Your primary contact in STAT 216 is your instructor. If you have concerns that cannot be answered by your instructor, you may reach out to the Student Success Coordinator.
Eliot Liucci
Email: eliot.liucci@student.montana.edu
Office: Wilson 1-135
Roland Owusu
Email: rolandowusu@montana.edu
Office: Wilson 1-135
Stat 216 is designed to engage you in the statistical investigation process from developing a research question and data collection methods to analyzing and communicating results. This course introduces basic descriptive and inferential statistics using both traditional (normal and \(t\)-distribution) and simulation approaches including confidence intervals and hypothesis testing on means (one-sample, two-sample, paired), proportions (one-sample, two-sample), regression and correlation. You will be exposed to numerous examples of real-world applications of statistics that are designed to help you develop a conceptual understanding of statistics. After taking this course, you should be able to:
This course fulfills the Quantitative Reasoning (Q) CORE 2.0 requirement because learning probability and statistics allows us to disentangle what’s really happening in nature from “noise” inherent in data collection. It allows us to evaluate claims from advertisements and results of polls and builds critical thinking skills which form the basis of statistical inference. Students completing a Core 2.0 Quantitative Reasoning (Q) course should demonstrate an ability to:
Interpret and draw inferences from mathematical models such as formulas, graphs, diagrams or tables. Represent mathematical information numerically, symbolically and visually. Employ quantitative methods in symbolic systems such as, arithmetic, algebra, or geometry to solve problems.
Entrance to STAT 216 requires at least one of the following be met:
You should have familiarity with computers and technology (e.g., Internet browsing, word processing, opening/saving files, converting files to PDF format, sending and receiving e-mail, etc.).
Two “textbooks” are required for this course:
CoursePack Title: Stat_216_Coursepack ISBN: 9781711474120 CPID: 1511657
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We will be using the statistical software R through the IDE RStudio for data visualization and statistical analyses.
You will access this software through the MSU RStudio server: rstudio.math.montana.edu. Your username is your 7-character NetID (in the form x##x###, where x is a letter and # is a number), and your password is the password associated with your NetID. Your email address will not work to log in to the RStudio server.
See the Statistical Computing section in the Welcome chapter of our textbook for alternative options for accessing RStudio.
D2L: Find your instructor and co-instructor/TA contact info, announcements, exploration information, instructor notes, exam review material, assignment and data files, discussion forums, gradebook.
Gradescope: Submit and review quizzes and assignments, review exam grades.For more details, see our links in D2L under Content –> Primary Resources –> Gradescope Help
Math and Stat Center: Free drop-in tutoring for 100- and 200-level math and stat courses.
Stat 216 will meet 3 times per week (Monday, Tuesdays, and Thursdays 10:00am - 12:20pm. Each week, students will:
Your grade in STAT 216 will contain the following components.
You will be expected to complete the assigned textbook reading and D2L videos using the reading guides provided on D2L prior to attending class each week. Concept check quiz questions will be completed in Gradescope. (Note that you can rewind/review the video as much as you like, and may submit your Video Quiz in Gradescope as many times as you like up through the due date. You can also check your answers in Gradescope after submitting (prior to the due date) by clicking on each question’s hyperlink. If a explanation appears, that means you answered the question correctly.)
Every class day, you will meet with your classmates and instructor to work through that day’s coursepack group activities or labs. Attendance and completion of the activity counts towards this portion of your grade.
Activities must be completed in the Stat 216 Coursepack.
Activities will be checked for completion at the beginning of the following class period.
Most class days, you will meet with your classmates and instructor to work through that day’s coursepack Rstudio group lab. The lab will reinforce the ideas learned in the activities completed in that module but with the use of Rstudio for exploring and analyzing data.
Each group will turn in selected questions from the lab to Gradescope. Labs are due Tuesdays and Thursdays at 8 pm Mountain Time each week.
Each student will also turn in each lab for completion at the beginning of the following class period.
You will complete bi-weekly assignments in Gradescope. These should be completed individually (meaning all answers should be written in your own words), but you may use your classmates, tutors, or your instructor/co-instructor/TA for assistance.
There will be two midterm exams (worth 15% of the course grade each). Midterm exams will be taken in class during your normal in-class time. Each exam has an group (first hour of class) and individual (second hour of class) component. Further details, resources, and instructions for each exam will be posted the week prior to the exam in D2L.
The final exam is cumulative, but will be more heavily weighted towards Unit 3 material and is worth 20% of the course grade. The final exam will be taken in class during your normal in-class time. The final exam has a group (first hour of class) and individual (second hour of class) component. Further details, resources, and instructions for each exam will be posted the week prior to the exam in D2L.
