make your bed. I have some great recipes for dinners or muffins if you want to make a little treat for your family. Wash your hands and limit your exposure to people outside your own home (I don’t care if they’re friends or family in another home that don’t feel sick, don’t do it unless it’s necessary!!)

Available help

You can all be successful in this class! If you are struggling or if you’re feeling good about things but have some questions, there are several resources:

Come see me at my drop-in office hours, or make an appointment, or see if my door’s open

  • Connect with your classmates. Call/text/Google meet them to ask questions, work on homework or labs together. There is a participant list on Moodle if you’re not sure who your classmates are.

  • I believe there will still be SI sessions. I don’t know what those will look like yet so stay tuned.

Notes and Statements

Note about Disabilities

I have the ability to automatically allow more time on quizzes and tests for those who have accommodations. I will also work with DAC to ensure everything is properly accessible. If you have accommodations, please let me know what I can do to help make this class better online.

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.

New Schedule

Tentative Outline of topics: The following table provides a rough sketch of the topics we’ll cover during specific weeks, along with the associated reading assignments in our textbook:

Week Topics Book Chapter
Day 1 Introduction to Stats 1
Week 2 Consuming and collecting Data 2 & 3
Week 3 Sampling and Studies 4, 5 & 6
Week 4 Summarizing and visualizing data, Normal distribution 7, 8 & 9
Week 5 More visualizing and review 9
Exam #1 (Tuesday, March 3)
Week 6 Relationships and Correlation 10 & 11
Week 7 Categorical Relationships, \(2 \times 2\) tables 12
SPRING BREAK (March 21 - 29)
Week 8 (3/30 - 4/2) Extended Spring Break
Week 9 (4/6 - 4/10) Testing Two Categorical Variables 13
Week 10 (4/13 - 4/17) Probability (briefly) and Sample Distributions Ch. 14 & 19 *DAR #1 due
Exam #2 (Mon - Tues April 20 - 21)
Week 11 (4/20 - 4/24) Confidence intervals 20 & 21
Week 12 (4/27 - 5/1) Hypothesis testing 22 & 23
Week 13 (5/4 - 5/8) Hypothesis testing (cont.) *DAR #2 due
Week 14 (5/11 - 5/13) Review
Final Exam: Monday, May 18, 2:00-4:00 PM