George Mason University
Volgenau School of Information Technology and Engineering
Department of Statistics


STAT 652 / CSI 672: Statistical Inference

Spring Semester, 2012
Tuesdays from 7:20 to 10:00 PM (starting Jan. 24, other dates given below)

Location: room B224 of Robinson Hall (note: Robinson has an A wing and a B wing)


Instructor: Clifton D. Sutton

Contact Information (phone, fax, e-mail, etc.) Office Hours: 6:00-7:00 & 10:00-10:30 PM on class nights (more information)


Text:

Statistical Inference, 2nd Ed. , by G. Casella & R. L. Berger (Duxbury, 2002)


Prerequisite:

a graduate level course in probability (STAT 544 or ECE 528) and exposure to basic statistical concepts (STAT 554)
(Note: You don't have to take STAT 554 before this course as long as you've had exposure in some course to statistical concepts such as estimation (including confidence intervals) and hypothesis testing (including null and alternative hypotheses, and p-values).)


Description:

The main goal of this course is to introduce you to some of the basic ideas of statistical inference. A knowledge of probability theory will be assumed, the foundations of parametric statistical inference will be presented, and specific methods for estimation and hypothesis testing will be covered. The material presented in this course will serve to justify and enhance some of the concepts and methods covered in other statistics courses.

More specifically, here are some course goals: The general plan of attack to be used in an attempt to achieve these goals is as follows:

Approximate week-by-week content:

[1] Jan. 24:
exponential families; location and scale families
[Sections 3.4 and 3.5 of text]
(HW #1 posted)
[2] Jan. 31:
random samples; sums of random variables; sampling from normal distributions, sample minimums and maximums
[parts of Sections 5.1, 5.2, 5.3, and 5.4 of text]
[3] Feb. 7:
convergence concepts
[Section 5.5 of text]
[4] Feb. 14:
more on convergence concepts, the sufficiency principle
[Section 6.2 of text]
(tentative: HW #1 due; HW #2 posted)
[5] Feb. 21:
more on the sufficiency principle, the likelihood principle; the equivariance principle
[parts of Sections 6.3 and 6.4 of text]
[6] Feb. 28:
point estimation methods
[Section 7.2 of text (subsection 7.2.4 won't be covered)]
(tentative: HW #2 due; HW #3 posted)
[7] March 6:
more on point estimation methods; evaluation of point estimators
[Sections 7.2 and 7.3 of text (subsection 7.2.4 won't be covered)]
[**] March 13:
No class due to Spring Break (Note: If any classes are cancelled (perhaps due to bad weather) prior to Spring Break, this week may be used to make up the missed class.)
[8] March 20:
more on the evaluation of point estimators
[Section 7.3 of text]
(tentative: HW #3 due; HW #4 posted)
[9] March 27:
hypothesis testing methods
[Section 8.2 of text (subsection 8.2.2 won't be covered) and part of Section 8.3 of text]
[10] April 3:
more on hypothesis testing
[Section 8.3 of text]
(tentative: HW #4 due; HW #5 posted)
[11] April 10:
confidence interval methods
[Section 9.2 of text]
[12] April 27:
more on confidence intervals
[Sections 9.2 and 9.3 of text]
(tentative: HW #5 due; part of HW #6 posted)
[13] April 24:
asymptotic methods
[Section 10.1 of text (subsection 10.1.4 won't be covered); part of Section 10.3 of text]
(tentative: remainder of HW #6 posted)
[14] May 1:
more on asymptotic methods
[Sections 10.3 and 10.4 of text]
(tentative: HW #6 due (no grace period))
[**] May 8:
No formal class (unless this day is used to make up a missed class), but if I don't have to make up a missed class, or if this room isn't assigned to another class, I will hold office hours in the class room from 7:20 PM until 9:00 PM to answer questions you may have concerning the final exam.
[**] May 15:
Final Exam (note: exam period is from 7:30 to 10:15 PM)

Grading:


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