Duke, Department of Statistical Science
Summer Term I 2015
It is easy to lie with statistics. It is hard to tell the truth without it.
Andrejs Dunkels
Sta 101: Data Analysis and Statistical Inference
Classroom:
Time:
Website:
Perkins LINK 071 (Classroom 5)
Monday thru Friday: 12:30 AM-1:45 PM
https:// stat.duke.edu/ ∼nmd16/ courses/ Summer15/ sta101.001-1/
Labs:
Time:
Old Chemistry 101
Tuesday, Wednesday, Thursday 02:00 PM-03:00 PM
Professor:
Office:
Email:
Nicole Dalzell
Old Chemistry 114
nmd16@stat.duke.edu
In the subject line of any email, include STA 101, your last name and brief phrase
describing the subject of the email. Example: STA 101 Dalzell Lab 1.
Monday through Friday, I will respond to email from 8 AM to 8 PM; messages
received after 8 PM will be answered the following day. On Saturday and Sunday
you may expect a response to emails by Sunday evening. Please try to keep email
messages brief and ask more in depth questions during class or office hours so that
others may benefit from the response.
Required materials:
Textbook
OpenIntro Statistics, Diez, Barr, Çetinkaya-Rundel
CreateSpace, 2nd Edition, 2012, ISBN: 1478217200
PDF available for free at http:// www.openintro.org or paperback copy on Amazon.
Calculator
Office hours:
Instructor
Exams:
You will need a four function calculator that can do square roots for this class. There
is no limitation on the type of calculator you can use.
Tentative: Monday 2:30pm - 3:30pm
Tentative: Wednesday 10am- 11am
I am also available by appointment. You are highly encouraged to stop by with any
questions or comments about the class, or just to say hi and introduce yourself.
Midterm 1: Monday, June 1
Project: Thursday, June 17
Final: Wednesday, June 24, 9:00am - 12:00pm
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Special Note for Lectures, Labs and Office Hours:
Perfume, cologne, scented lotion, body sprays and all other scented products may not be
worn to or applied during any meetings for this class. It is also important that you not
smoke immediately before any course meetings. I have severe asthma and cannot breathe
in the presence of these products. Please note that I will be unable to work with you in
lecture, lab or office hours if you are wearing a scented product. Feel free to email me with
any questions.
Course goals & objectives:
The overall goal of this course is to introduce you to the discipline of statistics as a science of understanding
and analyzing data and not as a branch of mathematics. The course is designed to provide you with the
tools you need for solving real world problems using statistics and a better understanding of the process
of scientific research and statistical inference.
By the end of this class you should be able to interpret statistical results in context and critique news
stories and journal articles that include statistical information. We expect you to be comfortable with
concepts such as association and causation, random sampling and random assignment, statistical bias and
statistical significance, and to understand and appreciate why real data beats anecdotes.
We plan to achieve these goals by introducing you to the relevant statistical knowledge, teaching you how
to use an open source (i.e. free!) statistical software called RStudio to perform data analysis, and having you engage in problem solving, application, analysis, and synthesis of statistical information through
homework, labs, quizzes and exams.
Tips for success:
1. Read the relevant sections before a new week begins, and then review again after the lectures.
2. Be an active participant during lectures and labs.
3. Ask questions - during class or office hours, or by email. Ask me and/or your classmates.
4. Do the homework - start early and make sure you attempt and understand all questions.
5. Start your project early and allow adequate time for working on it.
6. Give yourself plenty of time time to prepare a good cheat sheet for exams. This requires going
through the material and taking the time to review the concepts that you’re not comfortable with.
7. Do not procrastinate - don’t let a class go by with unanswered questions as it will just make the
following day’s material more difficult to follow.
Grading:
Your final grade will be comprised of the following.
Labs
Problem Sets
In Class Participation/ Activities
Pop Quizzes
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10%
15%
5%
5%
Project
Midterm
Final Exam
20%
20%
25%
Work load:
This is an accelerated summer course, and the material will move quickly.
• Problem Sets are due in class by 12:30 AM on the due date
• Labs Due on Sakai by 5 PM on the due date
See the schedule on the course website for exact due dates.
Late Work Policy
• If an assignment is turned in:
– late but during class: lose 10% of points
– next day: lose 40% of points
– after class on due date: lose 20% of points
– later than next day: lose all points
• There will not be make-ups for any of the problem sets, labs or exams.
• All regrade requests on homework assignments, labs and exams must be discussed with the professor
within one week of receiving your grade. There will be no grade changes after the final exam.
Lectures:
Lecture slides will be posted the day of the lecture. Note that these slides are not intended to be exhaustive and will be a poor substitute for taking your own notes during the course of the lectures. My
expectation is that students should attempt the assigned readings before class so that they are not seeing
the material for the first time in lecture. You are responsible for all the material covered in lecture as well
as in the text and homeworks. Please ask questions in class, office-hours or by e-mail if you are struggling
(or just curious), do not wait until just before an exam when it may be too late.
