Course Syllabus ST314 - Introduction to Statistics for Engineers - Ecampus - 3 Credits

Course Syllabus
ST314 - Introduction to Statistics for Engineers - Ecampus - 3 Credits


Contact Information

Instructor: Katie Jager, MS
Office: Weniger 273 Zoom Office Hours: TBA on Canvas or By Appointment


Course Materials

Required
    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

Introduction to Statistics for Engineers is a fast-paced introductory course for students majoring in engineering, science or computer science. The course requires a brief understanding of integral calculus. ST314 is designed to be a dense one-term introduction to probability, inferential statistics, experiments, hypothesis testing, estimation, regression, statistical process control and statistical coding and interpretation using R. ST314 is worth 3 credit hours. Students should expect to spend up to 9 hours per week on online instruction, homework and readings.


Learning Objectives

The following are expectations of a student after the completion of this course.
    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

The Canvas page is our classroom. Canvas contains lessons, contact information, and a calendar with events and due dates. You will turn-in data analyses, communicate with peers, receive feedback on assignments, review grades and take exams in Canvas. A teaching assistant monitors the Canvas discussion boards where you are encouraged to post questions. You can access Canvas through an app available for Android and Apple. Login to Canvas on a regular basis (at least every two days).


Weekly Modules

Materials and student expectations are listed in the Modules tab for each week of the course. For clear understanding of expectation, you should read and follow the instructions for the week. Modules for the following week are released on Friday of the week prior.


Lessons

A series of lessons are posted in each weekly module. The lessons include all of the material you are expected to know for that week. Spending time to watch and review video lessons and take notes is imperative to understand course material. Lessons include R Code and links to R video Tutorials, short quizzes (not graded) and “Your Turn” practice examples accompanied with video solutions. Assessments including Exams, homework and analyses are designed to emphasize learning the concepts initially covered in the 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

I strive to provide clear feedback and post grades quickly and often. You are responsible for monitoring your grades. Please voice grading concerns within one week of the original due date and prior to finals week.
Your final grade is based on the percentage of points earned out of 1000 points. Letter grades are automatically
assigned in the Canvas gradebook.

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
                                                                                                                                          Total 1000


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

Extra Credit is awarded to those who ask and answer questions on the discussion board. A few additional opportunities will be available throughout the term. Extra Credit is added at the end of the term.


Incomplete Grades

To request an incomplete please review the valid reasons for receiving an I Grade fill out the request form available online or in the Statistics office (Weniger 239). Statistics Department policy on Incompletes: http://www.stat.oregonstate.edu/current/incomplete. Please read the instructions for valid reasons to request an Incomplete. Return the completed request form to the Statistics office. You will be notified within a few days of making the request as to whether your request was granted.
Reasons an Incomplete will not be granted:
    Request is prior to University withdrawal date.
    Student has earned less than 60% of the points available upon request of the incomplete.


Participation

Peer interaction is encouraged and structured through four collaborative learning assignments. These assignments will have at least two staggered submissions to promote interaction. Please refer to specific weekly units and assignments to understand instructions for submissions. You will also be expected to take part in the ST314 Student Information Survey, Syllabus Quiz and After Midterm Survey. Participation is worth 10% of the overall grade and is based on the timely completion of these assignments.


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

    Submit work on time in Canvas. Work submitted after solutions are available will not be graded. Solutions are posted at 12PM PST following the due date.
    Label and type answers (exception only equations and arithmetic work can be written neatly by hand and included along with typed text answers.)
    Do not include question prompts in your submission. Doing so will falsely alert the plagiarism software. You are allowed to include any diagrams I have provided to aide you in answering the problem.
    After submission, review your submission to ensure you uploaded the correct document.
    You need to review feedback and grades. Grading concerns must be made within 1 week of the due date.


