What predictors represent majority of explainable variance

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Question: Problem: The Texas A & M University Real Estate Center collects home listings data in Texas. One of the metrics is the number of months a home is listed until it sells (Texas A & M University, n.d.). A stagnant home listing is not beneficial to anyone in the process, typically impacting the individuals selling their dwellings the most. Opportunities to reduce the wait-time-to-sales for a particular home will reduce the potentially negative impact on the individuals selling their homes.

Using the data consolidated by Texas A & M University (n.d.), what predictors represent the majority of the explainable variance when predicting the number of months a property will remain in inventory considering the quantity of real estate sales, the monetary value of those sales, and the average sale price, the median sale price, and the quantity of properties in the inventory, the year, and the month in the data set?

Objective: Use a random forest model as the analysis method to answer the research question. Additionally, consider how this research may help a realtor reduce the amount of time that their listings remain in their inventory when you discuss and present your findings.

Reference no: EM132812845

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