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Online STAT 705 – Regression and Analysis of Variance -- Syllabus for Spring 2022

Instructor Information

I am Dr. Karen Keating, your instructor for this course. I do not have an office on the Manhattan campus, so the best way to contact me is via email. I prefer that you use Canvas email for all correspondence. In the rare event that Canvas email is not available, you can also reach me at my

K-State address[email protected]. I am also available for personal conversations via Zoom. Just email me and we can set a time to meet.

Prerequisites

The prerequisite for this course is one previous statistics course. You should already understand how to perform a hypothesis test (particularly using the p-value approach), and you should also understand confidence intervals. If these concepts are vague to you, I strongly suggest that you do two things:

1) Read the document Review of Basic Statistical Concepts, which is the first link in the Getting Started module.

2) Obtain an undergraduate textbook for introductory statistics and keep it as a reference.

Structure of the Course

In the first half of the semester, we will be covering topics in regression analysis. In the second half of the semester, we will be covering topics in Analysis of Variance (ANOVA). This course consists of 6 modules, and each module contains between 3 and 8 lessons. Each lesson corresponds to one section in the textbook. Most lessons include short “Check Your Knowledge” questions, which you can use to assess your understanding of the lesson. These questions are available only online, and are not graded. There are four graded homework assignments in which you will analyze a provided data set and answer questions about the analysis. The answers to these assignments are submitted online. There are also two graded exams, which are also submitted online.

Timeline

The due dates for the exams and homework assignments are given in Canvas. These dates are based on a regular on-campus course. While I encourage you to work at your own pace, the course needs to be finished by the end the semester, so that I can turn in the grades on time. You are welcome to work through the material faster than what is indicated in the schedule shown below. To stay on schedule, you should plan to complete three lessons per week. This is equivalent to an on-campus course that meets three times a week.

Textbook

Your instructor has written a textbook specifically for this course. It is free and a PDF can be downloaded from Canvas. No other textbooks are required.

Exams and Homework

Your final course grade will be based on two exams (a midterm and a final), each worth 100 points, and four homework problems worth 25 points each. All of these will be submitted online. For each of the four homework assignments, I will provide a dataset and a list of questions to answer. You will work offline to answer the questions. When you are finished, you will enter your answers into Canvas. The two exams are also online, but you will not get the questions in advance.

No proctor is required for any of the assignments (neither homework nor exams). You are bound by the K-State Honor Pledge: "On my honor, as a student, I have neither given nor received unauthorized aid on this academic work."

Make-up Policy

Each exam and homework assignment has a due date and time. These must be submitted online by the deadline. You are welcome to submit these early, but late submissions cannot be accepted. (This is a limitation in Canvas. I cannot provide feedback to any student until all students have submitted the assignment.) All assignments will be graded within 48 hours after its deadline. At that point, you can view your scores, see the complete solution, and read my comments in the Canvas SpeedGrader.

The day and time for each deadline corresponds to the local time in Manhattan, KS. This is either CDT or CST, depending on the time of the year. Canvas should automatically convert all due dates to match

your local time. If there is ever any confusion, feel free to email me or you can use the online time zone

converter:https://www.timeanddate.com/worldclock/converter.html.

These deadlines have two purposes:

1. They help you stay on track so you can complete the entire course by the end the semester.

2. They allow the instructor to provide feedback to students and release the grades in a timely manner.

I strongly recommend that you try to submit these assignments a day or two ahead of the deadline, to avoid the stress of dealing with potential technical issues or other emergencies. If there is a dire and unavoidable circumstance that prevents you from completing an assignment on time, please contact the instructor as soon as possible. Personal emergencies should be documented through the Office of Student Life. Without documentation, missing or late assignments will receive a grade of 0.

Grading Scale

There are a total of 300 points possible for the semester. Letter grades are assigned as follows:

A is 270 to 300 points

B is 240 to 269 points

C is 210 to 239 points

D is 180 to 209 points

F is 179 or less

There will be no opportunities for individual extra credit, no make-up assignments, and no additional curving of grades at the end of the semester.

Software

We will be using SAS (an acronym for Statistical Analysis System) in this course. Prior knowledge of SAS is not a requirement for this course. I will provide complete SAS code for all the examples that are in the lectures, and you can modify the code to suit individual needs. There are many different ways to access SAS, and each one is slightly different. I highly recommend that you use SAS Studio, even if you already have access to a recent version of SAS. Older versions of SAS may not properly execute the code that I provide. SAS Studio operates through a web browser, and can be accessed from both MACs and PCs . You will need to create an account with SAS, but this is a free service and you can continue to use it after our course is complete. During the first week of the semester, I will provide directions for obtaining a free version of SAS and instructions for basic SAS programming. If you want to get started now, here are some links from the SAS website.

• General directions for accessing SAS Studio:

http://support.sas.com/ondemand/manuals/SASStudio.pdf

• After you are successfully enrolled, you can access SAS Studio at any time from any browser at this URL: https://odamid.oda.sas.com/SASLogon/login

• General information about using SAS Studio:

http://support.sas.com/documentation/cdl/en/webeditorug/66932/HTML/default/viewer.htm#

p092daf4a5ypjcn138maiooc8wsn.htm

Technology Requirements

K-State has technology recommendations (http://www.k-state.edu/its/buying/) for success in online learning. You can also visit the K-State Global Campus website to make sure your technology (http://global.k-state.edu/students/services/technology) is up to date. Canvas will work best in the Google Chrome browser, and JavaScript must be enabled. If you choose to use another browser, please make sure your course materials function within that system. You may need to confirm that your browser, java, flash, and pdf reader are all updated to the latest version.

Technical Difficulties

The K-State IT Help Desk is available to assist you with questions regarding the technology used for your course.

Phone: 785-532-7722 or toll free 1-800-865-6143

Email:[email protected]

If you have issues with your technology, please contact them first, they are the technology experts. If you continue to have problems, please email the instructor. If you miss a deadline due to technological difficulties, make sure it is documented through communication with the IT Help Desk, then exceptions may be made on a case-by-case basis.