Feel free to either give me the steps to do the following tasks in JMP or I can provide the dataset if there is a way.

Using the RidingMowers.jmp data which contains information about who the best sales prospects are for an intensive sales campaign. The INCOME (in 1000s) and the LOT_SIZE (in 1000 ft²) for a random sample of 24 homes is listed along with whether those homes had a riding lawn mower. Don't use validation. Set Target = non-owner.

- What percentage of households in the study were owners of a riding mower? Hint: You use descriptive stats

- Color the observations that are owners purple. Create a scatterplot of Income vs. Lot size. Which class seems to have the higher income? Which class seems to have the larger lot size?

- Run a logistic regression predicting ownership with INCOME and LOT_SIZE. Save the Probability formula in the dataset. Create a confusion matrix. What is Error Rate?

- What are the odds that a household with $60,000 income and a lot size of 20,000 sq ft is a non-owner? (Note: Keep all your decimal places to get accuracy)

- Assuming a cutoff of .5, create a rule for classification of non-owner based on the odds. What is the classification for a household with $60,000 income and a lot size of 20,000 sq ft?

- What is the minimum income that a household with 16,000 sq ft lot size should have before it is classified as an owner?

Below is what's in the dataset. Just three columns with Income, Lot-Size, and Ownership.

\begin{tabular}{|r|r|r|l|} \hline \hline & Income & Lot_Size & \multicolumn{1}{|c|}{ Ownership } \\ \hline 1 & 60 & 18.4 & owner \\ \hline 2 & 85.5 & 16.8 & owner \\ \hline 3 & 64.8 & 21.6 & owner \\ \hline 4 & 61.5 & 20.8 & owner \\ \hline 5 & 87 & 23.6 & owner \\ \hline 6 & 110.1 & 19.2 & owner \\ \hline 7 & 108 & 17.6 & owner \\ \hline 8 & 82.8 & 22.4 & owner \\ \hline 9 & 69 & 20 & owner \\ \hline 10 & 93 & 20.8 & owner \\ \hline 11 & 51 & 22 & owner \\ \hline 12 & 81 & 20 & owner \\ \hline 13 & 75 & 19.6 & non-owner \\ \hline 14 & 52.8 & 20.8 & non-owner \\ \hline 15 & 64.8 & 17.2 & non-owner \\ \hline 16 & 43.2 & 20.4 & non-owner \\ \hline 17 & 84 & 17.6 & non-owner \\ \hline 18 & 49.2 & 17.6 & non-owner \\ \hline 19 & 59.4 & 16 & non-owner \\ \hline 20 & 66 & 18.4 & non-owner \\ \hline 21 & 47.4 & 16.4 & non-owner \\ \hline 22 & 33 & 18.8 & non-owner \\ \hline 23 & 51 & 14 & non-owner \\ \hline 24 & 63 & 14.8 & non-owner \\ \hline \end{tabular}