Contact Information
Course Materials
WebAssign - WebAssign is a low cost yet rigorous and reliable online homework system.
o Purchase access from WebAssign.net or an access code from OSU Bookstore osubeaverstore.com
Statistical Software - We will explore data with statistical software R studio. Homework and Exam questions will assume you can interpret software output.
o R is a free open-source language. Download base R using this link:
https://cloud.r-project.org/
o R Studio is a user interface that uses the R language. No cost download for a system with base R
http://www.rstudio.com/
Remote access through apps.oregonstate.edu using your ONID ID. No download.
Calculator – Assessments assume you have a calculator (any model) for quick computations.
Word processor - Microsoft Word is available to all OSU students. Other word processors are accepted.
Optional
Probability & Statistics for Engineering and the Sciences, Jay L. Devore, Brooks/Cole Cengage Learning, Boston, MA. Ninth Edition (2012). Reading references will be for the Ninth Edition.
o Go to the textbook list at the OSU Bookstore website (http://osubeaverstore.com/) for current information or to purchase text. Earlier editions may also be of help.
Course Description
Learning Objectives
Have an understanding of the role of statistics within the engineering profession. Be able to graphically display data in ways meaningful for interpretation. Have an understanding of variability in engineering processes and ways of modeling such variability. Have a basic understanding of the tools of statistical inference. Have an understanding of the principles of experimental design and be able to identify when such principles can be put to use for engineering problems. Be able to construct and interpret linear regression models involving one or more independent variables. Understand statistical process control and the use of control charts.
Topics
Set theory and Probability, Discrete and Continuous Random Variables and their Probability Models Expectation and Variation for Random Variables Sampling and Experimental Designs Summary Statistics and visual displays for categorical and quantitative variables Central Limit Theorem and Sampling Distributions Estimation and Hypothesis testing for single sample means and proportions Estimation and Hypothesis testing for comparing two sample means and two proportions Single Factor ANOVA Simple and Multiple Linear Regression, Scatterplots, Correlation and Residual Analysis Statistical Process Control, xbar and S charts, p and c charts R software
Canvas
Weekly Modules
Lessons
Communication
Announcements - Please check the Announcements in Canvas to receive tips, updates and class information.
Discussion Board – When you have a concept or non-personal question, post it to the weekly “Got a Question? Ask Here” discussion board. This allows all students an opportunity to respond to your question, and benefit from the explanation. Asking questions is an important part of learning. Earn up to 50 points of extra credit over term. One point per question, asked or explanation given, up to 5 points per week.
Zoom – Weekly office hours in Zoom, you can join via phone or computer. You will need a smartphone or computer to access the meetings.
Email –Use only Canvas or your OSU email address for school communication. Instructor and TA email are posted to Canvas. Not checking your email is not a valid excuse for missed due dates or events.
Email Etiquette
Put ST314 Distance and YOUR NAME in the title of your email.
o I strive to respond to your email as fast as possible, in order for me to do so it helps to have this information to identify you and your specific needs.
Use salutations.
o Start your email by “Hello Instructor Jager”, “Hi Katie”, “Dear Statistics Master”
o End your email with From, Sincerely, Thank You, Cheers, -“Your name”.
Use email only when you have a personal question.
o For efficiency, use the weekly question Discussion Board for course structure or content questions.
o Please email if you want to discuss personal grades, grading feedback or personal concerns/conflicts.
Email respond time within 48 hours (most of the time).
o Limited correspondence over the weekend from Friday 5PM to Monday 8AM.
o Haven’t gotten back to you? Please follow-up if you have not received a reply after 48 hours. Student emails can end up in SPAM or I get busy. I want to assist you and may need a reminder.
