Introduction to Statistics II Fall 2010
Instructor: Maria Ripol
lectures: sec 7660, MWF 3rd
pd, TUR L007
sec 4433, MWF 4th pd, LIT 101
office: Griffin Floyd 117 C
phone: 392-1941 ext 217
office hours: Mon, Wed 6th and 7th periods (12:50 – 2:45 pm)
Tezcan Ozrazgat Baslanti Jorge
Griffin Floyd 209
office: Griffin Floyd 218
email: email@example.com email: firstname.lastname@example.org
office hours: Thu 1:30 – 4:30
pm office hours:
Tue 3:00 – 6:00 pm
Fri 1:30 – 3:30 pm
Wed 3:00 – 6:00 pm
Course Description and Objectives
In this course, students learn how to summarize data, analyze it, and make
appropriate decisions based on it. This course satisfies General Education
Credits in the Mathematical Sciences and is in the general category of M.
The sequence of courses STA 2023-3024 provides students with a firm
foundation in the basics of applied statistical methods. The prerequisite for
this course is STA 2023, which covered chapters 1-9 in the textbook (data
collection, graphical and numerical summaries, probability and an
introduction to statistical inference). Concepts from STA 2023 will be
reviewed as needed.
The course focuses on the following four topics:
1. Analysis of Variance to compare
three or more population means.
2. Inference for Regression, covering Simple Linear Regression and Multiple
3. Analysis of Two-Way Tables to study the relationship between two
4. Nonparametric Statistics that do not require a Normal distribution of the
Statistics: The Art and Science of Learning from Data, by Alan Agresti and Chris
Franklin, 2nd edition, Prentice Hall.
2. Scientific Calculator (around $10 to $15) that has some basic statistical
mean and standard deviation Graphing calculators are not allowed during the
Announcements for the course, and computer output to supplement the examples
done in class, will be linked from this page. Once the semester is underway,
there will also be instructions on that website that will direct you to
E-Learning, an integrated, password protected, web based classroom management
tool where you will be able to take the online quizzes, and check all your
grades. Note: The lectures for this class will NOT be available online.
Online Quizzes - There will be four online quizzes, administered through
E-Learning. You will have three tries for each quiz (with questions randomly
generated) over a period of approximately 4 days. Each quiz will be worth 10
points, for a total of 40 points. Hopefully these quizzes will serve the
purpose of improving your grade in the class, as well as be an important tool
in learning the material for the course. Quiz dates and details will be
announced in class.
Suggested Homework Problems will appear on the website. They will help
you master the material but will not be collected.
Projects - There will be two data analysis projects to be completed
during the semester. Each project will be worth 30 points, for a total of 60
points. Project dates and details will be given in class.
Exams - There
will be three exams given in class during the semester, each worth 100
points. All exams are in multiple choice format.
Students are required to take the exam in the section they are registered
for. All students must bring to the exam: their student ID number, picture
ID, a calculator, and pencils. In case of conflict or illness, if a student
is unable to take an exam at the scheduled time, they must get in touch with
the instructor immediately, for any arrangements to be made for a makeup.
Each case will be reviewed individually. Valid and detailed documentation is
a prerequisite under such extenuating circumstances. A grade of zero is the
minimum punishment of any type of dishonesty on an exam.
Exam 1 -
Wednesday, September 29th (in class) - Comparing Groups - Ch 10 and 14
Exam 2 - Wednesday, November 3rd (in class) - Regression - Ch 12 and 13
Exam 3 - Wednesday, December 8th (in class) - Chi Squared and
Nonparametric - Ch11 and 15
1 100 points
Exam 2 100 points
Exam 3 100 points
Projects 60 points
Quizzes 40 points
TOTAL 400 points
90% to 100%
A- 87% to 89%
B+ 84% to 86%
B 80% to 83%
B- 77% to 79%
C+ 74% to 76%
C 70% to 73%
C- 64% to 69%
D 60% to 63% (No
D+ or D- given)
E 59% and below
Email – will be answered within one working day in most cases. Please
be aware that statistical questions should be answered in person (in class or
during office hours) since they often require pictures and formulas that make
it very hard to communicate through email.
Attendance – although not required, is very highly recommended. This
class is NOT offered online. If you miss a class for any reason, it is your
responsibility to get a copy of the notes and all information given in class from
another student. Additionally, during class students should turn off their
cellular phones and refrain from eating, drinking, reading newspapers, doing
homework, listening to music and excessive talking.
designated “UF directory information” may be released without your written
consent. This applies to parents or anyone else who contacts me about your
Instructor's Honor Code - We the members of the University of Florida
community, pledge to hold ourselves and our peers to the highest standards of
honesty and integrity.
Academic Dishonesty - We adhere to the University of Florida rules and
guidelines for handling instances of academic dishonesty. Please refer to the
Office for Student Services for detailed information about the current
Grading – grades will be changed only when an error has been made.
Negotiation is not appropriate.
Incompletes are only assigned when extraordinary circumstances, arising after
the date for dropping the course, prevent the student from completing the
course requirements. Having a failing grade in the course is not a valid
reason for requesting an Incomplete.
Students with Disabilities - Students who require special accommodations
in class or during exams should follow the procedures outlined by the
Disability Resources Program (http://www.dso.ufl.edu/drp/) Please see the
instructor during office hours early in the semester, to discuss your
accommodation letter confidentially.