101: Spring 2011
Data Analysis and Statistical Inference
Syllabus, grading policies, office hours, and general information
Instructor: Elizabeth Mannshardt-Shamseldin, 216 Old Chem, (919) 681-8443, email@example.com
Lecture Times and Location: Tues/Thurs, 11:40AM-12:55PM, in LSRC B101.
Lab Times and Location: Mon. 10:20-11:10AM, 11:55AM-12:45PM, 1:30-2:20PM, 3:05-3:55PM. All in 01 Old Chem.
Instructor's Office Hours: Tuesday, 1-2:30PM Other hours available by appointment.
Teaching Assistants: Amy Oh (firstname.lastname@example.org), Loretta Bu (email@example.com), Yue Jiang (firstname.lastname@example.org);
TAs' Office Hours: All TA office hours are held in the Statistical Education and Consulting Center in Old Chem 211A. You can attend any of the office hours held in the Center and TAs can answer questions about Statistics 101. The schedule of office hours is found at the SECC home page.
To understand and be able to interpret basic statistical analyses used in research and in the media.
To learn how to perform exploratory data analysis on a data set.
To learn how to estimate population means, percentages, and regression line slopes while accounting for chance error.
To understand the role of study design in statistical conclusions.
The primary text is: Freedman, D., Pisani, R., and Purves, R. (2007). Statistics (fourth edition). W. W. Norton & Company, Inc.
Graded work for the course will consist of problem sets, quizzes, lab work, a final project, two midterms, and a final exam. Your final grade will be determined as follows:
Midterm exam 1
Midterm exam 2
In-class Quizzes and Problems
Missed Work Policy
Make-ups are not given for missed work except for the final exam. Your final exam grade is substituted for missed work that is excused by the instructor, not the TA, prior to the absence. If the absence is not priorly excused, the final exam score will be substituted only in the case of a qualifying excused absence, such as stated under the Dean's Short-Term Illness specifications. A grade of zero will be incurred for all other missed work.
We will use the statistical software package JMP in labs and for the final project. You can download JMP on to your personal computer for free from the OIT software web site. It is also available on all public PCs across campus.
You need a basic calculator. You don't need to purchase a calculator that can do graphing or has statistical functions. You will not be allowed to use your phone or computer's calculator for closed-book quizzes or exams. You will not be permitted to share calculators during closed-book quizzes or exams.
Descriptions of graded work
We will have two midterm exams and a final. The dates are finalized, barring a university-wide need to re-schedule, ie extreme weather, etc.
Midterm Exam 1: Tuesday, Feb 22nd
Midterm Exam 2: Thursday, Mar 31st
Final Exam: Tuesday, May 3rd; 9am-12pm Regular Classroom.
Homework problems will be posted on Blackboard and/or the Stat 101 course web site. During the semester there will be two types of homework problem sets. The majority will require you to submit answers direclty in Blackboard. For these types of homework assignments no work needs to be turned into the instructor. The second type of homework assignments will require you to turn in answers to the instructor. Due dates will be established as the semester progresses, but will always fall on days for which we have lecture or lab. Homeworks are due the beginning of class on the due date. If a homework assignment is not turned in by the beginning of class it will not be graded and will count as a zero. You are permitted to work with others on the problems but must prepare your own solutions and submit your anwers individually.
The homework problems include questions on material covered in previous lectures. These usually are problems from the text book or problems composed by the instructor. They also may include questions on the readings assigned for the upcoming class. These questions have two primary functions: 1) they allow you to practice essential statistical skills; and, 2) they reward you with grading points for keeping your reading current. Keeping your reading current is essential for getting the most out of lectures, because we use material from the assigned pages when discussing examples and concepts. The instructor will present lectures assuming that you have read the material for that class.
When you submit your answers to Blackboard, you will get a confirmation that you have submitted them but not reveal answers. Questions about homework grading should be directed first to the TA for your lab section.
I suggest that you keep paper copies of your work. That way, you can show your work to the professor or TAs to review and correct any mistakes that you may have made. Additionally, the copies will be useful for studying for exams.
Students are encouraged to make use of the SECC for help with homework. However, the SECC tutors and TA's cannot directly provide solutions, and should not be asked to do so. Additionally, please make use of the homework forum on Blackboard to discuss concepts and methods for the homework problems. It can be difficult and time-consuming for the TA's to answer individual questions on every homework assignment from every student. The issue that you are having may already have been addressed on the forum, or you are welcome to start a discussion with your classmates. TA's and the instructor may post tips and clarifications here as well.
We will have 3 in-class closed-book quizzes. These will consist of problems dealing with material covered in class. They will provide students an incentive to keep up with the material and provide feedback to the instructor. Quizzes will be announced at least one lecture in advance.
We will have 2-6 in-class problem sets. These will consist of problems covering material from previous lectures. The problems are similar in spirit to the Exercises and Review Problems in the text book and other problems posted by the instructor. The in-class problems provide a measuring stick for what you know and do not know before the exams. They also reward you for doing practice problems in the text and understanding the material.