Participation:
We will move very quickly in this course, and it is your responsibility to come to class. Activities and
group work conducted in class are essential for success in this course. Accordingly, there is a participation
component of your final grade which reflects your involvement in course activities. To earn your points,
you must
• Answer all participation questions during the course lecture
• Participate in group activities during the course lecture
• Participate actively in class and group discussion during lecture and lab
I realize that occasionally you may be late or need to miss class. Up to two unexcused late arrivals or
absences will not affect your participation grade. I ask that you email me in advance if you need to miss
class.
Quizzes:
Quizzes will be unannounced, and given as needed. Quizzes will be short and mainly conceptual, normally
based on material learned in the previous class.
Labs:
The objectives of the labs are to teach you how to do data analysis using a statistical software and to give
you hands on experience with the topics we cover in lecture. The labs will also provide you with tools you
will need for the project. We will use a statistical analysis package called RStudio, which is really a front
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end for a statistical language called R. You can use RStudio on any computer with a browser, Mac or
PC. To log on to RStudio, follow the link here and enter your Net ID and password, and choose RStudio.
You will work in partners for each lab session. One lab report should be turned in for the pair, and each
lab session you and partner should switch who authors the lab reports. Each lab contains a series of questions which must be answered and turned in on Sakai. A list of the lab partners groups may be found here.
Problem Sets:
These will be comprised of problems from the book. Each assignment will list a number of problems from
the book to be turned in for grading, and a few problems for practice. You do not need to turn in the
practice problems, and the solutions for those are at the back of the book.
The objective of the homework assignments is to help you develop a more in-depth understanding of the
material covered in the lectures and help you prepare for exams and the project. Grading will be based
on completeness as well as accuracy. In order to receive credit you must show all your work. The lowest
homework score will be dropped.
You are welcomed, and encouraged, to work with each other on the homework problems, but you must
turn in your own work. If you copy someone else’s work, both parties will receive a 0 for the homework
grade as well as being reported to the Office of Student Conduct.
If you work with someone else on the homework, you must write the name of your collaborator(s) on your
homework, ie ”Collborators: Jane Smith, John Doe”.
Your homework must be stapled, legible, and contain your name. It is due at the beginning of class on
the due date (see late work policy above). If I have problems reading your work, I may require that
the Problem Sets be typed and printed rather than handwritten. If you cannot make it to class the day
homework is due, please email me to make arrangements to drop off your homework earlier.
Project:
The Project will be done individually. For a parameter of interest to you, you will describe the relevant
data, compute a confidence interval and conduct a hypothesis test and summarize your findings in a
report up to 5 pages (double spaced) in length. More details on the project will be given as the class
progresses.
Exams:
The midterm is on Monday, June 1. The Final Exam is a comprehensive 3 hour exam that will be
administered on Wednesday, June 24 from 9am - 12pm. You must take the final exam in order to pass
this class. Exam dates cannot be changed. No make-up exams will be given. If you cannot take the
exams on these dates you should drop this class.
You are allowed to bring one sheet of notes (“cheat sheet”) to the midterm and the final. This sheet must
be no larger than 8 12 ” × 11”, and must be prepared by you. You may use both sides of the sheet.
Disability Statement Policy
Students with disabilities who believe that they may need accommodations in the class are encouraged
to contact the Office of Services for Students with Disabilities at 684-5917 or disabilities@aas.duke.edu as
soon as possible to better ensure that such accommodations are implemented in a timely fashion. Please
feel free to contact me, and I will be happy to discuss any necessary accommodations.
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Academic integrity:
Duke University is a community dedicated to scholarship, leadership, and service and to the principles
of honesty, fairness, respect, and accountability. Citizens of this community commit to reflect upon and
uphold these principles in all academic and non-academic endeavors, and to protect and promote a culture
of integrity. Cheating on exams and quizzes, plagiarism on homework assignments and projects, lying
about an illness or absence and other forms of academic dishonesty are a breach of trust with classmates
and faculty, violate the Duke Community Standard , and will not be tolerated. Such incidences will
result in a 0 grade for all parties involved as well as being reported to the Office of Student Conduct.
Additionally, there may be penalties to your final class grade.
Please review the Academic Dishonesty policies at http:// www.studentaffairs.duke.edu/ conduct/ resources/
academicdishonesty.
Excused Absences:
Students who miss tests due to a scheduled varsity trip, religious holiday or short-term illness should fill
out an online NOVAP , RHoliday or short-term illness form respectively and will be given the grade of
their Final Exam for those tests. Those with a personal emergency or bereavement should seek a Dean’s
Excuse; check with your academic dean for details.
Green Classroom:
This course has achieved Duke’s Green Classroom Certification. The certification indicates that the faculty
member teaching this course has taken significant steps to green the delivery of this course. Your faculty
member has completed a checklist indicating their common practices in areas of this course that have
an environmental impact, such as paper and energy consumption. Some common practices implemented
by faculty to reduce the environmental impact of their course include allowing electronic submission of
assignments, providing online readings and turning off lights and electronics in the classroom when they are
not in use. The eco-friendly aspects of course delivery may vary by faculty, by course and throughout the
semester. Learn more at http://sustainability.duke.edu/action/certifications/classroom/index.php.
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