STAT 611 - Prof. Cline

Time and Place:	MWF 9:10am–10:00am, Blocker 156 (Statistics and mathematics majors only).
Instructor:	Daren Cline, Department of Statistics.
Office:	Blocker 459D, 845-1443.
E-mail:	dcline@stat.tamu.edu
Hours:	MWF 10:15am–11:30am or by appointment. Please check my schedule.
Grader:	Soutir Bandyopadhyay. hours: MF 2–5pm (questions about homework only). email: soutir@stat.tamu.edu.
Web Page:	http://stat.tamu.edu/~dcline/611.html Homework will be assigned at this web page.
Text:	G. Casella and R.L. Berger, Statistical Inference, 2nd ed., Duxbury.
References: (On reserve in Evans Library)	P.J. Bickel and K. Doksum, Mathematical Statistics: Basic Ideas and Selected Topics, 2nd ed., Vol. 1 (Prentice Hall). E.J. Dudewicz and S.N. Mishra, Modern Mathematical Statistics, Wiley. R.V. Hogg, J.W. McKean and A.T. Craig, Introduction to Mathematical Statistics, 6th ed., Macmillan. I. Miller and M. Miller, John E. Freund's Mathematical Statistics, 7th ed., Prentice-Hall. A.M. Mood, F.A. Graybill and D.C. Boes, Introduction to the Theory of Statistics, 3rd ed., McGraw-Hill. V.K. Rohatgi, An Introduction to Probability Theory and Mathematical Statistics, Wiley.
Prerequisite:	Statistics 610 or equivalent, including random variables and their probability distributions commonly used distributions probability density and probability mass functions expectation, variance and other moments quantiles multivariate distributions, especially bivariate normal and multinomial conditional distributions and conditional expectations random sampling and basic sample statistics law of large numbers and central limit theorem Statistical or mathematical computing experience is helpful.
Disabilities Help:	The Americans with Disabilities Act ensures that students with disabilities have reasonable accommodation in their learning environment. If you have a disability and need help, please contact me and Disability Services in B118 Cain Hall, 845-1637.
Academic Integrity:	You are expected to maintain the highest integrity in your work for this class. This includes not passing off anyone else's work as your own, even with their permission. Please see the homework and exam policies below for specifics.
Copyright:	All the resources I provide for this course are copyrighted and may not be copied or distributed without my express, written permission.

Homework:	Homework will be assigned (on the course web page) and collected regularly. Homework is worth 20% of the total term score. Please see the homework policy below.
Exams:	Two midterm exams worth 22.5% each and a final exam worth 35%. Please see the exam policy below.
Exam Dates:	Exam I: Wednesday, 28 February. Exam II: TBA. Final Exam: Monday, 7 May, 8:00am--10:00am.
Grading Scale:	A: 85% – 100%. B: 70% – 84%. C: 60% – 69%.

Homework Policy:

Your homework solutions must be your own work, not from outside sources, consistent with the university rules on academic dishonesty. I expect you to follow this policy scrupulously. Your performance on the exams is much more likely to be better.
You may use:

Your textbook and notes from class.
Your notes, homework, etc., from a related class that you took or are taking.
References listed on the syllabus.
Discussion with the instructor or grader.
Voluntary, mutual and cooperative discussion with other students currently taking the class.

You may not use:

Solutions manuals (printed or electronic) and copies of pages from solutions manuals.
Solutions from previous classes.
Solutions, notes, homework, etc., from classes taught elsewhere or at another time.
Solutions, notes, homework, etc., from students who took the class previously.
Copying from students in this class, including expecting them to reveal their solutions in "discussion".

Exam Policy:

Each exam will be comprehensive, cumulative and closed book.

Please bring your own paper. I ask that separate problems be on separate sheets.
No resources other than pen and paper are acceptable. (No calculator.)

I will not expect you to quote theorems and results explicitly but I do expect you to demonstrate that you can make use of them. Specifically, you will need to:

Show all your work. This does not necessarily mean showing every individual algebraic or calculus step – but it must be clear what those steps are.
Identify (by name, number or description) any theorems, examples or homework problems you use.
Clearly identify the solution and/or the end of a proof or derivation.

Copies of my old exams will be available on the course web page.

Missed Work and Incompletes:

This is based on university policy.

If you must miss an exam due to illness or circumstances beyond your control, notify me or the Statistics Department before the exam. See me immediately after you return (within one day) to schedule a make-up exam.
Incompletes will be given only in the event that circumstances beyond your control cause prolonged absence from class and the work cannot be made up.

Topic		Section
1. Statistical Models
	parametric and hierarchical models, exponential families	3.4, 3.5, 4.4
	identifiability
2. Data Reduction
	sufficiency, completeness, ancillary statistics	6.1
	likelihood principle	6.2
	invariance principle	6.3
3. Estimation Techniques
	method of moments, least squares, quantile estimates	7.2
	maximum likelihood	7.2
	M-estimation, estimating equations	10.2
	Bayes and minimax estimation	7.2
4. Estimation Issues
	bias, sampling error, sampling distribution	5.5, 7.3
	best unbiased estimators	7.3
	lower bounds on variance	7.3
	consistency, large sample properties	10.1
5. Hypothesis Testing
	likelihood ratio tests, Neyman-Pearson Theorem	8.2
	p-values, power	8.3
	Bayesian tests	8.2
	unbiased and most powerful tests	8.3
	score tests
	large sample tests, chi-square tests	10.3
6. Interval Estimation
	pivotal quantities, inversion of tests	9.2
	confidence intervals, Bayes intervals	9.2
	large sample confidence intervals	9.3, 10.4

Course Information

Grading

Course Policies

Course Outline