Stat 418 – Analysis of Cross Classified DataIntroductionsWhat is Categorical Data AnalysisSlide 4What is Categorical Data Analysis?Slide 6Slide 7ReadingStat 418 – Analysis of Cross Classified DataIntroductionsRollSyllabus/webpages highlightsCourse technologyLab usage rulesDay 1 HandoutNote: HW 1 is posted in PolyLearn (due Friday)What is Categorical Data AnalysisIf you buy a used car, your best bet is an orange one.Kaggle: Matched previously separate data sets on buyers, colors, and after-purchase problems. They figured out that if a car’s original owner chose an odd color, the car was most likely a means of self-expression. That self-identification raises the odds that the owner cared more than usual for the vehicle.What is Categorical Data AnalysisThe best way to tell if a person is likely to make their flight is if he or she has preordered a vegetarian meal.Kaggle: The psychology of making that trip personal, by knowing your meal is on it, makes you more likely to get to the plane on time.What is Categorical Data Analysis?CellTel (African model phone company): They could predict the location of impending massacres in the Congo, because there were spikes in the sale of prepaid phone cardsMore calls around the planning or fleeing of the massacre? In fact, prepaid cards were denominated in dollars, not the local currency. People, sensing impending chaos, wanted to have something valuable they could carry with them that was protected against local inflation.What is Categorical Data Analysis?If you watch a movie that ends in a number, you will probably think less of it than if it had a different title. Numbers usually indicate sequels, and most sequels are bad.But:“The physicists and electrical engineers are better at it a lot of the time. They are grounded in real things, and they don’t obsess over which regression model they should use.”What is Categorical Data Analysis?What is data?What is categorical data?Types of categorical data:Binary (two outcomes)Nominal (unordered categories)Ordinal (ordered categories)Reading Be reading Chapter 1For tomorrow:Review binomial distributionDownload