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
Instructor:
Office:
Phone:
Email:
Office Hours:
Online Discussion
Forum:
Sections 21-26:
MWF 1:50-2:40 PM, B117 Wells Hall
Dr. Marianne Huebner (“Dr. H”)
C-422 Wells Hall
(517) 432 3385 (email preferred)
huebner@msu.edu
MW 12:30-1:30pm and by appointment
https://piazza.com/msu/spring2016/stt200 (preferred
method of contact for course related questions)
Prerequisites:
Course Web page
MTH 103 or appropriate score on math placement test
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. 
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
Lecture exams (3)
Online Quizzes (Standardized to 80
points total. No dropped quizzes.)
Computational projects with R (2)
Final exam
Total
Maximum Points
150
80
20
50
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%
85-89.9%
79-84.9%
73-78.9%
Policies:
4.0
3.5
3.0
2.5
65-72.9%
60-64.9%
55-59.9%
0-54.9%
2.0
1.5
1.0
0.0
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.
STT 200 - 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
Chapter 7: 3-6, 11, 12, 15-18, 27, 28, 37-39
Chapter 8: 1, 3, 5, 11-18, 23, 24, 29-30, 39-40, 55-56
Chapter 9: 1, 2, 5, 6, 11, 12
Chapter 10: skip
Chapter 11: 1, 2, 19-20 (optional)
Chapter 12: 5-10, 25, 26, 39, 40
Chapter 13: 7-14, 37, 38, 49, 52
Chapter 14: 1, 2, 15, 16, 19-21, 31-35
Chapter 15: 1-4, 9, 10, 13, 14, 21, 22, 31, 32, 42, 45
Chapter 16: 1-4, 7-10, 17-20
Chapter 17: 23-34
Chapter 18: 11-14, 22-26, 29, 30, 37-30, 47, 48
Chapter 19: 1-3, 5, 7, 13-15, 17, 18, 25, 26, 30
Chapter 20: 1-3, 11-16, 19, 20, 23, 28
Chapter 21: 1-4, 13, 17-23
Chapter 22: 7-12, 15, 16, 19, 20, 29-32, 38
Chapter 23: 1, 2, 7-10, 17-22, 27, 28, 31-34, 37, 38
Chapter 24: 1, 2, 7, 8, 11-14, 21, 23, 31, 32, 35, 36, 42
Chapter 25: 5, 6, 7, 23, 25