Spring 2016 – SYLLABUS

Michigan State University

STT 200: Statistical Methods

Time and Place: / Sections 1-8:
MWF 11:30 AM - 12:20 PM, 103 Erickson Hall
Sections 21-26:
MWF 1:50-2:40 PM, B117 Wells Hall
Instructor: / Dr. Marianne Huebner (“Dr. H”)
Office: / C-422 Wells Hall
Phone: / (517) 432 3385 (email preferred)
Email: /
Office Hours: / MW 12:30-1:30pm and by appointment
Online Discussion Forum: / https://piazza.com/msu/spring2016/stt200 (preferred method of contact for course related questions)
Prerequisites: / MTH 103 or appropriate score on math placement test
Course Web page / http://msu.lon-capa.org

Recitations

Teaching Assistants (TA):

Section / Time Tuesday / Location / TA
Lecture MWF 11:30 AM - 12:20 PM, 103 Erickson
1 / 9:10-10:00 / A122 WH / Kaixu Yang
2 / 10:20-11:10 / A116 WH / Atreyee Majumder
3 / 11:30-12:20 / 2243 Eng / Jeonghwa Lee
4 / 12:40-1:30 / A234 WH / Kaixu Yang
5 / 11:30-12:20 / A322 WH / Kaixu Yang
6 / 12:40-1:30 / A218 WH / Scott Manski
7 / 1:50-2:40 / A322 WH / Scott Manski
8 / 3:00-3:50 / A222 WH / Scott Manski
Lecture MWF 1:50-2:40 PM, B117 Wells Hall
21 / 11:30-12:20 / A326 WH / Shawn Santo
22 / 9:10-10:00 / A201 WH / Jeonghwa Lee
23 / 12:40-1:30 / A224 WH / Chitrak Banerjee
24 / 1:50-2:40 / A234 WH / Jeonghwa Lee
25 / 9:10-10:00 / A218 WH / Atreyee Majumder
26 / 11:30-12:20 / A316 WH / Chitrak Banerjee

Course description: Data analysis, probability models, random variables, estimation, tests of hypotheses, confidence intervals, and simple linear regression.

Requirements:

Text (required): DeVeaux, Velleman, and Bock (2011). Intro Stats [3rd ed], Pearson ed, Inc, Addison-Wesley 2009. Homework problems refer to this edition.

Calculator (required): TI-84. This calculator has statistical functions that save you a lot of work in the assignments and exams. Explanations on using the statistical functions for the TI-84 will be provided in class. Otherwise the calculator policy is the same as for the ACT http://www.actstudent.org/faq/answers/calculator.html.

Online Forum (required): https://piazza.com/msu/spring2016/stt200/): This is the forum where class announcements such as exam coverage or deadline will be posted. You can ask questions on Piazza anytime. Other 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 compliant and 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 10 points extra credit.

LON CAPA (required): http://msu.lon-capa.org): 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.

Statistical Computing (required): 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. Computational projects and some quiz questions will use Rstudio and example code will be provided. R is open source and runs on UNIX, Windows, or Mac. To download go to http://www.r-project.org. It is maintained by the R core development team, an international team. 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 https://www.rstudio.com/. However you need to install R first. The use of R/Rstudio will be demonstrated in class to which you can bring your laptop with R/Rstudio installed.

Clickers (optional): To assess comprehension and participation during lectures questions will be given requiring your use of I-clickers. You can bring your I-clicker to the lectures for assessing knowledge to see what needs further discussions. You can register your I-clicker at http://www.iclicker.com/registration/. I-clicker Go is enabled (for voting with your cell phone), but there have been technical problems in the past.

Bring to every class: Calculator (for sure) and i-clicker (if you have one). If you like, you can print out the lecture slides to take notes on (posted on LonCapa).

Attendance: You are expected to attend all meetings of the class. If you miss a class for whatever reason, you are responsible for all you missed. If you miss a class, it is difficult to study on your own and you can be lost quickly. Lecture notes are posted on LON CAPA. Some instructional videos posted on MSU Media space carefully explain and work through additional examples. A visit to Dr. H’s office hours can be of great help and can save you a lot of time understanding the relevant points. J

Lecture: The lectures are used to present basic ideas. STT 200 is an introductory statistics course with practical and commonly encountered statistical concepts and methods. The textbook will be followed fairly closely.

There will be some videos on MSU media space to work through examples for further practice and explanations.

