Spring 2018 – SYLLABUS
Michigan State University
STT 430: Probability and Statistics for Engineering
Time and Place: / MW 3:00-4:20pm, A126 Wells HallInstructor: / Dr. Marianne Huebner
Office: / C-422 Wells Hall
Email: / (preferred method of contact for course related questions is via piazza)
Online Discussion Forum and Contact: / (preferred method of contact for course related questions)
Helproom: / A-102 Wells Hall. Hours:
Office Hours: / MW 1:30-2:30pm or by arrangement
Prerequisites: / MTH 234
Course Web page /
Course description: Calculus-based probability and statistics with applications. Discrete and continuous random variables and their expectations. Point and interval estimation, tests of hypotheses, and linear regression.
Requirements:
Text: Devore J (2011). Probability and Statistics for Engineering and the Sciences [8thed], Thompson/Brooks/Cole, Belmont CA. Special Edition.Homework problems refer to this edition.
Calculator:TI-84 or a calculator with probability distributions (normal, t, binomial, Poisson, chi-square, F, inverse normal, inverse t). Explanations how to use these functions on the TI-84 (probability distributions and statistical inference) will be provided in class. You should bring your calculator to every class.
Statistical Computing:Computing is a fundamental tool of discovery that involves the use of statistical software for computational and graphical approaches to summarize data, analyze data, and evaluate models.
Homework assignments will use Rstudio and example code will be provided. R is open source and runs on UNIX, Windows, or Mac. To download go to It is maintained by the R core development team, an international team of volunteerdevelopers. It has built-in statistical functions, excellent graphics, and, in some cases, more up-to-date statistical software than commercial products. It is recommended that you use Rstudio, a visual interface to R that runs on Windows, Mac, or Linux, at However you need to install R first. The use of R/Rstudiowill be demonstrated in class to which you can bring your laptop with R/Rstudio installed.
Online Forum( Post your questions on Piazza anytime. Students can respond or collaborate to edit responses (Wiki Style). The instructor can endorse answers given by students. Students can opt to post or edit anonymously. Tag your post with a # sign, e.g. #chap3, to be able to filter answers and questions efficiently. The site is FERPA compliantand you can ask your questions by marking it private so that only the instructor will be able to see. The most helpful students will receive up to 5 additional points extra credit.
LON CAPA (: Class materials and homework assignments are posted on LON CAPA. Answers to online homework questions are submitted and graded on this website. Your grades will be posted on this site. You need to make sure the grades recorded on LON CAPA are correct. If these do not agree with your record, please let the instructor know in a timely fashion. No grades on LON CAPA will be changed after the last day of class.
Lecture: The lectures are used to present basic ideas. This is a calculus based probability and statistics course with practical and commonly encountered statistical concepts and methods.
Tentative outline of the course
Week of Jan 8: Introduction to Rstudio and Rmarkdown. Descriptive statistics, Probability concepts
Week of Jan 15: Probability concepts (chap 2)
Week of Jan 22: Discrete probability distributions (chap 3)
Week of Jan 29: Continuous probability distributions (chap 4)
Week of Feb 5: EXAM. Continuous probability distributions
Week of Feb 12: Multiple random variables (chap 5)
Week of Feb 19: Central limit theorem (chap 5)
Week of Feb 26: Confidence intervals (chap 7)
Week of Mar 12: Hypothesis test (chap 8)
Week of Mar 19: EXAM. Two sample inferences
Week of Mar 26: Two sample inference (chap 9)
Week of Apr 2: Categorical data analysis (chap 14)
Week of Apr 9: Linear Regression (chap 12)
Week of Apr 16: Multiple regression (chap 13)
Week of Apr 23: Diagnostics (chap 13)
Week of Apr 30: FINAL EXAM
Attendance: You are expected to attend all meetings of the class. If you miss a class for whatever reason, you need to arrange for someone to take notes for you.
Other useful information:
Help Room: Statistics Help Room A102 Wells Hall is staffed for certain hours of the week with teaching assistants to give walk-in help. See Help Room schedule posted on .
Statistics with R: There are many online sources and help forums (stackexchange). Functions and code you need in class are provided in the R tutorials that are included in the special edition textbook. They can also be downloaded from here:
- R reference card (pdf) by Tom Short (
- Quick-R: quick online reference for data input, basic statistics and plots ( )
Grading:
Computational Homework is assigned in class and will be collected at the beginning of the class period of the due date. No late homework will be accepted for any reason.It is required that you use Rstudio to solve the homework questions and write your homework as an R markdown file.
Online Quizzes are assigned occasionally and are excellent practice to make sure you understand the concepts and procedures. There are no make-up quizzes. You need to use R to derive the numerical answers, since this was used to code the problems and calculators are not as precise. These are randomly generated data sets and thus by chance problems can occur. In that case your online answer will be graded manually.
There will be some In-Class Quizzes.
Examsare closed books and closed notes, but hand calculators are permitted. Exams are worth 60 points each. There will be two exams and a final. Students who miss an exam for a valid reason and contact the instructor on or before day of the exam will be allowed to drop that score. No make-up exams will be given for any reason.
The exams contain questions concerning textbook problems, quiz problems, classroom examples and discussions,instructional videos. There will be questions regarding interpretation of computer output from R, or writing/interpreting R code.
Exams will be returned in class. If you disagree with the grading, you must show the hard copy to the instructor during the same class the test is returned. If you miss the class when the test is returned, you have one week to pick up the test and discuss any grading of that test with the instructor. No changes to the grade will be made after that time.
