
|
Instructor |
Dr. Anda Gadidov |
|
Office |
Science
Building Room 529 |
|
Phone |
(770)423-6098,
e-mail: agadidov@kennesaw.edu |
|
Office
hours |
MW
11:00am- 12:30pm; T 4:00pm-6:30pm. Other times by appointment |
|
Class
meets |
T
6:30pm-9:15pm in CL1007 |
|
Text |
An
Introduction to Mathematical Statistics and its Applications, fourth ed., by Richard J.
Larsen and Morris L. Marx, Pearson Education, Prentice Hall, Upper
Saddle River, ISBN: 0 – 13 – 186793-8. |
|
Prerequisites |
STAT
7010 with grade if C or better |
|
Description |
Review
of hypothesis testing, two-sample problems, goodness-of-fit tests,
regression, analysis of variance and introduction to nonparametric tests.
Software such as Maple 12, Minitab or SAS will be used. |
|
Learning |
1.
Students will be able to construct confidence intervals for the
parameters of various distributions and interpret the results. 2.
Students will be able to compare the performance of various
estimators using properties such as unbiasedness,
efficiency and minimum variance. 3.
Students will understand the concept of statistical hypothesis
testing and will be able to use it accordingly in applications. 4.
Students will be able to apply statistical methods in solving
two-sample problems. 5.
Students will be able to use the goodness-of-fit methods in
assessing the underlying distribution of a given data set. 6.
Students will be able to use the goodness-of-fit methods in
assessing independence of two variables under analysis. 7.
Students will be able to apply linear regression to determine
whether there is a relationship among various components of a complex system
of variables. 8. Students will be able to use the
analysis of variance in problems involving more than two samples. 9. Students will be able to perform
statistical analysis using a software of choice: SAS, Minitab or Microsoft
Excel. 10. Students will be able to read,
discuss and present professional articles reporting statistical results. |
|
Topic
outline |
1.
Estimation: Review of MLE and MOM estimators;
Properties of estimators (Chapter 5) Minimum variance estimators.
Sufficiency, Consistency; Bayesian estimation. 2.
Hypothesis testing (Chapter 6): p-values;
type I and type II errors; tests for one proportion. The generalized
likelihood ratio test. 3.
Distributions derived from the normal
distribution (Chapter 7). Inferences about the mean and variance. 4.
Two-Sample Problems: testing the equality
of two means, two-variances or two proportions. Confidence intervals for
two-sample problems. (Chapter 9) 5. Goodness-of-Fit
Tests: the multinomial distribution, goodness-of-fit tests, contingency
tables. (Chapter 10) 6. Regression: the
method of least squares, the linear model, covariance and correlation, the bivariate normal distribution. 7. The Analysis of
Variance: the F test, multiple comparisons: Tuckey’s
method, testing subhypotheses with contrasts. 8. Randomized
Block Designs: the F test and the paired t-test. (Chapter 13) 9. Nonparametric
Statistics: the sign test, Wilcoxon tests, the Kruskal-Wallis test. The Friedman test. |
|
Grading |
Working
the homework will be a very important component of success in the course. Your
grade will be based on your performance on homework assignments, class
discussions and presentations of ongoing projects and articles read in professional
journals, projects and tests. There will be two semester exams and a final.
The date the project is due will be announced. Make-up
tests will not be given unless there are exceptional circumstances. If
you must miss a test, you should notify me in writing before the
scheduled test time. Tentative
exam schedule: Exam 1:
Feb. 10, 2009 Exam 2:
March 31st, 2009. Final
Exam: May 5, 2009, 6:30 – 8:30 PM. Check
my homepage http://math.kennesaw.edu
for updates on the course. A: 90%
or above, B: between 80% and 90%; C: between 70% and 80%, D: below 70%. |
|
Academic |
Every KSU student is responsible for upholding the
provisions of the Student Code of Conduct, as published in the Undergraduate
and Graduate Catalogs. Section II of the Student Code of Conduct addresses
the University’s policy on academic honesty, including provisions
regarding plagiarism and cheating, unauthorized access to University materials,
misrepresentation/falsification of University records or academic work,
malicious removal, retention, or destruction of library materials,
malicious/intentional misuse of computer facilities and/or services, and
misuse of student identification cards. Incidents of alleged academic
misconduct will be handled through the established procedures of the
University Judiciary Program, which includes either an “informal”
resolution by a faculty member, resulting in a grade adjustment, or a formal
hearing procedure, which may subject a student to the Code of Conduct’s
minimal one semester suspension requirement. |
|
Withdrawal |
Students who find that they cannot continue in college for
the entire semester after being enrolled, because of illness or any other
reason, need to complete an online form. To completely or partially withdraw
from classes at KSU, a student must withdraw online at www.kennesaw.edu, under Owl Express,
Student Services. The
date the withdrawal is submitted online will be considered the official KSU
withdrawal date which will be used in the calculation of any tuition refund
or refund to Federal student aid and/or HOPE scholarship programs. It is
advisable to print the final page of the withdrawal for your records.
Withdrawals submitted online prior to midnight on the last day to withdraw
without academic penalty will receive a “W” grade. Withdrawals
after midnight will receive a “WF”. Failure to complete the
online withdrawal process will produce no withdrawal from classes. Call the
Registrar’s Office at 770-423-6200 during business hours if assistance
is needed. Students may, by means of the same online withdrawal and
with the approval of the university Dean, withdraw from individual courses
while retaining other courses on their schedules. This option may be
exercised up until March 6, 2009. This is the date to withdraw without academic penalty
for Spring term, 2009 classes. Failure to withdraw by the date above will
mean that the student has elected to receive the final grade(s) earned in the
course(s). The only exception to those withdrawal regulations will be for
those instances that involve unusual and fully documented circumstances. |
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