r discussion question and need the explanation and answer to help me learn.
Sales of Riding Mowers.
A company that manufactures riding mowers wants to identify the best sales prospects for an intensive sales campaign. In particular, the manufacturer is interested in classifying households as prospective owners or nonowners on the basis of Income (in $1000s) and Lot Size (in 1000 ft2). The marketing expert looked at a random sample of 24 households, given in the dataset RidingMowers.
Use the following code to load the data
mowers.df <- mlba::RidingMowers What percentage of households in the study were owners of a riding mower? Create a scatter plot of Income vs. Lot Size using color or symbol to distinguish owners from nonowners. From the scatter plot, which class seems to have a higher average income, owners or nonowners? Use all the data to fit a logistic regression of ownership on the two predictors. Note you can either use the train function by setting the trainControl method to "none" or use the glm function. Among nonowners, what is the percentage of households classified correctly? To increase the percentage of correctly classified nonowners, should the threshold probability be increased or decreased? What are the odds that a household with a $60K income and a lot size of 20,000 ft2 is an owner? What is the classification of a household with a $60K income and a lot size of 20,000 ft2? Use threshold = 0.5. Requirements: