Nonparametric Statistics
Stat 216
Fall 2021

Professor Bradley A. Hartlaub
Office 305 Rutherford B. Hayes Hall
Phone 740-427-5405
Office Hours

• 2:00 - 3:00 on Monday, Wednesday, and Friday
• 1:00 - 3:00 on Tuesday
• Additional appointments are available; please don't hesitate to ask for help.

Required Text

Hollander, M., Wolfe, D. A., and Chicken, E. (2014), Nonparametric Statistical Methods, Third Edition, New York, NY: John Wiley & Sons, Inc.

Learning Goals

• Improve technical communication skills
• Introduce RStudio statistical software
• Develop mathematical maturity and apply methods that you have learned in previous courses, including the ability to write mathematical proofs
• Foster productive work habits with peers, including joint presentations and assignments
• Introduce distribution-free techniques and methods (nonparametric statistical methods) that are appropriate when data do not follow the normal distribution

Accessibility Accomodations

A student with a disability who thinks they may need an accomodation to access a campus program, activity, or service should contact Erin Salva in Student Accessibility and Support Services (SASS) at salvae@kenyon.edu to discuss specific needs. Advance notice is required to review documentation, evaluate accomodation requests and provide notice or arrangements for any accomodation.

Title IX Responsibilities

As a member of the Kenyon College faculty, I am concerned about the well-being and development of students, and am available to discuss any concerns. However, I want you to know that faculty members are legally obligated to share certain information with the College’s Civil Rights & Title IX Coordinator. This requirement is to ensure your safety and welfare is being addressed. These disclosures include, but are not limited to: reports of discrimination or harassment due to a protected characteristic, including sexual harassment, sexual assault, relational/domestic violence, and stalking.

The statistical software package R will be used throughout the course. Assignments and course announcements will be sent to you via e-mail or posted on the course web page. Data sets and R scripts will be placed in our Google Drive folder Stat216-Nonparametrics-F2021. Proper maintenance of computer accounts, files, etc. is your responsibility. I recommend that you back up your data sets and R scripts or markdown files on a regular basis.

Homework assignments will be given throughout the semester. Subsets of these assignments will be collected and randomly selected problems will be graded. You should work on as many problems as possible, including problems which have not been assigned. Working with other students is encouraged, but you must submit your own solution for each of the assigned problems to be collected. For more infomation, see the departmental guidelines for collaboration on homework, which I expect you to follow.

During the semester we will have weekly problem sessions which will be conducted by you (the students). These sessions are designed to improve your understanding of statistical ideas and enhance your mathematical reasoning skills by requiring a clear, detailed presentation of the material to your peers. During these sessions, you will be responsible for solving an assigned problem and presenting the solution to the rest of the class. Answering all questions about your solution is a required part of the presentation. Being able to solve problems and being able to present the solutions to a group in a logical and coherent fashion are two different tasks. Our goal is to master both tasks.

Assignments must be turned in at the beginning of the class period on the assigned due date. No credit will be given for late papers. If for any reason you cannot turn in your assignment on the due date, you must contact me before class. If you are unable to contact me, you can leave a message on my office phone (740-427-5405) or send e-mail to hartlaub@kenyon.edu.

Exam 1 Friday, October 22
Exam 2 Friday, December 3

Each student will find a data set and apply an appropriate nonparametric analysis. Ideally, you will collect this data set yourself or obtain it from a local resource. Your analysis must include a comparison of at least two statistical techniques. The variables in the data set and the purpose of the study should be clearly defined. If the data are obtained from a periodical, the date of publication must be later than January 1, 2017. Final papers containing a detailed explanation of the problem of interest, your analyses, and your conclusions must be submitted before 11:30 am on Wednesday, December 15, 2021.

Your course grade will be based on your overall percentage. The categories used to determine your overall percentage are listed below with their respective weights.

Homework and Labs (10%)
Problem Sessions (20%)
Exam 1 (25%)
Exam 2 (25%)
Final Project (20%)

Class participation will be used to help make borderline decisions. We will follow the department class attendance policy.

• Chapter 1 Introduction
• Chapter 2 The Dichotomous Data Problem
• Chapter 3 The One-Sample Location Problem
• Chapter 4 The Two-Sample Location Problem
• Chapter 5 The Two-Sample Dispersion Problem and Other Two-Sample Problems
• Chapter 6 The One-Way Layout
• Chapter 7 The Two-Way Layout
• Chapter 8 The Independence Problem
• Chapter 10 Comparing Two Success Probabilities
• Chapter 9 Regression Problems
• Chapter 11 Life Distribuions and Survival Analysis
• Chapter 14 Smoothing