Nonparametric Statistics
Stat 216
Fall 2023

 

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

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

Accessibility Accomodations

A student who thinks they may need an accomodation to access a campus program, activity, or service should contact Ruthann Daniel Harteis in Student Accessibility and Support Services (SASS) at danileharteis1@kenyon.edu 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.

Statistical Package & Computing

R and RStudio 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-F2023. 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.

Our class meets in a classroom where you will be expected to use your laptop, and we will be using statistical software extensively in the course. During regular class hours, the use of computers is restricted to activities deemed appropriate by the instructor. Playing computer games, reading e-mail, conversing in a chat room, surfing the web, and working on assignments for other courses are a few examples of inappropriate activities that can be distracting to the instructor and other students in the course. Inappropriate computer use may result in penalties ranging from warnings to loss of computer privileges for the period. In cases of extreme and/or repeated violations, grade penalties or expulsion from the course may result.

Homework

Homework assignments will be given throughout the semester. I encourage you to work on as many problems as possible, including problems which have not been assigned. Subsets of the homework assignments will be collected and graded. Your solutions must be submitted electronically to your Google Drive folder. You must submit a PDF of your solutions using a very specific naming structure. For example, the name of the file for the first homework assignment should be HW1-yourname.PDF. Working with other students is encouraged, but each student must submit her/his own solution for problems to be collected. For more infomation, see the departmental guidelines for collaboration on homework, which I expect you to follow.

Homework is due at the start of class on the assigned due date, unless specified otherwise. Each student will be allowed two "free" 48-hour extensions on homework assignments; no reason needs to be provided. Simply email me in advance of the due date to say that you would like to use one of your two extensions. After the second extension, late homework will not be accepted. However, your lowest homework score will be dropped at the end of the semester.

The grading rubric for all HW exercises is:

Complete (10/10)

  • Contains no non-trivial errors and clearly communicates understanding
  • Achieves a correct solution
  • Justifies decision(s) toward solution
  • Effectively communicates solution and support
  • Notation used is appropriate and clearly shows all steps

Substantial (9/10)

  • Meets expectations and contains an easily correctable mistake
  • Makes correct decision(s) toward solution
  • Justifies decision(s) toward solution
  • Effectively communicates solution and support
  • A slight error, confused reasoning, or notational mistake
  • Refinement is needed

Developing (8/10)

  • Contains correct work and a serious error in understanding or communication
  • Makes some correct decision(s) toward solution
  • Some justification of decision(s) toward solution
  • Attempts to communicate solution and support
  • A wrong decision, confused reasoning, and/or notational mistakes
  • Revision is needed

Developing (7/10)

  • Does not contain the correct answer but shows some correct work
  • Incorrect decision(s) toward solution
  • Insufficient or incorrect justification for decision(s) toward solution
  • Little or no communication of solution and support
  • Several wrong decisions, confused reasoning, and/or notational mistakes
  • Revision is needed

Minimal (5/10 or 6/10)

  • Does not contain the correct answer or work in the correct direction
  • Missing or incorrect decision(s) toward solution
  • Little or no justification for decision(s) toward solution
  • Several wrong decisions, confused reasoning, and/or notational mistakes
  • Major revision is needed

No work or something completely off base (0/10)

Problem Sessions

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. Randomization will be used to assign at least two students to each exercise. 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.

After your problem session presentation, you are required to upload a complete copy of your solution to the Google Drive folder !Student R Code_Solutions for Exercises using a specific naming structure. For example, the name of the file for exercise 0.42 will be 0.42_yourname.PDF or 0.42_yourname.R or 0.42_yourname.RMD. The primary reason for the specific naming structure is so that the folder stays organized and the entire class has a complete set of solutions for every exercise that we discuss during our problem sessions.

Late Policy

Your work must be turned in before class begins on the assigned due date. No credit will be given for late papers, except in the two cases where you may opt to use your "free" 48-hour extension. If for any reason you cannot turn in your assignment on the due date, you must contact me or send e-mail to hartlaub@kenyon.edu before class begins.

Exams
Exam 1 - Friday, October 20
Exam 2 - Friday, December 1
Final Project
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, 2019. Final papers containing a detailed explanation of the problem of interest, your analyses, and your conclusions must be submitted before 6:30 pm on Wednesday, December 13, 2023.
Grades
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. Class participation will be used to help make borderline decisions. We will follow the department class attendance policy.
Course Outline