Statistics 101: Spring 2011
Data Analysis and Statistical Inference

Syllabus, grading policies, office hours, and general information

Course Objectives



The primary text is:

Freedman, D., Pisani, R., and Purves, R. (2007). Statistics (fourth edition).  W. W. Norton & Company, Inc.


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.

Graded work

Graded work for the course will consist of problem sets, lab work, a final project, two midterms, and a final exam. Your final grade will be determined as follows:
Final exam 25 %
Midterm exam 1
15 %
Midterm exam 2
15 %
In-class problems
15 %
Lab work
10 %
Final project
10 %
Homework problems  10 %

There are no make-ups for exams, labs, or homework problems, except for a medical or familial emergency or previous approval of the instructor.  See the instructor in advance of relevant due dates to discuss possible alternatives.

Descriptions of graded work

Homework  problems:

Homework problems will be posted on the Stat 101 course web site and on Blackboard.   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.  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 submit your anwers individually.  When you submit your answers to Blackboard, you will get a confirmation that you have submitted them and the answers will be revealed.  Typically, we will briefly go over solutions to the Blackboard problems at the start of lecture of the day they are due.

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.

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.

In-class problems:

We will have an in-class problem set every week. These will consist of two 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. Each in-class problem set will be worth four points. You will recieve two points for simply turning in some answers. The other two points will come from correctly answering the questions. The two problems will be graded using an all or nothing scheme.

The dates of in-class problems will be announced as the semester progresses.    Roughly, you can expect one problem set per week.  If you miss an in-class problem set because you were not in class, it counts as a zero (absolutely no exceptions so please don't ask). However, I understand that planned and unplanned things come up during the course of a semester. To accommodate these situations in a flexible manner the two worst in-class problem scores will be dropped

Lab assignments:

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. Typically, there should be plenty of time to complete and turn in lab reports during lab. That said, there will be a couple of labs that may require more time to complete. For these, the lab report must be emailed to your lab instructor the day of the lab session.   Missed lab assignments cannot be made up unless pre-approved by the instructor (not the TAs).  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; we need the space).   

Final Project:

Web link to instructions for the final data anlaysis project that will be due towards the end of the semester.


We will have two midterm exams and a final. The tentative dates and topics covered for each are

Some advice for success in Statistics 101


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!

Academic honesty

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.