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Winter
2014

## Welcome to Math 183 (Winter 2014)

Instructor Lecture Time (MTuW) Location
Adam Bowers A 12:00 - 12:50 pm CENTR 101

Winter 2014 dates:   02 Jan 2014 - 22 Mar 2014

Section TA Time (Tu) Location Office Hours
A01 Hooman Sherkat 2 pm CENTR 217B F 10 am - 12 pm (APM 6442)
A02 3 pm
A03 Juan Bernal 4 pm CENTR 217B Tu 2-4 pm (APM 5412)
A04 5 pm
A05 Shaunak Das 6 pm CENTR 217B Tu & Th 9-10 am (APM 6434)
A06 7 pm
A07 Liyu Qin 6 pm CENTR 205 M 10 am - 12 pm (APM 2313)
A08 7 pm

Exam Information:   Exam 1     Exam 2     Final Exam
Basic Rules for Casino Games.

Feb 27
2014

## Unbiased Estimator

Do you remember that estimator we found in class? The one I didn't check to see if it was unbiased because it required using integration by parts FOUR TIMES? It turns out it is UNBIASED!
If you want to see the computations, then click this link.

• This PDF comes from Exercise 5.2.5 in the textbook, but the exercise only asks you to find the maximum likelihood estimate. It does not ask you to check to see if it is unbiased. (This topic doesn't even come up until Section 5.4.)
• I would never ask you to check for unbiasedness when it is this involved.

Feb 11
2014

## Section 3.7 In-Class Example

Here is the corrected solution to the example from class on Monday, Feb 10: example of a joint PMF.

Jan 23
2014

## Exam 1 Information

Exam 1 is scheduled for Friday, Jan 31 (during class). Not all students will be taking the exam in our usual lecture hall.   Click here for Midterm Exam 1 information and locations.

## Textbook

The required textbook for the course is An Introduction to Mathematical Statistics and its Applications (5th Edition), by Larsen and Marx. Published by Pearson (2012). (We will cover parts of Chapters 1-7 of the text, time permitting.)

Supplementary Textbooks:
OpenIntro Statistics, D. M. Diez & C. D. Barr & M. Cetinkaya-Rundel   (pdf)
Probability with R: An Introduction with Computer Science Applications, J.M. Horgan   (amazon)
Introduction to Probability, C. M. Grinstead & J. L. Snell   (pdf)
A Modern Introduction to Probability and Statistics: Understanding Why and How, F.M. Dekking
& C. Kraaikamp & H.P. Lopuhaä & L.E. Meester   (amazon)
Modern Mathematical Statistics with Applications, J. L. Devore & K. N. Berk   (amazon)

## Other sites of interest

Student Resources