class: center, middle, inverse, title-slide # Logistic regression: in-class analysis ### Dr. Olanrewaju Michael Akande ### Sept 24, 2019 --- ## Announcements - Feedback from survey responses - Modified office hours (yet again!). + Mon 3:00 - 4:30pm + Tue 1:45 - 2:45pm + Thur 2:00 - 3:30pm ## Outline - Questions from last lecture - Logistic regression with multiple predictors cont'd: in class analysis of the contaminated wells dataset --- ## The contaminated wells analysis We will do things differently in today's class. We will revisit the contaminated wells analysis we started looking at in the previous class. Recall, that we have the following data. Variable | Description :------------- | :------------ Switch | 1 = if respondent switched to a safe well <br /> 0 = if still using own unsafe well Arsenic | amount of arsenic in well at respondent's home (100s of micro-grams per liter) Dist | distance in meters to the nearest known safe well Assoc | 1 = if any members of household are active in community organizations <br /> 0 = otherwise Educ | years of schooling of the head of household --- ## The contaminated wells analysis - Today, we will work through the analysis together in R. - Treat switch as the response variable and others as potential explanatory variables. - Download the R script for this analysis [here](https://ids-702-f19.github.io/Course-Website/slides/lec-slides/Arsenic.R). - Download the data for this analysis: Go to the class site on Sakai, then go to .hlight[Resources] `\(\rightarrow\)` .hlight[Datasets] `\(\rightarrow\)` .hlight[Class Datasets] `\(\rightarrow\)` .hlight[arsenic.csv]. - You should look to discuss with someone close to you as we go on. - Feel free to ask questions at any point.