8.1 Correlation plots
Ben Tuttle
10/15/2019
In this exercise you will learn to visualize the pairwise relationships between a set of quantitative variables. To this end, you will make your own note of 8.1 Correlation plots from Data Visualization with R.
Q1 What factors have positve correlation with home price?
Living area, rooms, bathrooms, landvalue, pctCollege and lot size all have postive correlations with home price. Not all of them are strong through.
Q2 What factors have strong positve correlation with home price?
The living area has the strongest positive correlation with home price at 0.71. The second strongest is bathrooms at 0.6. Thirdly, landvalue also has a strong positive correlation with price which is demonstrated on the chart as 0.58.
Q3 What factors have negative correlation with home price?
Age has a negative correalation with home price at -0.19, meaning that the older the house the cheaper the price, however this is a weak correlation.
Q4 What factors have strong negative correlation with home price?
Age is the only factor that has a negative correlation with price.
Q5 What set of two variables has the highest positive Pearson Product-Moment correlation coefficient? What set of two variables has the greatest negative Pearson Product-Moment correlation coefficient?
Rooms and livingArea are the two variables that have the gretaest negative.
Q6 What set of two variables has the Pearson Product-Moment correlation coefficent that is closest to zero? Would you be sure that the two variables are not related at all? What would you do to check?
Q7 Plot correlation for CPS85 in the same way as above. Repeat Q1-Q6.
Hint: The CPS85 data set is from the mosaicData package. Explain wage instead of home rice.
Q8 Hide the messages, the code and its results on the webpage.
Hint: Use message, echo and results in the chunk options. Refer to the RMarkdown Reference Guide.