STATISTICS 120B -- Introduction to Statistics - Winter 2005

   instructor: Gang Liang
       office: 436G Computer Science
        phone: 949-824-9795
        email: liang@uci.edu


Objectives: Introduce basic concepts of statistical inference including 
		point estimation and confidence intervals, decision anlaysis, categorical
		data methods, and linear regression.  This is the second quarter of a 
		two quarter sequence in probability and statistics.

Prerequisites: Math 2A-B, Math 2D, one of Math 2J, Math 3A, Math 6C,
		Stat 120A or equivalent (Math 130A, Math 131A).

Tentative Course Outline:

Week 1 – Sampling from populations: mean and variance of a population, 
	properties of sample mean and sample variance, sampling distributions.

Week 2 - Estimation of parameters of probability distributions: review 
	probability distributions, estimation via method of moments, maximum
	likelihood.

Week 3 - Evaluating estimators: properties (bias, variance), large sample theory,
	role of sufficiency. 

Week 4 - Normal distribution theory (sample mean, sample variance, t-distribution)

Weeks 5-6 - Confidence intervals: interval estimation via pivotal quantities, likelihood.  Normal distribution theory and t-distributions.

Weeks 7-8 - Hypothesis tests: likelihood ratio tests, relationship of tests and confidence
	intervals.

Week 9 - Two sample inference: point estimates, confidence intervals and testing for 
	two population means.

Week 10 - Bayesian inference


Course Requirements: Students will be assigned problem sets, approximately 
	once in each week.  There will be midterm and final exams.  The grade 
	is determined by performance on this work as follows: homework
	(approx 30%), midterm exam (approx 30%), final exam (approx 40%).  

Text/Reading: Mathematical Statistics and Data Analysis, 2nd edition, 1995
	by John Rice, Duxbury Press. 

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