Exam rules: Bring a picture ID!During exams, cell phones are to be off and stowed where they cannot be seen. If your phone rings during an exam or you are seen with your phone out of your bag, you will be asked to leave the room and will receive a zero on the test. If you miss one exam (e.g. MSU sponsored trip, illness), you will be allowed to drop that score and be graded on the basis of the other exams. There will be no make-up exam for any reason.
Exam 1: Wednesday, February 7
Exam 2: Wednesday, March 21
Final Exam: Wednesday, May 2, 5:45pm
Grading scale:
Source / Maximum PointsExams (2) / 120
Final exam / 80
Homework assignments
Points will be standardized to 100 points. No dropped assignments. / 100
Quizzes (in class and online)
Points will be standardized to 100 points. No dropped quizzes. / 100
Total / 400
Your total number of points will be converted into a percentage and your grade will be determined by the following grading scale:
90-100% / 4.0 / 63-69.9% / 2.083-89.9% / 3.5 / 55-62.9% / 1.5
76-82.9% / 3.0 / 50-54.9% / 1.0
70-75.9% / 2.5 / 0-49.9% / 0.0
Policies:
Electronic devices:As a courtesy to your classmates and to limit disruptions during lectures or labs, ringtones of phones must be turned off during the class session. Students must not engage in talking on cell phones or text messaging in the classroom. Laptops should be turned off and stored unless authorized by the instructor. Use of computers or mobile devices for activities such as game playing, instant messaging, internet surfing, during class or recitations are prohibited.
Academic Honesty:The Department of Statistics and Probability adheres to the policies of academic honesty as specified in the General Student Regulations 1.0, Protection of Scholarships and Grades, and in the All-University of Integrity of Scholarship and Grades which are included in Spartan Life: Student handbook and Resource Guide. Student who plagiarize will receive a grade 0.0 in the course or the assignment.
Plagiarismat MSU is taken seriously: “no student shall claim or submit the academic work of another as one’s own.”
Honor Code: “Answers to quizzes, exams, and assignments are my own. I will not make solutions to quizzes, exams, and homework available to anyone else whether written by me or others.”
ADA: To arrange for accommodation a student should contact the Resource Center for People with Disabilities (353-9642).
Intellectual Property Rights: Students may not post course materials online or distribute them to anyone not enrolled in the class without the advance written permission of the course instructor.
Disclaimer: The instructor reserves the right to make any changes she considers academically advisable. Changes will be announced in class. It is your responsibility to keep up with any changed policies and assignments.
Emergencies:In the event of an emergency arising within the classroom the Instructor will notify you of what actions that may be required to ensure your safety. It is the responsibility of each student to understand the evacuation, “shelter-in-place,” and “secure-in-place” guidelines posted in each facility and to act in a safe manner. You are allowed to maintain cellular devices in a silent mode during this course, in order to receive emergency SMS text, phone or email messages distributed by the university. When anyone receives such a notification or observes an emergency situation, they should immediately bring it to the attention of the Instructor in a way that causes the least disruption. If an evacuation is ordered, please ensure that you do it in a safe manner and facilitate those around you that may not otherwise be able to safely leave. When these orders are given, you do have the right as a member of this community to follow that order. Also, if a shelter-in-place or secure-in-place is ordered, please seek areas of refuge that are safe depending on the emergency encountered and provide assistance if it is advisable to do so.
Suggested Exercises: We have tentatively selected some exercises from the textbook that illustrate ideas presented in class. If you encounter difficulty or are slow in solving problems, you should re-study the material, seek help, and do additional exercises to improve your mastery of the concepts and methods.The exercises with a * are to be handed in for grading as output from an R markdown file (format: Word, pdf, or html)Please make the documents self-contained (i.e. include text).Thepoints for each assignment are listed on LON CAPA under “Rstudio homework due in class”
1.2: 17, 19 (Rmd example)
1.3: 33, 35ab, 41, 38*
1.4: 45 (a. sample mean, b. sample standard deviation, d. sample standard deviation), 47, 57, 56* (boxplot and numerical data summaries), 59
2.1: 3, 4
2.2: 11, 15, 17, 21, 22
2.3: 35, 38*, 39
2.4: 47, 49, 53, 61, 60, 62
2.5: 71, 74, 77, 79
3.2: 12, 13, 16, 17, 23, 24
3.3: 29, 32, 35, 36, 39
3.4: 47 (d-g, with calculator), 49, 50, 55*, 60, 66
3.6 79 (with calculator), 81, 85, 86*
4.1: 1, 5, 7, 8,9
4.2: 11, 15, 17, 20
4.3: 29, 33, 34*,35, 37, 39, 40*, 43
4.4: 59, 60*, 61
4.5: 72, 73, 74
4.6: 87, 88*, 89
5.1: 1, 2, 3, 6
5.2: 22
5.4: 46, 47, 50, 51, 53
7.1: 3, 4*, 5, 7
7.2: 20, 21 (two-sided CI), 23
7.3: 33, 34 (two-sided CI and PI), 37 (ac), 38a
8.1: 3, 5, 6, 7
8.2: 19, 21, 23, 25, 29a, 32*
8.3: 37, 38a, 39
8.4: 47, 53, 55, 58
9.2: 19, 23*, 25, 27, 29
9.3: 37a*, 39, 40a, 41
9.4: 49, 51, 53a, 54
12.1: 1, 3, 7, 9
12.2: 15bc, 16,17, 18*, 19, 20
12.3: 31, 33, 35, 38*
12.4: 47, 54
12.5: 58, 59
13.1: 5,8
14.1: 3, 7
14.2: 16, 17
14.3: 25, 27, 28*
Class Begins
1/8/2018
Open adds end (8:00pm)
1/12/2018
Last day to drop with refund (8:00pm)
2/2/2018
Last day to drop with no grade reported (8:00pm)
2/28/2018
Class Ends
4/27/2018