An Introduction to
Statistical Methods and Analysis
TENTATIVE Course Syllabus--Fall 2007
An introduction to the concepts, techniques, and reasoning central to the understanding of data,
this lecture course focuses on the fundamental ideas of statistical analysis used to gain insight
into diverse areas of human interest. The use, abuse and misuse of statistics will be the central
focus of the course. Topics of exploration will include experimental study design, sampling
design, data analysis (visual devices, measures of center, measures of spread, normal
distributions, correlation and regression), sampling distributions and the Central Limit Theorem,
estimation (confidence intervals) and hypothesis testing (z-test, t-test, chi-square, ANOVA).
Applications will be drawn from current events, business, psychology, politics, medicine and
other areas of the life and social sciences. Statistical software will be introduced and used
extensively in this course, but no prior experience is assumed. An invaluable course for students
planning graduate study in the natural or social sciences. Open to any interested student—no
college level mathematical knowledge required.
Goal of Course: To learn the fundamentals of statistical analyses including data analysis,
study design, and basic inference.
Class Meeting: Lectures: Mondays/Thursdays, 11:05-12:30, Science Building 103
Group Conferences: Tuesdays, 9:00-9:50 or 10:00-10:50, Library E1
Attendance at lectures and group conferences is mandatory. Group
conference will be held weekly. Students will be assigned to one of the two
group conferences during the first week of class.
Instructor: Daniel King (You can call me anything reasonable, but I usually
respond best to the name 'Dan')
Phone: (914) 395-2424 (office phone with voice mail)
(646) 408-0715 (cell phone—please use it responsibly)
Office: 121 Alice Ilchman Science Building (first floor)
Required Text: Moore, David S., The Basic Practice of Statistics, Fourth Edition.
W. H. Freeman & Company Publishers, 2007. ISBN: 0-7167-7478-X
This mandatory text is available for purchase from the campus bookstore,
but you are welcome to purchase it through any vendor you choose.
However, purchase of the 4th edition is crucial—make sure to check the
ISBN number of the book you plan to buy and compare it to the one given
This is the main textbook and source of information for the course. We will
cover Chapters 1-11, 14-23, and 25-27. Additional reading of essays,
journal articles, newspaper clips is also required. These supplemental
documents will be provided to students in class.
Reserve Texts: Notx, William, Fligner, Michael, and Sorice, Rebecca L., Student Study
Guide for Moore's The Basic Practice of Statistics, Fourth Edition. W.H.
Freeman & Company Publishers, 2006.
This valuable study guide has been placed on reserve at the main desk of the
Raushenbush Library. Each section of this study guide begins with an
overview of the corresponding section in the main text. Most valuable is the
guided assistance provided on selected problems from the text. The authors
help students in the process of setting up and thinking about the problems.
After using the guided assistance, students can examine the complete
solutions which explain exactly how the answer was reached and why it was
done that way.
Course Readings: For each lecture meeting there will be an assigned reading from
the course textbook or from a supplemental handout. These readings will
form the basis of the course lectures. In advance of each lecture, students
are strongly encouraged to complete the associated reading. See ‘Course
Topics and Readings’ below for the schedule of readings. The ability to
read mathematics successfully (for deep understanding and long term
retention) is a skill that requires significant effort to develop. It is also a
skill that is often not developed in traditional high school courses. In this
course you will have much opportunity and will be given sufficient
guidance in developing your mathematical reading skills. Please consult
the ‘Suggestions for Effective Reading of Mathematics’ at the end of this
Course Exams: There will be three, 90-minute exams during the term. The coverage and
tentative dates for these exams are as follows:
Exam 1: Thursday, Oct 11—Data Analysis
Exam 2: Thursday, Nov 15—Study Design, Basics of Inference
Exam 3: Monday, Dec 17—Inference in Practice
Calculators: In this course we will focus less on tedious computations and more on the
understanding and proper interpretation of statistical calculations.
Nevertheless, a calculator with statistical capabilities is a valuable learning
tool. Access to a calculator with statistical functionality is required for this
course. The Texas Instruments TI-83 or TI-86 is recommended for this
course but any calculator with statistical functionality is acceptable. The
college owns a few of these calculators that can be borrowed by students.
You may already own a calculator that performs some statistical
calculations. See me if you need help using your calculator’s statistical
functions or need advice on purchasing a calculator for use in this course
Computers: We will be using the Microsoft Excel spreadsheet program in this course to
do some of our more complicated statistical calculations. Access to Excel
and instruction on its use will be provided in group conference. No prior
computer experience is required.
Conference Work: Group conferences will be held weekly. Time in group conference will be
spent in two ways: 1) reinforcing ideas presented in lecture through hands-
on activities conducted in workshop mode and 2) designing and executing a
small-scale research project in which students working in small teams will
be responsible for choosing a topic, designing an appropriate study,
collecting data, analyzing data and submitting a formal report of the results.
On the last day of lecture students will submit their final written report and
give a brief oral presentation of their findings in class.