Individual final exam will be Thursday, June 20 from 12:00 - 1:50pm.
Final course grades will be determined according to the following scale.
Letter Grade | Weighted Score |
---|---|
A | 93-100% |
A- | 90-92.99% |
B+ | 87-89.99% |
B | 83-86.99% |
B- | 80-82.99% |
C+ | 77-79.99% |
C | 70-76.99% |
D | 60-69.99% |
F | <59.99% |
The grade cutoffs may be shifted downward at the end of the semester based on student performance (never upward).
Videos: Videos are available in D2L at least one week prior to the due date, so extensions on these quizzes are not given unless extenuating circumstances that prevent the student from viewing the video for that entire period.
Activities and Labs: Attendance in this course is critical for success and is therefore required. The out-of-class, in-class activity and lab grades are a proxy for attendance and engagement. Students are expected to be in class during in-class activities and labs to provide support to each other and their teammates while working through the material. If you need to miss a class period due to illness, quarantine, or other extenuating circumstances, please email your section instructor a picture or scan of your completed activity due that day by 8pm Mountain Time, and we can give you credit for your completed activity. If the activity is not received by 8pm Mountain Time on the day it is due, you will not receive credit unless there are extenuating circumstances that prevented you from completing the activity for the entire week prior to the due date. If you need to miss a lab due to illness, quarantine, or other extenuating circumstances, please email your section instructor and group-mates letting them know prior to the lab meeting. You may participate in the lab via video conferencing if desired or you may complete the lab on your own. If the latter, your section instructor will determine an appropriate extension on the lab based on your individual circumstances.
Exams:
Respect for Diversity: It is our intent that students from all diverse backgrounds and perspectives be well-served by this course, that students’ learning needs be addressed both in and out of class, and that the diversity that students bring to this class be viewed as a resource, strength and benefit. It is our intent to present materials and activities that are respectful of diversity: gender identity, sexual orientation, disability, age, socioeconomic status, ethnicity, race, religion, culture, perspective, and other background characteristics. Your suggestions about how to improve the value of diversity in this course are encouraged and appreciated. Please let us know ways to improve the effectiveness of the course for you personally or for other students or student groups.
In addition, in scheduling exams, we have attempted to avoid conflicts with major religious holidays. If, however, we have inadvertently scheduled an exam or major deadline that creates a conflict with your religious observances, please let us know as soon as possible so that we can make other arrangements.
Support for Inclusivity: We support an inclusive learning environment where diversity and individual differences are understood, respected, appreciated, and recognized as a source of strength. We expect that students, faculty, administrators and staff at MSU will respect differences and demonstrate diligence in understanding how other peoples’ perspectives, behaviors, and worldviews may be different from their own.
Students in an academic setting are responsible for approaching all assignments with rigor, integrity, and in compliance with the University Code of Student Conduct. This responsibility includes:
When students fail to adhere to these responsibilities, they may intentionally or unintentionally “use someone else’s language, ideas, or other original (not common-knowledge) material without properly acknowledging its source” http://www.wpacouncil.org. When the act is intentional, the student has engaged in plagiarism.
Plagiarism is an act of academic misconduct, which carries with it consequences including, but not limited to, receiving a course grade of “F” and a report to the Office of the Dean of Students. Unfortunately, it is not always clear if the misuse of sources is intentional or unintentional, which means that you may be accused of plagiarism even if you do not intentionally plagiarize. If you have any questions regarding use and citation of sources in your academic writing, you are responsible for consulting with your instructor before the assignment due date. In addition, you can work with an MSU Writing Center tutor at any point in your writing process, including when you are integrating or citing sources. You can make an appointment and find citation resources at www.montana.edu/writingcenter.
In STAT 216, students involved in plagiarism on assignments (all parties involved) will receive a zero grade on that assignment. The second offense will result in a zero on that assignment, and the incident will be reported to the Dean of Students. Academic misconduct on an exam will result in a zero on that exam and will be reported to the Dean of Students, without exception.
More information about Academic Misconduct from the Dean of Students
This syllabus, course lectures and presentations, and any course materials provided throughout this term are protected by U.S. copyright laws. Students enrolled in the course may use them for their own research and educational purposes. However, reproducing, selling or otherwise distributing these materials without written permission of the copyright owner is expressly prohibited, including providing materials to commercial platforms such as Chegg or CourseHero. Doing so may constitute a violation of U.S. copyright law as well as MSU’s Code of Student Conduct.
More information about Academic Misconduct from the Dean of Students