least one slide in a bullet point format should contain a summary of the most important things

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Problem 2: Your goal is to conduct an exploratory data analysis (EDA) of the Ames Housing dataset. Keep the following questions in mind: • Which predictors may be useful in predicting house prices? • Could you gain any insight by looking at the relationship between the predictors? You’ll also get to know the data by doing EDA. This data will also be used for the competition (HW 6) and for your project. The data comes from https://www.kaggle.com/c/house-prices-advanced-regression-techniques. (You are welcomed to explore the site for ideas.) Use fairly cleaned-up and modified version of the data on Canvas: train_modified.csv. You should take 5-10 minutes to go over the data description file before you do anything. There are a few categorical variables that have been coded as numeric. You’ll have to tell JMP to treat them as categorical. The very last column, “SalePrice”, is the response variable. The “Id” column is not a predictor. After completing your EDA, summarize your results using PowerPoint or a similar presentation software (but convert to pdf format): • You can assume that the audience is familiar with statistical graphical tools and tables. • You should have some numerical or graphical summaries showing the relationship between your chosen predictors and the response. You will not be able to choose every single predictor. Just show the ones that look most promising to you. My recommendation is that you look at the relationship between the response and at least 7 predictors, and then choose the 3 most promising ones. • You should have a few numerical or graphical summaries that show the relationship between the predictors. Reporting about 3 pairs of predictors is reasonable. • At least one slide in a bullet point format should contain a summary of the most important things you learned.

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