SYLLABUS FOR STATISTICS 100A - LECTURE 1SPRING QUARTER 2011Instructor: Nicolas ChristouOffice: 8931 Math Sciences Bldg.Telephone: (310) 206-4420e-mail: [email protected]: http://www.stat.ucla.edu/~nchristo/statistics100AOffice hours: MWF 14:00-16:00, T 12:00-14:00Lecture Day Class Time LocationLEC 1 MWF 13:00 - 13:50 HAINES 118Discussion Day Discussion Time LocationDIS 1A T 14:00 - 14:50 GEOLOGY 3656DIS 1B T 15:00 - 15:50 GEOLOGY 3656COURCE RESOURCES:Handouts can be accessed at http://www.stat.ucla.edu/~nchristo/statistics100A.Textbook (optional): Sheldon Ross, A First Course in Probability, Eighth Edition, Pearson, 2009.Probability and Statistics EBook (freely available at): http://wiki.stat.ucla.edu/socr/index.php/EBook.Software: R (can be downloaded freely from http://cran.stat.ucla.edu), and Statistics Online ComputationalResource (SOCR), freely available at: http://www.socr.ucla.edu.COURSE TOPICS1. Combinatorial analysis (Chapter 1).Basic principle of counting.Permutations.Combinations.Multiple coefficients.2. Probability (Chapter 2, Chapter 3).Axioms of probability.Sample space and events.Conditional probability and independence.Law of total probability.Bayes’ rule.3. Discrete random variables (Chapter 4).Expected value.Variance.Bernoulli and Binomial random variables.Poisson random variable.Geometric random variable.Geometric random variable.Negative binomial random variable.Hypergeometric random variable.4. Continuous random variables (Chapter 5).Expected value.Variance.Uniform random variable.Normal random variable.Gamma, Beta, Cauchy, Weibull distributions.Distribution of a function of a random variable.5. Jointly distributed random variables (Chapter 6).Joint distributions functions.Independent random variables.Sums of inependent random variables.Bivariate normal distribution.Order statistics.6. Properties of estimation (Chapter 7).Expectation of sums of random variables.Covariance, variance of sums of random variables.Correlation.Moment generating functions.7. Limit theorems (Chapter 8).Chebyshev’s inequality and the weak law of large numbers.The Central Limit Theorem.The strong law of large numbers.8. Simulation (Chapter 10).Simulating continuous random variables.Simulating discrete random variables.COURSE POLICIES:Please remember to turn off cell phones. The use of laptop computers will not be permitted in class. You are expectedto adhere to the honor code and code of conduct. If you have a disability that will require academic accommodation,please contact the UCLA Office for Students with Disabilities (OSD).COURSE GRADES:There will be three (3) exams (cumulative), homework, and labs that will be assigned every week. Please write yourname and staple your homework and labs. Late homework or labs will not be accepted and make-up exams willnot be given. Being in class on time and fully participating is important for your understanding of the material andtherefore for your success in the course. Attendance will be taken at random times during the course and it willcount for 10% of your grade. The tentative dates for the exams are shown below.The course grade will be based on the calculationF inal score = 0.10 × Attendance + 0.10 × H omework + 0.20 × Exam1 + 0.20 × Exam2 + 0.40 × F inalImportant dates:First day of classes: 28 March.Holidays: 30 May (Memorial Day).Last class: 03 June.Exam 1: Week 4.Exam 2: Week 7.Exam 3: Week 10.Good Luck