I. PerspectiveII. OrganizationLectures are on Tuesdays and Thursdays, 5:00-6:15 PM in North Hall 1105.I. Introduction Ch. 1II. Data Description Ch 4.1- 4.2IV. Dispersion Ch 4.3 – 4.4, Ch 4.6 – 4.8I. Introduction to JMPII. HistogramsIII. Box and Whisker PlotsI. Introduction Ch 6.1II. Random Experiments Ch 6.2III. Events Ch 6.2IV. The Addition Rule Ch 6.4VII. Independence Ch 6.3VIII. De Mere AgainI. Introduction Ch 7.1-7.2II. Repeated Bernoulli Trials Ch 7.6III. Histograms of the Probability DistributionsVII. Variance of the Sum of Independent Random Variables Ch 7.4VIII. The Coefficient of Variation Ch 4.3IX. Applications of the Binomial DistributionI. Introduction Ch 8.1II. The Normal Approximation to the BinomialIII. Continuous Variables and the Uniform Distribution Ch 8.2I. Introduction Ch 9.1III. Confidence Intervals for Sample Means and Population Means Ch 9.2, Ch 10.3I. Introduction Ch 2.5II. Capital Asset Pricing Model Ch 18.6III. Ordinary Least Squares Ch 4.5I. IntroductionII. Correlation Ch 4.5, Ch 7.4, Ch 18.5, Ch 18.8III. Analysis of Variance Ch 18.5I. IntroductionII. The Assumptions of Least Squares Ch 18.4III. The Pathologies of Least Squares Ch 18.9VII. The Expected Value of the Sum of Squared ResidualsI. IntroductionII. Bayes Theorem and Conditional Probability Ch 6.5III. Duration Models, Failure Time, and the Exponential Distribution Ch 8.4I. IntroductionII. Failure Time Models and the Weibull DistributionIII. TransformationsIV. Cumulative Hazard FunctionV. Poisson Distribution Ch 7.7II. Bivariate Normal Density 18.4III. Marginal Density FunctionsIV. Conditional Density FunctionsV. Example: Rates of Return for a Stock and the MarketFall 2004 Econ 240A Llad PhillipsReading list - 1I. PerspectiveThis is a class in applied statistics, and will emphasize concepts, examples and applications. The lectures will establish a foundation for application and data analysis, covering concepts and using examples. The labs will provide hands-on experience with software and data, covering the idiosyncrasies of applying a statistical procedure with the software package at hand, and interpreting the results.The midterm and final will be a mix of conceptual questions, and questions based on interpreting results generated from procedures studied in the labs.The exercises assigned with a lab will extend your knowledge of the procedures covered in the Lab Notes. The projects will test your ability to conduct analyses on your own without specific lab or project notes to guide you. II. OrganizationLectures are on Tuesdays and Thursdays, 5:00-6:15 PM in North Hall 1105.Lecture Notes for class will cover the conceptsText: Gerald Keller and Brian Warrick, Statistics for Management and Economics, Sixth edition (2003)The two Labs are back to back on Wednesdays, 5:00-5:50, and 6:00-6:50 in Mesa,Phelps 1525. The capacity is 25 stations, so sign up for a lab section the first day of class.Software: Excel and EViewsLab Notes will cover the procedures of analysisTA: Darius Martin, Office, NH 2047Section: TBA, weeklyExams: Midterm Tuesday, Nov. 2Final Tuesday, December 9, 7:30-10:30 PMProblem Sets, Pre-Midterm: #1 Sept. 30, 2004 due Oct 7, 2004#2 Oct 7, 2004 due Oct 14, 2004#3 Oct 14, 2004 due Oct 21, 2004#4 Oct 21, 2004 due Oct 28, 2004#5 Nov. 4, 2004 due Nov. 16, 2004Exercises: as assigned on the Lab NotesTakehome Project: An exercise to test your quantitative and writing skills. You can work collectively but the 2-3 page report must be yours. Last Fall we did group projects with PowerPoint presentations and I will probably repeat this format.Your grade for the course will be based on your scores on the midterm(18%), final(37%) and 2 projects(each 18%), and your effort as indicated by problem setsand lab exercises turned in for credit(9%). Of course the latter are more important than the weight indicated. I distribute the grades by letter, weighing the problemFall 2004 Econ 240A Llad PhillipsReading list - 2sets one third of a grade point, and by total score for the class, and reconcile the course grades.1. Thursday, Sept. 23, Lecture One: Exploratory Data Analysis, Ch’s 1, 2, 3, 4 I. Introduction Ch. 1II. Data Description Ch 4.1- 4.2III. Exploratory Data Analysis Ch 2.1 – 2.4, Ch 2.6-2.7, Ch 3Stem and leaf diagramIV. Dispersion Ch 4.3 – 4.4, Ch 4.6 – 4.8Interquartile rangeBox and whiskers plotSample standard deviation2. Tuesday, Sept. 28, Lecture Two :Exploratory Data Analysis Meets in Humanities and Social Sciences (HSSB) 1203 . Web: www.lsit.ucsb.eduI. Introduction to JMPII. HistogramsIII. Box and Whisker PlotsIV. The 3D Spinning Plot3. Wednesday, Sept. 29, Lab One: Orientation to Excel, Exploratory data Analysis4. Thursday, Sept. 30, Lecture Three: Probability Ch 6I. Introduction Ch 6.1II. Random Experiments Ch 6.2III. Events Ch 6.2IV. The Addition Rule Ch 6.4V. Interpretations or Meanings of Probability Ch 6.2VI. Conditional Probability Ch 6.3VII. Independence Ch 6.3VIII. De Mere Again5. Tuesday, Oct. 5, Lecture Four: Random VariablesI. Introduction Ch 7.1-7.2II. Repeated Bernoulli Trials Ch 7.6III. Histograms of the Probability Distributions IV. Pascal’s Triangle V. The Binomial Distribution Ch 7.6VI. Expected Value of the Sum of Random Variables Ch 7.4VII. Variance of the Sum of Independent Random Variables Ch 7.4VIII. The Coefficient of Variation Ch 4.3IX. Applications of the Binomial Distribution6. Wednesday, Oct 6, Lab Two: Binomial Distribution7. Thursday, Oct 7, Lecture Five: Normal Distribution Ch’s 5, 8, 9Fall 2004 Econ 240A Llad PhillipsReading list - 3I. Introduction Ch 8.1II. The Normal Approximation to the Binomial III. Continuous Variables and the Uniform Distribution Ch 8.2IV. The Sampling Distribution of the Mean Ch 9.2V. Student’s t-Distribution Ch 8.5VI. Sampling Ch 5.1 – 5.68. Tuesday, Oct 12, Lecture Six: Interval Estimation and Hypothesis Testing Ch’s 10, 11, 12I. Introduction Ch 9.1II. Confidence Intervals for Sample Proportions and Population Proportions Ch 9.3, Ch 12.4III. Confidence Intervals for Sample Means and Population Means Ch 9.2, Ch 10.3IV. Hypothesis Tests for Proportions Ch 12.4V. Hypothesis Tests for a Sample Mean Ch 11.3VI. Decision Theory Ch 11.49. Wednesday, Oct. 13, Lab Three: Sampling Distributions10. Thursday, Oct. 14, Lecture Seven: Bivariate Relationships Ch 18I. Introduction Ch 2.5II. Capital Asset Pricing Model Ch 18.6III. Ordinary Least Squares Ch 4.511. Tuesday, Oct. 19, Lecture Eight: Correlation and
View Full Document