WebAssign Homework

WebAssign homework is intended to provide students with immediate, formative feedback. Weekly homework is due on Sunday and is accessed and submitted in WebAssign. To prevent you from falling behind, due date extensions are not granted, however, your lowest TWO WebAssign scores are dropped and replaced by the average of your other grades. The homework key is reviewable in WebAssign after the Sunday due date. Grades are manually posted to Canvas at midterm and finals weeks.


WebAssign Communication

Please use the discussion board for homework questions. Post the homework question number and any work you may have started or need clarification on. Do not use the WebAssign functions “ask your teacher” and “request an extension”.


Exams

About the Exams - There are two online exams in this course. A midterm and a comprehensive final.
    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 resources
o    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

Any action that misrepresents a student or group’s work, knowledge, or achievement, provides a potential or actual inequitable advantage, or compromises the integrity of the educational process. Prohibited behaviors include, but are not limited to doing or attempting the following actions:
1.    Cheating. Unauthorized assistance, or access to or use of unauthorized materials, information, tools, or study aids. Examples include, but are not limited to, unauthorized collaboration or copying on a test or assignment, using prohibited materials and texts, unapproved use of cell phones, internet, or other electronic devices, etc.
2.    Plagiarism. Representing the words or ideas of another person or presenting someone else's words, data, expressed ideas, or artistry as one's own. Examples include, but are not limited to, presenting someone else's opinions and theories as one's own, using another person's work or words (including unpublished material) without appropriate source documentation or citation, working jointly on a project and then submitting it as one's own, etc.
3.    Falsification. Fabrication or invention of any information. Examples include, but are not limited to, falsifying research, inventing or falsely altering data, citing fictitious references, falsely recording or reporting attendance, hours, or engagement in activities such as internships, externships, field experiences, clinical activities, etc.
4.    Assisting. Any action that helps another engage in academic misconduct. Examples include, but are not limited to, providing materials or assistance without approval, altering someone's work, grades or academic records, taking a test/doing an assignment for someone else, compelling acquisition, selling, bribing, paying or accepting payment for academic work or assistance that contributes to academic misconduct, etc.
5.    Tampering. Interfering with an instructor’s evaluation of work by altering materials or documents, tampering with evaluation tools, or other means of interfering.
6.    Multiple submissions of work. Using or submitting work completed for another or previous class or requirement, without appropriate disclosure, citation, and instructor approval.
7.    Unauthorized recording and use. Recording and/or dissemination of instructional content without the express permission of the instructor(s), or an approved accommodation coordinated via Disability Access Services.


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

University students encounter setbacks from time to time. If you encounter difficulties and need assistance, it’s important to reach out. Consider discussing the situation with an instructor or academic advisor. Learn about resources that assist with wellness and academic success at oregonstate.edu/ReachOut. If you are in immediate crisis, please contact the Crisis Text Line by texting OREGON to 741-741 or call the National Suicide Prevention Lifeline at 1-800-273-TALK (8255)


Students with Disabilities

Accommodations for students with disabilities are determined and approved by Disability Access Services (DAS). If you, as a student, believe you are eligible for accommodations but have not obtained approval please contact DAS immediately at 541-737-4098 or at http://ds.oregonstate.edu. DAS notifies students and faculty members of approved academic accommodations and coordinates implementation of those accommodations. While not required, students and faculty members are encouraged to discuss details of the implementation of individual accommodations.


Technical Assistance

    OSU Accounts, Canvas or Computer Issues
o    IS Service Desk, Milne 201, 541-737-8787 or go to http://is.oregonstate.edu/is-helpdesks-get-help-now
    Technical Help from Ecampus
o    http://ecampus.oregonstate.edu/services/technical-help.htm
    WebAssign Technical Support
o    Call toll free (800) 955-8275 or go to http://webassign.com/support/student-support/


Course Evaluation

I encourage you to engage in the course evaluation process. The evaluation is available toward the end of each term, and you will be sent instructions through ONID. You will login to “Student Online Services” to respond to the online questionnaire. The results on the form are anonymous and are not tabulated until after grades are posted.


During the term if you have comments or concerns, I invite you to a respectful and insightful conversation.



2021-01-07