Professor Bradley A. Hartlaub
Office 305 Rutherford B. Hayes Hall
Phone 740-427-5405
e-mail hartlaub@kenyon.edu
Office Hours

• 1:00 - 2:00 on Monday, Wednesday, and Friday
• 2:00 - 4:00 on Tuesday, (sign up for an appointment)
• Additional appointments are available, please don't hesitate to contact me to set up a convenient meeting time.

Required Textbooks

Wackerly, D. D., Mendenhall, W., Scheaffer, R.L. (2008), Mathematical Statistics with Applications, 7th Edition, Belmont, CA: Brooks/Cole, Cengage Learning, Inc.

Chihara, L., and Hesterberg, T. (2018), Mathematical Statistics with Resampling and R, 2nd Edition, NJ: John Wiley & Sons, Inc.

Learning Goals

• Improve technical communication skills, both oral and written
• Introduce RStudio statistical software
• Continue to develop mathematical maturity, especially with proofs
• Make connections with and provide derivations for statistical methods applied in previous courses
• Foster productive work habits with peers, including joint presentations and assignments
• Apply methods learned in probability to provide mathematical proofs for statistical methods used to make inferences
• Master different methods for deriving appropriate estimators
• Explore mathematical properties of different statistics
• Gain an understanding of how to compare and constrast different inference methods
• Discover how to compare and contrast statistical models from a mathematical persepective

Accessibility Accomodations

A student who thinks they may need an accommodation to access a campus program, activity, or service should contact Ruthann Daniel Harteis in Student Accessibility and Support Services (SASS) at danielharteis1@kenyon.edu  to discuss specific needs. Advance notice is required to review documentation, evaluate accommodation requests and provide notice or arrangements for any accommodation.

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 and Computing

The R statistical software package 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, R scripts, and R Markdown files will be placed in our Google Drive folder. Proper maintenance of computer accounts, files, etc. is your responsibility. I recommend that you back up your data sets, worksheets, and R scripts on a regular basis. I will not assume you have prior experience with statistical software so you do not need to be concerned about the use of technology in the classroom. R is free and you may download and use it on your own personal machine.

Homework & Labs

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 problem sessions which will be conducted by you (the students). These sessions are designed to improve your understanding of the material and enhance your mathematical maturity 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.

After your problem session presentation, you are required to upload a complete copy of your solution to the Google Drive folder !Problem Sessions - Student Solutions using a specific naming structure. For example, the name of the file for exercise 1.42 will be 1.42_yourname.PDF or 1.42_yourname.R or 1.42_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. You do not need to provide a rationale to use your 48-hour extension, but you must let me know before class.

Exams

Exam 1 - Friday, March 1

Exam 2 - Friday, April 19

Comprehensive Final Exam - Friday, May 10 from 1:30 until 4:30 pm - there may be a take-home component to the exam.

Group Project(s)

Each group will prepare 20 minute presentations for class. You may use the blackboard, a standard overhead projector, Power Point, or some other presentation software of your choice.

Your presentations will focus on a mathematical statistics topic of your choice. The topic should build on the basic foundation we have developed so far in the course, but the objective of this assignment is for you to apply the concepts and results we have learned to a problem that goes beyond what we have covered in class. For example, you may want to introduce a new statistical method for inference (e.g., permutation tests, bootstrapping, MCMC, etc.) that we have not considered. You might want to compare and contrast different estimators or hypothesis tests in a variety of settings.

More details will be provided on our course web page as the project deadlines approach. However, a short proposal describing your project will be required. I will approve your project proposal or make suggestions as soon as possible after I receive your proposal. The proposal will be submitted via e-mail. Before your presentation, you should prepare a short (1 page, front and back if necessary) handout which summarizes the main ideas from your presentation for members of the audience. In short, I want you to be creative.

Grades

Your course grade will be based on your overall percentage. The categories used to determine your overall percentage are listed below. The categories will be weighted equally.

Homework Assignments

Problem Sessions and responses to Google Forms

Group Projects

Exam 1

Exam 2

Final Exam

Class participation will be used to help make borderline decisions.

Chapter 6 (Review) Functions of Random Variables

Chapter 7 (Review) Sampling Distributions and the Central Limit Theorem

Chapter 8 Estimation

Chapter 9 Properties of Point Estimators and Methods of Estimation

Chapter 10 Hypothesis Testing

Chapter 11 Linear Models and Estimation by Least Squares

Chapter 12 Considerations in Designing Experiments

Chapter 13 The Analysis of Variance

Chapter 14 Analysis of Categorical Data