PS 551Introduction to Statistical Inference for Political ScienceCharles H. FranklinUniversity of Wisconsin, MadisonMatt HollequeTeaching AssistantFall 20091 IntroductionThis class aims to introduce you to both the theory and the practice of statistical analysis. Thereare four parts to the class:1. Descriptive statistics and data visualization2. Probability theory3. Statistical inference and hypothesis testing4. Linear regressionThe first and last deal with data analysis, while the two theoretical parts deal with how we justifythe inferences we make about the processes that generate the data.Throughout the class, we will use the R statistical language. This is the most powerful statisticalsystem in the world, and it is free. R runs on Windows, Mac OS X and Linux. You can downloada copy from the Comprehensive R Archive Network athttp://cran.wustl.edu/Browse the CRAN site for documentation as well. Have this installed on your computer by thesecond class. R is available on all the computers in the Social Science Micro Computer Lab as well.Exercises in the class will be a combination of solutions using R and calculations done by hand(with the aid of a calculator). You do not need a sophisticated calculator, though one with severalmemories, a square and square root key is required. Logarithm keys are also handy. You mightchoose a “statistics” calculator, which will have a number of formulas built in for mean, varianceand perhaps more. However, you are responsible for knowing how to calculate the formulas so don’trely on the calculator as a “black box”. Exams will require use of a calculator, so be sure to getused to one in solving homeworks and use the same calculator in exams.The only way to learn statistics is to solve problems, so there will be regular homework assign-ments. I am happy for you to talk about the assignments with one another, but be aware that ifyou let other people solve your homework you will almost certainly do poorly when on your ownfor exams. So talk, discuss and so on, but in the end work your own solutions.12 Schedule of ExaminationsThere will be three in-class exams during the semester plus a comprehensive (cumulative) finalexam. The exam dates are1. September 30, Data distributions & summaries2. October 28, Probability & Sampling Distributions3. December 2, Inference for Means, Proportions & Tables4. December 19: Comprehensive FINAL EXAM, 10:05AM-12:05PM. And yes indeed, that IS aSaturday.Please note these dates. If you cannot be available for a scheduled exam, drop the course now. Noexcused absence will be permitted except in case of documented serious illness.Each mid-term exam counts 1/6 of your final grade. The final counts 2/6 and the homeworkscount 1/6.3 SyllabusThe text for the course is Moore, McCabe and Craig’s Introduction to the Practice of Statistics,6th edition 2009, New York: W. H. Freeman. This is referred to as “MM&C” below.In addition to the sections listed on the syllabus, you should always read the introductorysection of each chapter.You should read the assigned sections before each class. My lectures will not slavishly repeatmaterial you can learn from the textbook. Rather I will clarify difficult material and extend thepresentation to additional and more advanced topics. You are responsible for all the material inthe assigned readings as well as the lecture content. Seriously, this will be demanding so you haveto keep up with the reading in the text and not wait until the exam to read.Homework is assigned on Wednesday and due the following Monday.3.1 September 2: Introduction to statistics3.2 September 7: NO CLASS! Labor Day.3.3 September 9: Distributions of Data• MM&C, Ch. 1.1-1.23.4 September 14: Density Curves• MM&C, Ch. 1.33.5 September 16: Bivariate relationships• MM&C, Ch. 2.1, 2.23.6 September 21: Regression• MM&C, Ch. 2.3-2.423.7 September 23: Tables & Causation• MM&C, 2.5-2.63.8 September 28: Producing Data– Experiments & Sampling• MM&C, Ch. 3.1-3.23.9 September 30: EXAM I–Covers Ch. 1-33.10 October 5: Probability I• MM&C, Ch. 4.1-4.23.11 October 7: Probability II• MM&C, Ch. 4.3-4.43.12 October 12: Probability III• MM&C, Ch. 4.53.13 October 14: Probability IV– Extensions• MM&C, None (or review all of chap 4!)3.14 October 19: Sampling distributions I• MM&C, Ch. 5.13.15 October 21: Sampling distributions II• MM&C, Ch. 5.23.16 October 26: Sampling distributions III• MM&C, None, Chapter Review3.17 October 28: EXAM II– Probability and Sampling Distributions3.18 November 2: Introduction to Inference I• MM&C, Ch. 6.1-6.23.19 November 4: Introduction to Inference II• MM&C, Ch. 6.3-6.43.20 November 9: Inference for means I• MM&C, Ch. 7.133.21 November 11: Inference for means II• MM&C, Ch. 7.23.22 November 16: Inference for proportions I• MM&C, Ch. 8.13.23 November 18: Inference for proportions II• MM&C, Ch. 8.23.24 November 23: Two-way tables• MM&C, Ch. 9.1-9.33.25 November 25: Catch-up day• MM&C, None. This is a day to catch up on whatever we fall behind on. Since it is inevitablethat one of the topics in this section will take more time, this is a serious class day, not a freeinvitation to leave early for Thanksgiving!3.26 November 30: One-Way ANOVA• MM&C, Ch. 12.1-12.23.27 December 2: EXAM III– Inference for Means, Proportions & Tables3.28 December 7: Inference for Simple Regression• MM&C, Ch. 10.1-10.23.29 December 9: Multiple Regression I• MM&C, Ch. 11.1-11.23.30 December 14: Multiple Regression II• MM&C, Review Ch. 10-11.3.31 December 19: Comprehensive FINAL EXAM10:05AM-12:05PM,