Download STAT 4201 Introduction to Mathematical Statistics I Spring Semester

STAT 4201 Introduction to Mathematical Statistics I
Spring Semester 2013
Lecture: MWF 3:00-3:55pm in Hitchcock Hall 0035
Instructor: Yoonkyung Lee
Office: 440B Cockins Hall
Phone: 292-9495
Office Hours: M 11:00-noon, W 4:00-5:00pm or by appointment
Email: [email protected]
TA:
Office
Phone
Email
Office Hours
Yulei Zhang
MA 422
247-2589
[email protected]
T 3:00-5:00pm
Jingjing Yan
CH 304A
292-4956
[email protected]
T 2:00-3:00pm W 12:30-1:30pm
Recitation:
W 11:30-12:25pm in SON 0048 (Yulei Zhang)
W 12:40-1:35pm in CL 0120 (Yulei Zhang)
W 1:50-2:45pm in SM 1048 (Jingjing Yan)
Recitations are an integral part of this course. In some recitations, the TA will spend time going
over examples, explaining concepts and answering questions about the homework. At other times,
the TA will cover material that is not covered in lecture.
Text: John E. Freund’s Mathematical Statistics with Applications (the 7th edition)
by I. Miller and M. Miller, Pearson Prentice Hall 2004.
The book is on reserve in the Science and Engineering Library (SEL).
Prerequisite: Math 2153 or Math 254 or permission of instructor.
Website: The course has a web page on Carmen. You will find the class schedule, homework
assignments, solutions, and other course announcements on the web page. Please check it on a
regular basis.
Course Description
Statistics 4201 is the first course in a two semester sequence on probability and mathematical
statistics. It aims to introduce basic concepts in mathematical statistics, including probability,
discrete and continuous distributions and densities, mathematical expectation, functions of random
variables, transformation techniques, sampling distributions, order statistics. Chapters 1 through
8 of the text will be covered.
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Grading
Your course grade will be based on homework assignments, two midterms, and a comprehensive
final exam.
Homework (20%): There will be approximately weekly assignments. Homework problems and solutions will be posted on the course web page. No late homework will be accepted. Homework is
due at the beginning of class.
Midterm 1 (25%): on February 8 (Friday) in class.
Midterm 2 (25%): tentatively on March 8 (Friday) in class.
Final exam (30%): on April 24 (Wednesday), 4:00-5:45pm
All exams will be closed book. For each midterm you are allowed to bring one standard size (8.5×11
inch) sheet of notes (front and back); for the final you are allowed two standard size sheets of notes
(front and back). Also bring a calculator to all exams.
Academic Misconduct
Although students are encouraged to work together on assignments, each student must submit their
own written work in his or her own words. Academic misconduct will not be tolerated and will be
dealt with procedurally in accordance with University Rule (oaa.osu.edu/procedures).
Special Accommodations
Any student who feels they may need an accommodation based on the impact of a disability should
contact the instructor privately to discuss your specific needs. You should also contact the Office of
Disability Services at 292-3307 or in 150 Pomerene Hall to coordinate reasonable accommodations
for students with documented disabilities.
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Tentative Course Schedule and Textbook Readings
Date
Jan 7 (M)
Jan 9 (W)
Jan 11 (F)
Jan 14 (M)
Jan 16 (W)
Jan 18 (F)
Jan 21 (M)
Jan 23 (W)
Jan 25 (F)
Jan 29 (M)
Jan 30 (W)
Feb 1 (F)
Feb 4 (M)
Feb 6 (W)
Feb 8 (F)
Feb 11 (M)
Feb 13 (W)
Feb 15 (F)
Feb 18 (M)
Feb 20 (W)
Feb 22 (F)
Feb 25 (M)
Feb 27 (W)
Mar 1 (F)
Mar 4 (M)
Mar 6 (W)
Mar 8 (F)
Mar 11-15
Mar 18 (M)
Mar 20 (W)
Mar 22 (F)
Mar 25 (M)
Mar 27 (W)
Mar 29 (F)
Apr 1 (M)
Apr 3 (W)
Apr 5 (F)
Apr 8 (M)
Apr 10 (W)
Apr 12 (F)
Apr 15 (M)
Apr 17 (W)
Apr 19 (F)
Apr 22 (M)
Apr 24 (W)
Topics (Textbook Readings)
Intro to probability, Review of combinations and permutations (Ch. 1, 2.1-2.4)
Probability rules, Conditional probability (2.4-2.5)
Conditional probability, Independent events (2.6-2.7)
Independent events (2.6-2.7), Bayes’ theorem (2.8)
Random variables and probability distributions (3.1-3.2)
Continuous random variables, Probability density functions (3.3-3.4)
Martin Luther King Day - no class
Multivariate distributions (3.5)
Marginal and conditional distributions (3.6-3.7)
Expected value (4.1-4.2)
Moments and moment-generating functions (4.3, 4.5)
Moment-generating functions, Product moments (4.5-4.6)
Product moments (4.6)
Review for Midterm 1
Midterm 1 (1.1-4.6)
Moments of linear combinations of random variables (4.7)
Conditional expectations (4.8)
Discrete uniform, Bernoulli distributions (5.1-5.3)
Binomial distribution (5.4)
Negative binomial and geometric distributions (5.5)
Hypergeometric distribution (5.6)
Poisson distribution (5.7)
Multinomial distribution (5.8)
Continuous density functions, Uniform distribution (6.1-6.2)
Gamma, Exponential distributions, Chi-square distributions (6.3)
Review for Midterm 2
Midterm 2 (4.7-6.3)
Spring Break
Beta, Weibull and Pareto distributions (6.4)
Normal distribution (6.5)
Normal approximation to binomial (6.6)
Functions of random variables: distribution function technique (7.1-7.2)
Transformation techniques: one variable (7.3)
Transformation techniques: one and two variables (7.3-7.4)
Transformation techniques: two variables (7.4)
Moment generating function technique (7.5)
Sampling distributions, Sampling distribution of the mean (8.1-8.2)
Sampling distribution of the mean (8.2)
Central limit theorem (8.2)
Distribution of mean in finite populations (8.3)
Chi-square distribution (8.4)
t-distribution, F-distribution (8.5-8.6)
Order Statistics (8.7)
Review for Final
Final exam (comprehensive)
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