A company that manufactures riding mowers wants to identify the best sales prospects for an intensive sales campaign

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 of the basis of Income (in $1000s) and Lot Size (in 1000ft2). The marketing expert looked at a random sample of 34 households, given in the file Riding Mower. Use the data to fit a logistic regression of ownership on the two predictors in SPSS and answer the following questions.

I. Preparing the data sets:

a) Split the data into training and validation datasets using a 70%:30% ratio.

b) Why should the data be partitioned into training and validation sets? What will the training set be used for? What is the validation set used for?

II. Pre-processing:Explore the data set by applying appropriate instruments depending on the data type: descriptive statistics, boxplots and histograms. Based on these methods describe the data and make relevant conclusions. Does the data need cleaning? Can you identify any missing values and outliers in data? Why?