Economics 240AOutlinePowerPoint PresentationSlide 4Office hoursCourse OverviewConcepts 1Slide 8Slide 9Slide 10Slide 11Concepts 2Concepts 3Statistical Inference and ProbabilitySlide 15Slide 16Slide 17Slide 18Slide 19Resources for StudyingSlide 21Slide 22Slide 23Slide 24Concepts 4Keller & Warrack Slide ShowSlide 272.1 Introduction2.2 Types of data and informationTypes of data - examplesSlide 31Types of data – analysisCross-Sectional/Time-Series Data2.3 Graphical Techniques for Interval DataExample 2.1: Providing informationSlide 36Slide 37Class widthShapes of histogramsSlide 40Modal classesDescriptive StatisticsConcepts 5Slide 44Concepts 6Moving from Concepts to MeasuresSlide 47Slide 48Slide 49Slide 50Slide 51Slide 52Concepts 7Exploratory Data AnalysisSlide 55Slide 56Slide 57Box DiagramSlide 59WhiskersSlide 61Next Tuesday Only!Slide 631Economics 240APower One2OutlineCourse OrganizationCourse OverviewResources for StudyingI. Organization Lectures are on Tuesdays and Thursdays, 5:00-6:15 PM in North Hall 1105. Lecture Notes for class will cover the concepts Text: Gerald Keller, Statistics for Management and Economics, Seventh edition (2005) The two Labs are back to back on Wednesdays, 5:00-5:50 in Leadbetter, Phelps 1530, and 6:00-6:50 in Gaviota, Phelps 1529. The capacity is 25 stations, so sign up for a lab section the first day of class. Software: Excel and EViews Lab Notes will cover the procedures of analysis TA: Munpyung O, Office, NH 2040 Section TBA Exams: Midterm Tuesday, Nov. 1` Final Tuesday, December 8, 7:30-10:30 PMProblem Sets, Pre-Midterm: #1 Sept. 29, 2005 due Oct 6, 2005 #2 Oct 6, 2005 due Oct 13, 2005 #3 Oct 13, 2005 due Oct 20, 2005 #4 Oct 20, 2005 due Oct 27, 2005 Problem Set, Post-Midterm #5 Nov. 3, 2005 due Nov. 10, 2005 Exercises: as assigned on the Lab Notes Organization ( Cont.)Takehome Project: An exercise to test your quantitative and writing skills. Youcan work collectively but the 2-3 page report must be yours. Last Fall we didgroup projects with PowerPoint presentations and I will probably repeat thisformat.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 sets and 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 problem sets one third of a grade point, and by total score for the class, and reconcile the course grades.5Office hoursLlad Phillips•North Hall 3032, Wed. 4:00-4:40, by appt•[email protected]Munpyung O•Section : Th NH 2111, 4:00-4:50•Office, NH 2040, Tu 4:00-4:50•[email protected] OverviewTopics in Statistics•Descriptive Statistics•Exploratory Data Analysis•Probability and Distributions•Proportions •Interval Estimation•Hypothesis Testing•Correlation and Regression•Analysis of Variance7Concepts 1Two types of data:•Time series•Cross section8http://research.stlouisfed.org/fred2/9http://research.stlouisfed.org/fred2/10Examples of:1.Graphical Display of Results2.Cross-Section Data3.Survey Sample of 12,571 1.Men & women2.Ages 15-4411What is the Message?12Concepts 2Population Versus SampleSpecial Election this Fall•Population: All eligible voters•Sample: Field pollPopsample13Concepts 3Different views of the world (universe)•Deterministic•Stochastic14Statistical Inference and ProbabilityDeterministic•Newtonian physics: e g. distance = rate*time•Einsteinian(relativistic) physics: E=m*c2Stochastic (random)•Quantum mechanics15Statistical Inference and ProbabilityProbability: A tool to understand chanceWhat is chancy about the statistical world we will study?Example: •Suppose I number everyone in the class from 1 to 30?•And draw one number a meeting to ask a question; what is the likelihood I will call on you today?1617181920Resources for StudyingKeller •Text Readings•CDROM•AppletsInstructor•Lecture Notes•Lab Notes & Exercises•Problem Sets•PowerPoint Slide Shows21http://econ.ucsb.edu22Keller CDROM23http://www.duxbury.com/statistics24Student Book Companion Siten25Concepts 4Three types of data•Cardinal•Ordinal•Categorical26Keller & Warrack Slide ShowExcerpts from Ch. 227Graphical Descriptive TechniquesGraphical Descriptive TechniquesChapter 2Chapter 2282.1 IntroductionDescriptive statistics involves the arrangement, summary, and presentation of data, to enable meaningful interpretation, and to support decision making.Descriptive statistics methods make use of•graphical techniques•numerical descriptive measures. The methods presented apply to both•the entire population•the population sample292.2 Types of data and informationA variable - a characteristic of population or sample that is of interest for us.•Cereal choice •Capital expenditure•The waiting time for medical servicesData - the actual values of variables •Interval data are numerical observations•Nominal data are categorical observations•Ordinal data are ordered categorical observations30Types of data - examplesInterval dataAge - income55 7500042 68000. .. .Age - income55 7500042 68000. .. .Weight gain+10+5..Weight gain+10+5..NominalPerson Marital status1 married2 single3 single. .. .Person Marital status1 married2 single3 single. .. .Computer Brand1 IBM2 Dell3 IBM. .. .Computer Brand1 IBM2 Dell3 IBM. .. .31Types of data - examplesInterval dataAge - income55 7500042 68000. .. .Age - income55 7500042 68000. .. .Nominal dataWith nominal data, all we can do is, calculate the proportion of data that falls into each category.IBM Dell Compaq Other Total 25 11 8 6 50 50% 22% 16% 12% IBM Dell Compaq Other Total 25 11 8 6 50 50% 22% 16% 12% Weight gain+10+5..Weight gain+10+5..32Types of data – analysisKnowing the type of data is necessary to properly select the technique to be used when analyzing data.Type of analysis allowed for each type of dataInterval data – arithmetic calculationsNominal data – counting the number of observation in each categoryOrdinal data - computations based on an ordering process33Cross-Sectional/Time-Series DataCross sectional data is collected at a certain point in time
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