General Information about STA 4322/5325
Mathematical Statistics
Spring 2007
Lectures: TR 9:30–10:45 in Room 108 OSB
Instructor: Fred W. Huffer, Room 209C OSB, Phone 644-6696.
Office Hours: TR 10:45–11:45 (or by appointment)
e-mail: huffer@stat.fsu.edu
Class Materials posted at: http://stat.fsu.edu/∼huffer/mordor/4322
This address must be typed completely; you cannot get there by clicking on a series
of links. The posted files are pdf files and require Acrobat Reader to read and print
them. This syllabus and some homework solutions will also be posted in mordor.
Items posted in mordor will include: this syllabus, lecture notes, homework solutions,
and old exams and quizzes.
Required Text: Mathematical Statistics and Data Analysis (Third edition), John A. Rice,
Duxbury, 2007.
Prerequisite: STA 4321 (Intro Math Stat)
If you have had STA 4442 (Intro to Prob), MAC 2313 (Calc III), and are familiar with
multivariate (joint) distributions, that should also be sufficient.
Goal of Course: To introduce the theory and concepts which underly and justify commonly
used statistical methods.
Tentative Syllabus: Chapters 8 and 9, and selected topics from later chapters. A tentative
list of topics is given below.
• Parameter estimation: method of moments and maximum likelihood.
• Pearson’s chi-squared goodness-of-fit test.
• Comparison of estimators using mean squared error and bias.
• Asymptotic distributions via the δ-method.
• The Fisher information for parametric families of distributions.
• Asymptotic distributions for maximum likelihood estimates.
• Confidence intervals for maximum likelihood estimates.
• Bayesian estimation.
• The Cramer-Rao lower bound.
• Sufficient statistics and the factorization criterion.
• The Rao-Blackwell theorem.
• Introduction to Hypothesis Testing.
• The Neyman-Pearson Lemma.
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• Likelihood ratio tests.
Course Grades: Your course grade will be based on quizzes (given roughly every other week)
and two exams. The percentage weights attached to these items are:
Quiz Average
Score on Exam # 1
Score on Exam # 2
40%
30%
30%
A course total will be computed using these weights. This will be used to assign grades
according to the following scale (which reports the lowest percentage score in each of the
grade ranges):
A
A–
90.00 85.00
B+
80.00
B
B–
C+
75.00 70.00 65.00
C
60.00
C–
D
55.00 50.00
Lower grade cutoffs may be used (at my discretion) if the above grade cutoffs lead to
what I consider an unreasonable distribution of grades.
Test Schedule:
Exam # 1
Exam # 2
Thursday, March 1, 9:30–10:45AM in 108 OSB
Tuesday, April 24, 10:00–12:00 (noon) in 108 OSB
The two exams are “unit” exams. There will not be a cumulative final exam.
Quizzes: Quizzes will be given roughly every other week and will be announced in advance.
Quizzes will cover recent homework and lecture material. They will not be cumulative.
Quiz problems will typically be modified versions of problems assigned as homework or
modified versions of examples presented in lecture. They could also be short answer or
multiple choice questions testing recollection of definitions, formulas or concepts covered
in lecture.
Schedule for first few quizzes (tentative):
• January 23 (Tuesday)
• February 6 (Tuesday)
• February 20 (Tuesday)
Your quiz average, which counts for 40% of your grade, is computed after dropping your
lowest quiz score.
If you miss a quiz, you receive a zero for that quiz (and this zero counts as one of your
lowest scores). If you miss a quiz for a legitimate reason (medical problem or family
emergency) and you bring adequate documentation of this reason, you will receive an
“excused” absence. (The documentation should be brought in as soon as possible after
the missed quiz.) If you have more than one excused absence, you will be given make-up
quizzes for the additional excused absences. (Nothing special will be done if you have
only one excused absence; this will still count as a zero. Non-excused absences will always
count as a zero.)
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First Assignment:
posted in mordor
Homework exercises are not handed in. However, quiz and test problems will strongly
resemble homework exercises (or lecture examples). Solutions to all (or most) of the
exercises will be handed out to the class (in advance of the quiz covering that material).
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