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Unformatted text preview: 1 Regression with categorical independent variables ESM 206B 15 Jan. 2008 2 Types of variables Numeric Continuous Observations can take on, in principle, any real number Infinite # of possible values between 1 and 10 Discrete Observations can take on, in principle, any integer 10 possible values between 1 and 10 Categorical Dichotomous: Male/Female Preregulation/Postregulation Island/Mainland Nominal (nom = named) Continent Political party Soil type Ordinal (ord = ordered) Survey response: strongly disagree, disagree, neutral, agree, strongly agree Size classifications: small, medium, large Income ranges 3 Dummy variables How can we handle categorical explanatory (independent) variables in a regression? Answer: make a dummy! Dichotomous: zero or one Categorical with q categories: q1variables each scored zero or one (examples to follow) 4 Alien Species Exotic species cause economic and ecological damage Not all countries equally invaded Want to understand characteristics of country that make it more likely to be invaded. Well measure invasiveness as fraction of species that are Alien Two hypotheses 1. Human population density plays a role in a countrys invasiveness. 2. Island nations are more invaded than mainland nations. 5 200 400 600 800 1000 1200 0.0 0.1 0.2 0.3 0.4 0.5 0.6 Pop_dens Prop_exotic Mainland Island 0.0 0.1 0.2 0.3 0.4 0.5 0.6 Island Prop_exotic 6 A Simple Model ISL is a Dummy variable , coded 0 if mainland, 1 if island Dummy changes intercept (explain). i i i i P ISL A + + + = 3 2 1 7 Call: lm(formula = Prop_exotic ~ Pop_dens + Island, data = ExoticSpecies) Coefficients: Estimate Std. Error t value Pr(>t) (Intercept) 7.944e02 2.708e02 2.934 2....
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 Spring '08
 KENDALL,BERKLEY
 Environmental Science

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