The dates of in-class problems may be announced ahead of time. However, I reserve the right to administer unannounced in-class problems during the course of the semester. If you miss an in-class problem set because you were not in class, it counts as a zero, and the course policy on missed work applies. However, I understand that unexpected things come up during the course of a semester. To handle these situations in a flexible manner the worst in-class problem score will be dropped
Each week, there are weekly data analysis problems completed in lab. Labs provide hands on experience analyzing data under the guidance of the TAs. The labs teach you how to apply the skills discussed in lectures and readings.
You are graded on lab reports that must be turned in. Lab attendance is mandatory. Labs are designed to be completed in the one hour lab period and are to be turned in at the end of each lab section. However, if you have an excused absence (cleared with the TA) or have worked on the lab during the scheduled lab period but have been uable to complete it, you may turn the completed assignment in on the Monday after the section. If you need additional time, have the TA sign off on the lab at the end of the lab period in order to receive credit. Late lab reports will not be accepted. Missed lab assignments are given a zero and the course policy on missed work applies. Questions about lab grading should be directed first to the TA for your lab section.
Labs should be completed in your assigned lab section, unless you are given permission by the instructor or TAs to complete the lab in another section. This is necessary because space in the labs is at a premium. You are permitted to begin the lab before it is due (although not in 01 Old Chem on Thursdays during the other section of Sta101; we need the space). Students may only come to a different lab time on a particular day where they have an excused absence and they have cleared which section they will be attending with the appropriate TA's in advance. It is not permitted to sign up for one lab section but attend another.
A final project will be due at the end of the semester. This will provide an opportunity for hands-on analysis, implementing the ideas and skills learned in the course.
Final Project Due: Thursday, Apr 21 in class
Other important dates:
Add/Drop Date: Wed, Jan 26th
Spring Break: Monday, Mar 7th - Friday, Mar 11th
Withdrawal Date: Wednesday, Mar 30th
Some advice for success in Statistics 101
DO AS MANY PROBLEMS FROM THE TEXT BOOK AS POSSIBLE!!!
The best way to learn statistics, or any quantitative subject, is to work problems on a consistent schedule. The homeworks and in-class problems provide a structured mechanism for doing so. I recommend starting the problems at least two days before they are due, so that you have sufficient time to come to office hours with questions. For particularly difficult concepts, I recommend working problems beyond those assigned, so that you get additional practice. Then, visit your instructor and TAs to review answers.
Most sections in the text are followed by a set of exercises. I recommend working two or three of these problems as you are reading. This allows you to gauge what you did and did not understand on first reading. so that you can re-read if necessary. After reading, go back and do a good chunk of the remaining exercises. There are review problems at the end of most chapters. I recommend working a few problems each week from previous review exercises to maintain and solidify your understanding. Answers to the exercises are in the back of the book, and you can check with the TAs in the Statistical Education Center about answers to review problems.
To maximize your chances of success in Statistics 101, I recommend that you spend at least 6 hours per week outside of the classroom working on problems. I recommend setting up a realistic study schedule in which you spread your work over the week. Leaving all your statistics studying to one night is a sub-optimal strategy, because you won't spend enough time to develop a thorough understanding of the material. There are some useful handouts describing strategies for studying for quantitative courses on the web site for Duke's Academic Skills Instructional Program (at the site, select "Math and Quantitative Studies"). It's packed with good tips, especially for those who don't have much experience studying for quantitative courses at Duke.
I strongly encourage you to form a study group and work problems together. Evidence shows that students who work in groups in quantitative courses learn more and enjoy the course more than those who work alone (see the studies by Richard Light at Harvard University).
Finally, visit the TAs and instructor when you get stuck or even
when you figure something out and want to share your victory.
Almost everyone who does well in this course asks for help at some
point in the semester. Think of us as allies in your efforts to
learn statistics. Nothing makes us happier than you
understanding all the material!
You are expected to abide by Duke's Community Standard for all work for this course. Violations of the Standard will result in a failing grade for this courses and will be reported to the Dean of Students for adjudication. Ignorance of what constitutes academic dishonesty is not a justifiable excuse for violations.
For the homework problems, you may work with a study group with
others but must submit your own answers on Blackboard. For
in-class problems and exams, you are required to work alone and for
only the specified time period. For labs, you are allowed and
encouraged to help each other, but each person must complete the lab
independently and turn in his or her own written report.
On the final project, you work and submit results in groups.
Procedures if you suspect your work has been graded incorrectly
Every effort will be made to mark your work accurately. You should be credited with all the points you've worked hard to earn! However, sometimes grading mistakes happen. If you believe that an error has been made on an in-class problem or exam, return the paper to the instructor immediately, stating your claim in writing.
The following claims will be considered for re-grading:
(i) points are not totaled correctly;
(ii) the grader did not see a correct answer that is on your paper;
(iii) your answer is the same as the correct answer, but in a different form (e.g., you wrote a correct answer as 1/3 and the grader was looking for .333);
(iv) your answer to a free response question is essentially correct but stated slightly differently than the grader's interpretation.
The following claims will not be considered for re-grading:
(v) arguments about the number of points lost;
(vi) arguments about question wording.
Considering re-grades takes up valuable time and resources that TAs and the instructor would rather spend helping you understand material. Please be considerate and only bring claims of type (i), (ii), (iii), or (iv) to our attention.