Problem Solving and Communication in Applied Statistics
Stat 470
Instructor Kirsten Eilertson, PhD
323C Thomas Building
or via Canvas
Graduate Teaching Assistants
Christian Schmid
Frank Shen
Course Objectives
1. Be able to apply statistical knowledge to real world problems
2. Be able to recognize experimental design
3. Be proficient in ANOVA, and GLMs including understanding the modeling assumptions
4. Be able to identify concerns about the use or interpretation of statistical models in context
5. Be able to communicate statistical findings through written and verbal communication
Course Pre-requisites:
· Stat 461 Analysis of Variance
· Stat 462 Applied Regression Analysis
· Software experience with R (Recommended)
Class Meeting Times: 001: T TH 9:05 – 10:20 a.m Ferguson 105
002: T TH 10:35 – 11:50 a.m. Ferguson 105
003: T TH 3:05 – 4:20 p.m. Sparks 6
Office Hours: Instructor: Monday 1:30 – 3pm, 323C Thomas (by appointment)
GTA:
Required Materials:
· CANVAS
· Broadening Your Statistical Horizons: Generalized Linear Models and Multilevel Models
Julie Legler and Paul Roback, St. Olaf College
http://pages.stolaf.edu/bysh/
· Assigned journal articles and selected readings (available through CANVAS)
Grading
HW 30%
Projects 40%
Discussion Leader 5%
Midterm 15%
Professionalism 10%
A: 93+ A-: 90 B+: 87 B: 83 B-: 80 C+: 77 C: 70 D: 60 F:<60
Homework
There will be about a dozen homework assignments throughout the semester which are to be completed individually. Some assignments will be on content from BYSH (class text), but other assignments will be based on assigned readings posted on CANVAS, computer lab activities, or the class projects.
Design Project
Students work in small groups to carry out a designed experiment or observational study from beginning to end. Each group writes a proposal for a project of their own devising; plans and implements the collection of data; analyzes the data in an appropriate manner; and finally writes a formal report of their findings. Groups will have at least 6 weeks to complete the study. The project must require the use of analyses more advanced than those seen in Stat 200.
Case Studies
Students will work in a small group to address the questions of a “client” on a few projects throughout the semester. Each group will be responsible for analyzing the data, writing a report appropriate for a non-statistician, and presenting the results. These projects will emphasize explaining methods and results without relying on jargon. These projects are also designed to challenge the students statistically. Professional conduct of each student in the meetings and in the final report will be evaluated and graded.
Discussion Leader
On the job, you will need to be able to teach yourself new things and explain them to others. For this assignment, each student will have a turn leading an engaging and interactive class discussion with a partner on an assigned special topic related to statistics or data science.
Professionalism
Professionalism includes attending class; arriving on time to class and meetings; being engaged while in class; and being respectful of the teacher and other students’ questions/comments and time. In presentations and meetings each student is expected to be prepared; to actively participate; and should be able to answer questions about all content presented even if it is not specifically something he/she contributed to the project. Three or more unexcused absences will affect the professionalism grade. Unexcused absences on the day of a presentation or group meeting will also affect the individuals project grade.
Problem Solving and Communication in Applied Statistics
Stat 470
Effort & participation (E & P) will be scored at the discretion of the professor & TA. Students will begin with a 75% score on the first day of class, which will then go up or down as the course progresses based on demonstrated actions. E & P is intended to help you assimilate to the dynamic that will dominate your professional/performance evaluations in a future career. Raises, promotions, and terminations can happen at the discretion of management. If you just meet the minimum expectations, you might keep your job but likely won’t get much farther. You will lose your job if you don’t consistently meet expectations, and you’ll only be rewarded with raises and advancement by going above and beyond the minimum expectations.
In our class, students that more or less just coast along and completing the minimum expectations of the course will generally earn a 70-79% score for E & P. Students that go out of their way to contribute to the success of their classmates, show initiative, emerge as leaders in groups, consistently exceed expectations etc, will earn higher E & P scores. Students that behave in ways that are problematic to others, degrade group dynamics, etc will earn a lower E & P scores.
This is a writing intensive course; all written work will be graded in terms of grammatical correctness, clarity of writing, organization, and accuracy of content.
Class may occasionally be canceled to allow scheduling of small group meetings with Dr. Eilertson for the consulting projects and design projects. These dates will be announced on Canvas and in class.
Many classes will be full or partial “Workshop Days”. On these days the class period will be driven by class discussions, problem solving work in small groups, and occasional small group meetings with Dr. Eilertson.
When relevant, class will be held in the traditional lecture format to provide relevant background knowledge needed to tackle a particular project. Topics may include:
Problem Solving and Communication in Applied Statistics
Stat 470
Problem Solving and Communication in Applied Statistics
Stat 470
v Professional Ethics
v Common Statistical Pitfalls
v Generalized Linear Models
v Multilevel Modeling
v Design (CR, LS, RB)
v Surveys
v Consulting Procedures/Strategies
v Scientific Writing
v Multiple Testing
v Equivalence Testing
v Power/Sample Size
v Bayesian Data Analysis
v Principle Component Analysis
Problem Solving and Communication in Applied Statistics
Stat 470
A tentative schedule is posted on CANVAS, but please note that this is subject to change! The rate of progress through the material cannot be perfectly determined, and may change due to experimental design logistical concerns, background of the students, weather, availability of computer resources, etc.
Add/Drop information can be found here:
http://www.registrar.psu.edu/academic_calendar/calendar_index.cfm
ABSOLUTELY NO LATE WORK WILL BE ACCEPTED! If you have a UNIVERSITY approved excuse and communicate your excuse no later than one week before your absence then, as per Faculty Senate guidelines, I will accommodate the assignment. Please note that any extended travel for personal reasons is NOT an excuse for missing class and any assignments missed will be graded as zeros. THIS POLICY IS STRONGLY ENFORCED. I WILL NOT MAKE EXCEPTIONS!
Problem Solving and Communication in Applied Statistics
Stat 470
Penn State welcomes students with disabilities into the University's educational programs. Every Penn State campus has an office for students with disabilities. Student Disability Resources (SDR) Web site provides contact information for every Penn State campus:http://equity.psu.edu/sdr/disability-coordinator. For further information, please visit Student Disability Resources Web site:http://equity.psu.edu/sdr.
In order to receive consideration for reasonable accommodations, you must contact the appropriate disability services office at the campus where you are officially enrolled, participate in an intake interview, and provide documentation:http://equity.psu.edu/sdr/guidelines. If the documentation supports your request for reasonable accommodations, your campus’s disability services office will provide you with an accommodation letter. Please share this letter with your instructors and discuss the accommodations with them as early in your courses as possible. You must follow this process for every semester that you request accommodations.
All Penn State policies regarding ethics and honorable behavior apply to this course. Academic integrity is the pursuit of scholarly activity free from fraud and deception and is an educational objective of this institution. All University policies regarding academic integrity apply to this course.
Academic dishonesty includes, but is not limited to, cheating, plagiarizing, fabricating of information or citations, facilitating acts of academic dishonesty by others, having unauthorized possession of examinations, submitting work of another person or work previously used without informing the instructor, or tampering with the academic work of other students. For any material or ideas obtained from other sources, such as the text or things you see on the web, in the library, etc., a source reference must be given. Direct quotes from any source must be identified as such. All exam answers must be your own, and you must not provide any assistance to other students during exams. Any instances of academic dishonesty WILL be pursued under the University and Eberly College of Science regulations concerning academic integrity.