{"content":[{"text":"2","bbox":{"left":0.845462,"top":0.094683,"width":0.009552000000000005,"height":0.015109999999999998}},{"text":"I recently experimented with allowing participants to use either Stata or R and found, \n from student evaluations, and from both R and Stata users that the support for both \n pieces of software was both distracting and unnecessary. Stata users found that it was \n reasonably easy to pick up R for the purposes of the course. Further, Some of the speciﬁc \n software used in the course does not exist (or exist in the same useful way) in Stata. I \n found that the implementation in Stata often required some programming (loops, macros, \n etc...) and that was a threshold many participants did not want to cross. Thus, R will \n be the only oﬃcially supported software. That said, I have Stata code for many of the \n examples in class and would be happy to share with interested participants. If you want \n to use this course as an opportunity to strengthen your R skills, but have little familiarity \n with that software, you should take the R workshop that I teach in the ﬁrst three weeks \n of the ﬁrst session.","bbox":{"left":0.117647,"top":0.159465,"width":0.737492,"height":0.215747}},{"text":"If you’re one of those “glutton-for-punishment” types, you may also ﬁnd it useful \n to learn LATEX. LATEXis a system for typesetting documents. People ﬁnd it most use- \n ful for typesetting documents that are heavy on mathematical notation, but this is just \n the tip of the iceberg. LATEXhas its own bibliographic software (BibTEX) and will au- \n tomatically build (and re-build) tables of contents, lists of ﬁgures and lists of tables. It \n also automatically numbers (and re-numbers when necessary) tables, ﬁgures and equa- \n tions, changing appropriately formed references to those objects when table, ﬁgure or \n equation numbers change. Best of all, common LATEXtypesetting engines are free (see \n http://www.latex-project.org/ftp.html for links to the software appropriate for \n your OS). Everything I present in class is written in LATEX; speciﬁcally, the slides are \n all made with a package called “Beamer”. There are some nice literate programming \n tools (Sweave and StatWeave) that integrate LATEX, R and Stata as well. Further, there \n are those who see LATEXas a sort of secret handshake for nerds. So, if you want to be one \n of the “cool” kids, then you should deﬁnitely try it; everyone else is doing it.","bbox":{"left":0.117647,"top":0.396581,"width":0.7374719999999999,"height":0.2522259999999999}},{"text":"3","bbox":{"left":0.117647,"top":0.679137,"width":0.01580899999999999,"height":0.021758000000000055}},{"text":"Course Text(s)","bbox":{"left":0.16513,"top":0.679137,"width":0.20661300000000005,"height":0.021758000000000055}},{"text":"No one text eﬀectively presents all of the material that will be covered in this course. \n That said, much of the material is covered (and covered well) in:","bbox":{"left":0.117647,"top":0.717306,"width":0.7374080000000001,"height":0.03334899999999996}},{"text":"Fox, John. (2015) Applied Regression Analysis and Generalized Linear Models. \n Thousand Oaks, CA: Sage Publications, Inc.","bbox":{"left":0.116926,"top":0.77657,"width":0.670832,"height":0.03334999999999999}},{"text":"3rd","bbox":{"left":0.799446,"top":0.774867,"width":0.023507000000000056,"height":0.016813999999999996}},{"text":"ed.","bbox":{"left":0.831583,"top":0.77657,"width":0.023441000000000045,"height":0.015109999999999957}},{"text":"Fox, John and Sanford Weisberg. (2011) An R Companion to Applied Regression. \n ed. Thousand Oaks, CA: Sage Publications, Inc.","bbox":{"left":0.116927,"top":0.83129,"width":0.699581,"height":0.03334999999999999}},{"text":"2nd","bbox":{"left":0.828928,"top":0.829585,"width":0.025278000000000023,"height":0.016815000000000024}},{"text":"The R Companion is a great book for those currently learning R. I would highly recom- \n mend getting the recently update and expanded second edition. This is widely recognized \n as one of the best ways for Social Scientists to get into R. The Applied Regression book","bbox":{"left":0.117647,"top":0.886008,"width":0.737482,"height":0.051589999999999914}}],"images_bbox":[],"images_bbox_not_text_overlap":[]}