Additional Help: I encourage students who are having difficulty with the course
material to meet with me for individualized help. Students are also
encouraged to develop and maintain an email dialogue with me so
that I may provide timely assistance with smaller-scale questions.
Students of this course can also access the free services of the
Mathematics Resource Center. More information about these
services will be discussed in class.
Evaluations: At the end of the semester an individual course evaluation and course grade
will be given to each student. This evaluation will be based primarily on the
results of the three course exams, quality of execution of the research project
and class attendance.
Worksheets: Completion of worksheets is optional in this course. Students wishing to
submit a worksheet should do so on the final day of class. Your worksheet
should detail the work completed in class and conference, listing topics
studied, research conducted, etc. Forms are available from the Office of
Student Records in Westlands.
Attendance: Both lecture and conference attendance is absolutely mandatory. Students
who miss more than two classes or conferences (without a documented
reason) run the risk of reduced course credit. Number of student absences
(or occurrences of significant tardiness) at lecture and group conferences
missed will be indicated on the course evaluation. If a session is missed, the
student is responsible for obtaining class notes and assignments and is
expected to be fully prepared for the next class session.
Course Topics and Readings
The following represents a tentative schedule of our activities during the semester and is subject to
revision. The readings listed under each lecture are best read in advance of the lecture.
Unit I: Data Analysis
Moore, BPS: Chapter 1—Picturing Distributions with Graphs
Moore, BPS: Chapter 2—Describing Distributions with Numbers (Part I)
Moore, BPS: Chapter 2—Describing Distributions with Numbers (Part II)
Moore, BPS: Chapter 3—The Normal Distributions
Moore, BPS: Chapter 27—Statistical Process Control (on CD or on-line)
Moore, BPS: Chapter 4—Scatterplots and Correlation
Moore, BPS: Chapter 5—Regression
Moore, BPS: Chapter 6—Two-Way Tables
Review: Topics in Data Analysis
Exam: Topics in Data Analysis (Tentative Date: Thursday, October 11)
Unit II: Study Design and the Basics of Inference
Moore, BPS: Chapter 8—Producing Data: Sampling
Moore, BPS: Chapter 9—Producing Data: Experiments
Moore, BPS: Chapter 10—Introducing Probability
Moore, BPS: Chapter 11—Sampling Distributions
Moore, BPS: Chapter 14—Confidence Intervals: The Basics
Moore, BPS: Chapter 15—Tests of Significance: The Basics
Moore, BPS: Chapter 16—Inference in Practice
Review: Topics in Study Design, Basics of Inference
Exam: Topics in Study Design, Basics of Inference (Tentative Date: Thursday, Nov. 15)
Unit III: Inference in Practice
Moore, BPS: Chapter 18—Inference about a Population Mean (t-test)
Moore, BPS: Chapter 19—Two-Sample Problems (Comparing Two Means)
Moore, BPS: Chapter 20—Inference about a Population Proportion (z-test)
Moore, BPS: Chapter 21—Comparing Two Proportions
Moore, BPS: Chapter 23—Two Categorical Variables: The Chi-Square Test
Moore, BPS: Chapter 25—One-Way Analysis of Variance: Comparing Several Means
Moore, BPS: Chapter 26—Nonparametric Tests (on cd or online)
Review: Topics in Inference in Practice
Exam: Topics in Inference in Practice (Tentative Date: Monday, Dec 17)
Student Research Study Presentations
Suggestions for Effective Reading of Mathematics
1. When confronted with the task of reading a piece of mathematical text, skim the
entire reading first to discern its general outline and to identify its main points
2. If necessary, review earlier portions of the textbook (or prior mathematical topics
studied) to recall forgotten or unfamiliar vocabulary, techniques or theorems
before attempting a thorough reading of the current text.
3. Don’t rush! Read slow! Mathematical writing is typically dense with ideas.
Spend as much time as necessary to understand the full intended meaning of each
of the author’s arguments and examples.
4. Pay particular attention to the precise statement of new definitions and theorems.
5. Do not immediately skip over a portion of the reading that doesn’t make sense in
the hope that its meaning will become more apparent later. Because of the linear
nature of mathematical writing in which one topic builds from those that precede
it, it is very important to fully understand one topic before proceeding to the next.
6. Try to identify the cause of any misunderstanding of the topics being studied.
Consider all reasonable methods to resolve the misunderstanding. Whenever
possible discuss difficult portions of the text with a friend, study partner, or study
7. If all else fails, make sure to mark any portions of the text that remain perplexing
so that you may raise these issues subsequently in class.
8. Occasionally authors will intentionally leave some details of arguments or
examples to the reader to complete as an exercises. Authors do this for
pedagogical reasons and not laziness! As a useful check on your understanding
of the material, always fill-in in the details omitted by the author.
9. Examples in textbooks often come with a moral. Discern the author’s main point
in providing the example. Make sure you struggle to understand every aspect of
the computation, manipulation, or procedure presented in the example.
10. Always keep pencil and paper handy whenever reading mathematical text. It can
be very helpful to highlight important passages, insert marginal notes to yourself
(ala Fermat!), and make simple calculations while involved in the reading of the