Types of data (chapter 2)

Categorical data (chapter 3), omit pie charts

Quantitative data (chapter 4, use TI-84), omit stem-and-leaf plots

Comparing distributions, boxplots (chapter 5, use TI-84)

Normal probability distribution (chapter 6, use TI-84), omit table of z-scores (“by hand”), omit normal probability plot

Linear regression (chapters 7, 8, 9, use TI-84)

Gathering data (chapters 11, 12, 13)

Probability (chapters 14, 15)

Random variables (chapter 16), omit correlation

Binomial random variables (chapter 17), omit geometric, Poisson

Sampling distributions (chapter 18)

Confidence intervals for proportions (chapter 19, use TI-84)

Hypothesis tests for proportions (chapter 20, 21, use TI-84)

Comparing two proportions (chapter 22, use TI-84)

Confidence intervals and hypothesis tests for means (chapter 23, use TI-84)

Comparing means (chapter 24, 25, use TI 84)

EXAM INFORMATION

Unit Exam 1: Wednesday, February 3

Unit Exam 2: Wednesday, March 2

Unit Exam 3: Wednesday, April 6

Final Exam for sections 1-8:

Thursday, May 5 2016. 10:00am - 12:00pm in 103 Erickson Hall

Final Exam for sections 21-26:

Monday, May 2 2016. 3:00pm - 5:00pm in B117 Wells Hall

Exam procedure: On the day of the exam, you need to wait outside the classroom and show your ID to receive your exam copy with an ASSIGNED seat. Check-in starts 5 minutes before class time. At the end of the exam, make sure you have filled in your name, ID, and exam number on the scantron form and hand in the exam copy and form before you leave the room.

Note: You have to take the exam in the lecture you are registered for, since the exams will be different, there are assigned seats, and there are no extra seats in the respective rooms. You will get a zero on an exam that is not for your section.

You cannot miss the final exam.

You cannot miss more than one of the three unit exams to pass the course.

If you miss one unit exam (MSU sponsored trip, illness, other reasons), you can take the comprehensive make-up exam during the last week of classes covering the whole semester provided that you have taken and passed the other exams, and you contact the instructor on or before the day of the exam to arrange a conference.

Comprehensive make-up exam on Friday, April 29, 2016

Please meet with Dr. H during the first two weeks on the semester, if you already know you will miss some classes or an exam due to an MSU sponsored trip. It takes careful pre-planning, so you won’t get lost with the missed material.

Other useful information:

Help Room: Statistics Help Room C100 Wells Hall is staffed for certain hours of the week with teaching assistants to give walk-in help. See Help Room schedule posted on www.stt.msu.edu .

The Khan Academy offers a series of YouTube videos on probability and statistics: http://www.khanacademy.org/math/probability

Google helpouts for private online video tutorials. https://helpouts.google.com. Some are free.

DataCamp offers a free, interactive introduction to R: https://www.datacamp.com/courses/introduction-to-r

Grading:

Quizzes are online and will be given most Fridays. Every student will get a different version. Due to randomly generated numbers errors can occur. If you believe your answer is correct and the computer’s answer is not, please contact the instructor. All your choices and time of entry are recorded in the system. The points vary depending on the number of questions and there are no make-up quizzes. There are no drops. You have 24 hours to complete a quiz, but there are limits on the number of times you can change an answer. Some of the quizzes require computation using R. The quiz questions are similar to what you might expect on the exams.

Exams are closed books and closed notes, but hand calculators are permitted (see calculator policy). Exams are worth 50 points each, 2 points per question. There will be three in-class exams during the course of the semester and a final exam. The exams will contain questions concerning text material and problems, classroom examples and discussions, and the output of a statistical software package.

Exam rules: Bring a picture ID! During exams, cell phones are to be turned 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.

Results: Feedback on online quizzes are immediate upon submission (right-wrong). Answers can be discussed during recitation in the following week. Exam results will be sent by the scoring office. So it is important to have your correct name and student ID on the scantron form. If you do not receive such an email, you need to check with Dr. H.

Grading scale:

Source / Maximum Points
Lecture exams (3) / 150
Online Quizzes (Standardized to 80 points total. No dropped quizzes.) / 80
Computational projects with R (2) / 20
Final exam / 50
Total / 300

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 / 65-72.9% / 2.0
85-89.9% / 3.5 / 60-64.9% / 1.5
79-84.9% / 3.0 / 55-59.9% / 1.0
73-78.9% / 2.5 / 0-54.9% / 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.

Plagiarism at 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). http://www.rcpd.msu.edu

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.

STT200-001
SPRING SEM 2016
1/11/2016 Class Begins
1/15/2016 Open adds end (8:00pm)
2/5/2016 Last day to drop with refund (8:00pm)
3/2/2016 Last day to drop with no grade reported (8:00pm)
5/6/2016 Class Ends

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. Some of these exercises will be discussed during your recitations.

Chapter 2: 1-4, 7-11, 18-21, 28-29

Chapter 3: 1, 3, 7-10, 13-16, 25, 29, 35-38

Chapter 4: 3, 7-10, 13, 14, 23-26, 31, 32

Chapter 5: 5, 6, 9, 10, 21, 22, 29-32, 37

Chapter 6: 15, 16, 27, 28, 39-48, 51-54