

Instructor: 
Roumen
Vesselinov, Ph.D.
Office: 200C
LeConte
Email: roumen@sc.edu
Office phone:
7775074
Meeting Times: MW
4:00PM 5:15PM, LC 210A
Office Hours: Mon
1:30pm3:30pm & Wed 2:30pm3:30pm
and
by
appointment.
Website: http://www.stat.sc.edu/~vesselin/stat700.html

Bulletin Description: 
STAT
700—Applied Statistics I (3).
Introduction to probability and the concepts of estimation and
hypothesis testing for use in experimental, social, and professional
sciences. One and twosample analyses, nonparametric tests, contingency
tables, sample surveys, simple linear regression, various statistical
packages including SAS.
Not to be used for M.S. or Ph.D. credit in statistics or mathematics. 
Purpose of Course: 
To
provide future scientists in these
fields with a base on which to
build a continually expanding array of methods for experimental design
and data analysis. Students will ideally come away with:
(1) an
understanding of basic probability and the manner in which all formal
statistical inference depends on it;
(2) the ability to carry out the
basic analyses listed in the description using widely available
software;
(3) a knowledge of the universal principles underlying all
hypothesis testing and interval estimation, thereby
facilitating
interactions with professional statisticians. 
Expectations: 
All
students
are expected to:
 Attend
class regularly, asking questions when clarification is needed and
participating in any inclass activities
 Read
the
material listed on the board before the next class meeting
 Attempt
all of the assigned homework problems and turn them in at the start of
the class in which they are due
 Use
the
resource of their fellow students and their instructor to seek answers
to questions that arise in class, in the readings, and on the homework

Required Text: 
Introduction
to the Practice of Statistics (5^{th}
edition),
by D.S. Moore and G.P. McCabe, W.H. Freeman and Co., 2006.
Additional materials
are on the course website.

Computers
and Calculators: 
This
course will use the software package SAS. You will have an account on
the CSM Windows domain. Currently the computers in LC 124, LC 303A
and PSC 102 have SAS. Student copies of SAS for home use are also
available for purchase from the university's computer service division.
NO PREVIOUS
KNOWLEDGE OF SAS IS ASSUMED.
SAS is the de facto standard statistical package in a number of
industries, and experience with SAS is a prerequisite for many jobs in
statistics and in fields that use statistics. While we will only
scratch the surface of SAS's capabilities, it should provide a useful
introduction into the more standard routines, and a jumping off point
for future experience with it.
Students can chose a different statistical package, e.g. SPSS, Minitab,
R, etc.
A basic calculator may be used on the exams.

Exams
and
Topics Covered: 
There
will be three exams and the final. The topics covered in the exams will
generally follow the chapters of the text listed above. However, the
exams may also cover material which was solely presented in class, and
that is not contained in the text.
The first exam will
be held in class on Monday, October 2. It will
focus on the subjects covered by this time:
graphical methods, measures of center and variability, basic rules of
probability, probability distributions, the binomial random variable
and counting rules, the normal distribution, and the normal
approximation of the binomial distribution.
The
second exam will be held in class on Monday, October 30. It will
focus on the material covered after Exam 1, including the central
limit theorem, sampling distributions, and estimation and inference for
one and two populations for means, variances, and proportions.
The
third exam will be held in class on Wednesday, November 29. It will
focus on the material covered after Exam 2, including oneway analysis
of variance and linear regression.
The
final exam will be held at 5:30pm on Wednesday, December 13 in BA 210A. It will be
cumulative, covering both the material from the previous three exams
and the material on contingency tables.
Make up exams will be given only in extreme circumstances, and only
when accompanied by appropriate documentation.
Incidence
of cheating and academic dishonesty will be punished to the full extent
allowed by university regulations. 
Homework and Project: 
Homework
is due at the beginning of the class period it was assigned
for.
Late homework is not accepted.
Homework
will be assigned at least one week in advance in class, and will also
be posted on the class website. If the homework is on a handout, that
handout will be available in class and during office hours.
The writing on the homework must be legible, the work used to obtain
the answers must be shown and correct, and the final answers must be
clearly indicated in order to receive full credit.
Extra points
may be deducted for violating any of the following:
 Multiple
pages must be stapled together. No clips.
 Copies
of
the SAS code must be included with any homework requiring SAS.
 Extraneous
pages of SAS output should not be turned in.
You MAY work on the
homework
assignments with other students, but each student must write it up
individually. (i.e., no photocopies of another student's work.)
There will also be a project
involving collecting
and analyzing a data set using the techniques learned in the course.
The details
of the project are given on the course website.

Grades: 
The
grade is
determined by the scores on the homework, project and
examinations as follows:
Homework  10%
Project  10%
Exam 1  20%
Exam 2  20%
Exam 3 20%
Final exam  20%
with the
letter grade determined by the percentage of points obtained.
Letter

Minimum

Grade

Percent

A

90

B+

87

B

80

C+

77

C

70

D+

67

D

60

F

<60

Any questions
involving the grading of a homework assignment or exam must be raised
by the class period following the one in which it was returned.
The homework with
the lowest
grade will be dropped from the
calculations.
There is no "extra credit".
Any deviations from
the above grading scheme will be to the benefit of
the students. 
Complaints
and
Comments: 
While
there are end of semester evaluation forms, they come far too late to
resolve any difficulties experienced in the class. All complaints
should be raised by either speaking with me directly, or by anonymously
leaving a message in my mailbox in 216 LeConte. 
Topics 
Data description and
graphical representation

Probability,
discrete random variables, binomial distribution 
Continuous random
variables, the normal distribution 
Sampling 
Sampling distributions, the
central limit theorem 
Estimation,
confidence intervals 
Hypothesis
testing 
Comparing two treatments or
populations 
Categorical data analysis

Correlation and simple
linear regression 
Twoway tables analysis



