APMA 1650
Statistical Inference I
Fall 2016

Prof: Benjamin Kunsberg
office: 182 George Street, Office 222
e-mail: benjamin_kunsberg@brown.edu
office hours: TBA

TAs: Clark Bowman

Nathan Meyers

Brandon Zborowski

Yue Bai

Michael Golz

Hwai-ray Tung

Please see the calendar below for office hours.
To email any TA please use firstname_lastname@brown.edu
Lecture: MWF 2:00 - 2:50, Barrus and Holley 168

In addition to office hours, there are two Problem Sessions per week. Problem sessions are optional. Dates TBA (Most likely Tuesday 5 p.m. and Thursday 5 p.m.). (See Calendar below for locations).




Course Description: APMA 1650 begins an integrated first course in mathematical statistics. The first half of APMA 1650 covers probability and the last half is statistics, integrated with its probabilistic foundation. Specific topics include probability spaces, discrete and continuous random variables, methods for parameter estimation, confidence intervals, and hypothesis testing. Prerequisite: MATH 0100 or its equivalent. We will cover (approximately) the first 10 chapters of the textbook.

Trying to decide between 0650 and1650? See here.

Required texts:
Mathematical Statistics with Applications, Wackery, Mendenhall, Scheaffer. 7th Edition.

Homework:
There will be weekly homework assignments due each Friday. You are encouraged to work together but all students must independently write up their own solutions. All homeworks are due by the beginning of class unless otherwise noted. We prefer that homeworks be turned in to the drop off boxes in the lobby of 182 George St., although in class is also accepted.

Homework Policy: Late homework will generally not be accepted. If you have a serious reason for needing to turn in an assignment late, you must contact me directly. TAs can not grant homework extensions. If you cannot complete an assignment on time, turn in as much as you can. Completing the homework on time is the best way you can get the most out of the class.
At the end of the semester we will drop your lowest homework score.

Grading Policy: If there is a mistake in the grading of your assignment (points are added incorrectly, your score was misentered into the grade book) please let me know immediately.
If you disagree with the grading of your assignment then you may: copy the relevant portion of your assignment, attach a written explanation of your disagreement and turn it back in to me. I will look at the concern at the end of the semester if it will possibly affect your overall grade. Please note that small changes in homework points generally do not affect an overall grade. Given the large size of the course, this policy allows for a better use of time by the staff.


Homework 1 due Friday Sept 16th. Please include this cover sheet (or equivalent) with your homework.
Homework 2 due Friday Sept 23rd. Please include this cover sheet (or equivalent) with your homework.
Homework 3 due Friday Sept 30th. Please include this cover sheet (or equivalent) with your homework.
Homework 4 due Friday Oct 7th. Please include this cover sheet (or equivalent) with your homework.
Homework 5 due Friday Oct 21th. Please include this cover sheet (or equivalent) with your homework.
Homework 6 due Friday Oct 28th. Please include this cover sheet (or equivalent) with your homework.
Homework 7 due Friday Nov 4th. Please include this cover sheet (or equivalent) with your homework.
Homework 8 due Friday Nov 11th. Please include this cover sheet (or equivalent) with your homework.
Homework 9 due Friday Dec 2nd. Please include this cover sheet (or equivalent) with your homework.
Homework 10 due Friday Dec 9th. Please include this cover sheet (or equivalent) with your homework.

Fall 2016 Expected Schedule:
Week 1: Introduction to central ideas of statistics and probability. Definition of Probability space. Uniform Distribution Additive rules of probability. Products, orderings, binomial coefficients, multinomial coefficients. (Approx. textbook sections: 2.1-2.6)
Week 2: Conditional probability, Bayes Law, Theorem of Complete Probability. Independence. Multiplicative Law, Tree diagrams. (Approx. textbook sections: 2.7-2.10)
Week 3: Expectation, Binomial Distribution, Geometric Distribution, Poisson Distribution, Hypergeometric Distribution
Week 4: Indicator R.V.s, Deviations from the mean: Variance. (3.3) Markov's inequality, Chebyshev's inequality (~3.11). (up to Sept. 30, 2016).
Week 5: Weak Law of Large Numbers, Continuous probabilities. CDFs, densities. (4.1-4.3)
Week 6, 7: More CDFs, densities. Uniform distribution, Normal distribution (4.4-4.6)
Week 8: Gamma, exponential distributions, Multivariate, marginal and conditional distributions, independence (5.1-5.6)
Week 9: expected value(5.1-5.6) Covariance and correlation. (5.7) Sampling, point estimators, Bias, MSE. (8.1-8.4)
Week 10: Central Limit Theorem. Error of estimation, confidence intervals. (7.1-7.3, 8.5-8.10)
Week 11: Method of Moments, MLE. (9.1-9.7)
Week 12: Hypothesis Testing (10.1-10.6)
Week 13: Hypothesis Testing (10.7-10.10)
Week 14: Likelihood Ratio tests (10.11)

Grading:
There will be two (in-class) midterms(~35%) and a final(~35%) in addition to weekly assignments(~30%).

Midterm 1: Friday, Oct 14th, in class: 2:00 - 2:50
Midterm 2: Nov 18th, in class: 2:00 - 2:50
Final: Dec 16th, 2-5 p.m.