MATH 456-02: Syllabus
Applied Statistical Methods II
BSS Building 237
TTh 9.30 - 10.45am
Contact Information
Edward A. Roualdes (call me Edward)
email: eroualdes@csuchico.edu
Office hours:
- WTh 2 - 2.50 in Holt 204
- F 11 - 11.50 in Innovation Lab
- or by appointment, please email me to find a time that works for us both
Course Description
Advanced topics in applied statistics including multiple and logistic regression, multivariate methods, multi-level modeling, repeated measures, and others as appropriate. The statistical programming language R is used. Appropriate for biology, agriculture, nutrition, business, psychology, social science and other majors. 3 hours discussion
Student Learning Objectives / Goals
- Improve understanding of Mulitple Linear Regression
- Begin Logistic Regression
- Begin hierarchical linear models
- Practice programming language R
Textbook
- OpenIntro Statistics, 4th Edition (OS4). A pdf of this book is free, just slide the amount you are willing to pay to $0.00. Alternatively, you can order a B&W paperback version of this book for $25; $40 for color. We'll focus on the last chapters, but the first few may be helpful.
Here's some other free references which I like on the topic.
- https://hbiostat.org/rmsc/
- https://uc-r.github.io/
- https://online.stat.psu.edu/stat501/
- https://online.stat.psu.edu/stat504/
Additional Requirements
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Access to a computer will be essential to master the material of this course. If you don't have immediate and consistent access to a laptop, please speak to me as soon as possible.
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We will learn to code in R using the programming environment RStudio Desktop, both of which are free software.
Content Delivery
Lectures are in person at the times listed above. No recordings will be available. As Gil Scott-Heron says, the revolution will not be televised; this class will be live.
All course materials will be posted to my website: roualdes.us/teaching/456.
Course Communication
The absolute best place to ask a question is during lecture. I understand, though, that not all students feel comfortable asking questions publicly.
If you prefer more private and in person communication, come to office hours.
If you prefer written and identifiable communication, email me at eroualdes@csuchico.edu. If your questions become too complex for email, as judged by me, I reserve the right to ask you to come visit my office to receive your answers in person.
If for any reason I need to address everyone in the course, I will send you an email to your student email account, eg you@csuchico.edu.
Course Grading
Your final grade for this course will be given according to the +/- grading system, based on the following percentages and scale: 90 - 100, A; 80 - <90, B; 70 - <80, C; 60 - <70, D; <60, F.
| Component | Percentage |
|---|---|
| Homework | 10% |
| Quizzes | 30% |
| Tests: 3 @ 20% each | 60% |
Grades will be posted to a shared (between me and each of you, individually and exclusively) Google Sheets file.
So long as you understand the Academic Integrity Policy below, I encourage you to use large language models, like ChatGPT, to help you learn. However, I refuse to grade AI slop. If I judge the content of your work to be AI slop, I reserve the right to give you a failing grade on that assignment. You can meet me in office hours to try to defend your case.
Assignments
All assignments must be created using Quarto, compiled into HTML (preferred) or PDF, and uploaded to our shared Google folder.
There will be so much time to work on homework in class, that homeworks will be part at home and part in class. This is part of the reason that access to a laptop is essential to this course.
Each homework assignment should be uploaded into its own subfolder,
called say homework01 which itself is located within our shared
Google folder. Notice how I'm attempting to force you on proper
computer organization. Folders should provide the context, not file
names.
Tests
There will be three tests. Two mid-terms and one final. Tests will be pen and paper. No notes. No GPT (nor any other LLM). No computers.
Make-Up Policy
Homework assignments can be submit late, or resubmit, one time, for a maximum of 50% of the points you missed. You can submit a homework assignment as late up until the next test, but not after.
You can make up a test so long as you missed the test for an unavoidable emergency. Please contact me within 24 hours of the test to let me know of your unintended absence, and so that we can schedule your make up.
Diversity Policy
Respect: Students in this class are encouraged to speak up and participate during class meetings. Because the class will represent a diversity of individual beliefs, backgrounds, and experiences, every member of this class must show respect for every other member of this class (this includes me).
Academic Integrity Policy
Students are permitted and encouraged to collaborate on all assignments other than quizzes and tests. I even encourage you to learn from GPT (or another LLM of your choice). However, each student must turn in their own work. Your own work is not produced by any LLM. Submitting work that is even suspected to be not yours will be met with an immediate 0% grade. Repeated submission of not your own work will be dealth with as cheating, as described below.
Further, it is the expressed expectation of this instructor that all students demonstrate integrity and individual responsibility in all actions related to this course. Unethical behavior of any kind is unacceptable and will be prosecuted vigorously. Any sign of cheating in any way on any course assignment will be addressed directly, according to University standards. If you do not understand what plagiarism is, or what cheating entails, you must seek information regarding this matter from the current University Catalog and from me. The consequences of plagiarism begin with a failing grade on the work, and possibly a failing grade in the course, depending upon University action. More information is found on the Student Conduct, Rights, and Responsibilities campus webpage.
Disability Support
If you have any disability related needs, please contact Disability Support Service (Colusa Hall 898-5959 or campus information 898-INFO for directions) on campus to obtain the appropriate documentation. Afterwards, email me to identify your needs within the first two weeks of class so that any necessary arrangements can be made.
Confidentiality and Mandatory Reporting
As an instructor, one of my responsibilities is to help create a safe learning environment on our campus. I am required to share information regarding sexual misconduct with the University. Students may speak to someone confidentially by contacting the Counseling and Wellness Center (898-6345) or Safe Place (898-3030). Information on campus reporting obligations and other Title IX related resources are available here: www.csuchico.edu/title-ix.
Course Outline
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Recap 315/615
- Data Basics
- Data Collection
- Observations and Experiments
- Types of Variables
- Categorical Data
- Contingency Tables
- Summary Statistics
- Box Plots / Histograms
- Plots by Group
- Scatter Plots
- Group Summary Statistics in R
- Discrete
- Continuous
- Point Estimates
- Sampling Distribution
- Confidence Intervals
- Central Limit Theorem
- Testing Means
- Testing Proportions
- Testing Differences
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Test 1
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Multiple Linear Regression
- Inference and Interpretation About Parameters
- Bootstrap
- Assumptions
- Diagnostics
- Transformations
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Test 2
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Logistic Regression
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Multi-level Modelling
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Penalized/regularized regression
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Anything else we want and have time for
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Test 3