{"content":[{"text":"Regression Analysis III: Advanced Methods","bbox":{"left":0.251359,"top":0.070178,"width":0.528711,"height":0.030083}},{"text":"1","bbox":{"left":0.845462,"top":0.094683,"width":0.009552000000000005,"height":0.015109999999999998}},{"text":"Syllabus - Summer 2015","bbox":{"left":0.347995,"top":0.117771,"width":0.33552200000000004,"height":0.021758000000000013}},{"text":"Instructor: \n Dave Armstrong \n Department of Political Science \n University of Wisconsin - Milwaukee","bbox":{"left":0.117647,"top":0.202772,"width":0.30578999999999995,"height":0.06982900000000003}},{"text":"e: dave@quantoid.net \n Oﬃce Hours: 1:30PM-2:30PM M-F (or by appointment) \n Course website: http://www.quantoid.net/ICPSRReg3.html","bbox":{"left":0.117647,"top":0.280276,"width":0.521134,"height":0.05160300000000001}},{"text":"1","bbox":{"left":0.117647,"top":0.389527,"width":0.01580899999999999,"height":0.021758}},{"text":"Overview and Course Objectives","bbox":{"left":0.165129,"top":0.389527,"width":0.453244,"height":0.021758}},{"text":"The Regression III course takes a considerably diﬀerent form than the ﬁrst two re- \n gression courses at the Summer Program. This course will hopefully prepare you for the \n things you will encounter when you (attempt to) publish quantitative work with linear \n models. Initial linear model classes focus on the assumptions and theoretical consider- \n ations of linear models and generally walk you through estimation and interpretation. \n Good courses also deal with diagnostics, though these often get less time than they \n should. Further, it is not always obvious what violations of these assumptions will lead \n to in practical terms. This course will provide you with a systematic approach to assess- \n ing, ﬁxing and presenting your linear model results. Though we focus almost exclusively \n on the linear model (we will allude to nonlinear models occasionally), the logic we follow \n will be helpful in dealing with nonlinear models as well.","bbox":{"left":0.117647,"top":0.427695,"width":0.737498,"height":0.19750799999999996}},{"text":"This is a class that deals exclusively with observational data - those not collected in \n experimentally controlled environments. As such, we will spend little time on ANOVA \n and no time at all talking about concerns that are speciﬁc to the analysis of experimental \n data.","bbox":{"left":0.117647,"top":0.646572,"width":0.73746,"height":0.06982999999999995}},{"text":"2","bbox":{"left":0.117647,"top":0.746731,"width":0.01580899999999999,"height":0.021757999999999944}},{"text":"Requirements","bbox":{"left":0.165129,"top":0.746731,"width":0.1908,"height":0.021757999999999944}},{"text":"This course is a practical, data-analytic extension of what you learned in your depart- \n ment’s linear models class or the Regression II class at the ICPSR Summer Program. As \n such, I assume you are familiar with the types of things taught in these courses - Gauss- \n Markov assumptions, properties of OLS estimators, and statistical inference for linear \n model coeﬃcients. While I assume this knowledge exists, I will spend time reviewing \n these ideas brieﬂy in class. If you are not sure where you belong in the series of linear \n models courses at the Summer Program, please see me or the Summer Program director \n and we will make sure you end up the most appropriate class.","bbox":{"left":0.117647,"top":0.7849,"width":0.737455,"height":0.14278799999999991}}],"images_bbox":[],"images_bbox_not_text_overlap":[]}