Grades
WebAssign Homework 200
Ten Assignments @ 20 points each
Data Analyses 200
Ten Reports @ 20 points each
Participation 100
Surveys and Quizzes 35 points
Collaborative Learning Assignments Total 65 Points
Midterm 250
Final Exam 250
Final Letter Grade Distribution. *:
|
A = 92% or higher | A- = 90 – 91.99% |
B+ = 87 – 89.99% | B = 82 – 86.99% | B- = 80 – 81.99% |
C+ = 77 – 79.99% | C = 72 – 76.99% | C- = 70 – 71.99% |
D+ = 67 – 69.99% | D= 62 – 66.99% | D- = 60 – 61.99% |
|
F = 59.99% or less |
|
Right to Flexibility
The instructor reserves the right to adjust final grades according to the performance of the class as a whole. The instructor may modify assignments listed in the syllabus. There may be good reason for doing so, such as incorporating an improvement partway through, or refocusing the assignment so that students can be more successful.
Extra Credit
Incomplete Grades
Request is prior to University withdrawal date. Student has earned less than 60% of the points available upon request of the incomplete.
Data Analyses
Analyses allow students to explore statistical software, practice data manipulation and discovery, implore deeper understanding of topics, and to receive individualized feedback. Submissions must be typed and submitted in Canvas. Once submitted these are sent to, “Turn it in”, a third party site to check for plagiarism. All work should be the personal thoughts and ideas of the individual submitting the assignment. What is Plagiarism?
Analyses are due on Monday each week and must be submitted on time. Specific due dates are on the Canvas calendar and within each module. The TWO lowest data analyses score are dropped and replaced by the average of the remaining analyses. Within one week of the due date, your teaching assistant will grade and provide feedback on your work.
Pre-grading of Analyses - You are invited and encouraged to turn in your data analysis early for pre-grading and feedback. Analyses submitted on Friday prior to the Monday due date, will be pre-graded by Sunday. At which point, you will have the opportunity to view feedback, make changes and resubmit your work by Monday night for final grading. If you choose to not re-submit, the grade received during pre-grading will be finalized.
Data analysis requirements for grading
WebAssign Homework
WebAssign Communication
Exams
Midterm - The midterm window is during week 6 of the term and will include material from weeks 1-5. Final - The final exam is comprehensive. The exam window is scheduled during finals week. See Canvas for specific exam window dates. Exams are administered online in Canvas.
o Due to COVID 19 exams will not be need a proctor.o You may not use each other or any other online resources to complete questions. Sharing exam questions or responses is in violation of student conduct.
Exam Policies
Allowances
o Calculator or R- Any model. Except cell phone.o Notes – Any course resourceso Statistical tables – Provided in exam.o Pencil/Scratch Paper
Exam submitted during the exam window.
o Exam windows are non-negotiable.o You may reschedule an exam if it is within the exam window.o Failure to take an exam during the exam window may forfeit the opportunity to take an exam.
Technical issues during the online exam
o If a technical issue prevents you from completing the exam, immediately email the instructor.o Document the situation and provide a report to the instructor.o If you need another attempt or extension due to extraordinary circumstances, please make your request within 2 hours of original issue. Later requests may be denied.
Student Conduct and Academic Integrity
You are expected to submit your own ideas and efforts for all assignments and to transparently provide credit to the work of others if you use it. If you are curious whether something might be considered academic dishonesty, please ask me!
A violation of these expectations may result in a zero grade on the assignment and in some cases disciplinary action. Link to Oregon State University's entire Student Conduct Code: http://studentlife.oregonstate.edu/code
External Sources and Academic Dishonesty
Using past solutions from friends or sites like chegg, coursehero, koofers and/or study blue must be cited. The use of these materials must not violate the rules of academic dishonesty.
Any materials posted to an external site must be your own work. I prohibit my intellectual property from being shared in any manner without explicit or written consent. My intellectual property includes, but is not limited to, the course notes, syllabi, exams, homework and data analysis questions, keys and solutions.
Cheating hurts all students. It changes the way a teacher has to provide materials and give assessments. Ultimately, cheating erodes the foundation of a prosperous learning environment. If you witness a violation of academic dishonesty, please report the issue.
Reach Out for Success
Students with Disabilities
Technical Assistance
o IS Service Desk, Milne 201, 541-737-8787 or go to http://is.oregonstate.edu/is-helpdesks-get-help-now
o http://ecampus.oregonstate.edu/services/technical-help.htm
o Call toll free (800) 955-8275 or go to http://webassign.com/support/student-support/
Course Evaluation
During the term if you have comments or concerns, I invite you to a respectful and insightful conversation.