8.1 Correlation plots
Janel Bachand
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?
Factors that have positive correlation with home price are fireplaces, number of bedrooms, amount of livng space, and the number of rooms within the house. The more of each in the house, the higher the price can be.
Q2 What factors have strong positve correlation with home price?
Factors that have strong positive correlation with home prices are the number amount of bathrooms, and the amount of living area space.
Q3 What factors have negative correlation with home price?
Factors that have negative correlation with home price is age because the older the home is, the less expensive it can be.
Q4 What factors have strong negative correlation with home price?
There are no factors that have a strong negative correlation with home 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?
The two variables that has the highest positive Pearson Product-Moment correlation coeeficient is living area and rooms. The two variables that has the greatest negative Pearson Product-Moment correlation coefficient is bathrooms and age.
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?
The two or more variables that has the correlation coefficient closest to zero is landvalue and age, and age and lotsize. They are very close to zero so there is little to no linear relationship between the two. 
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 price.
1. Factors that have positive correlation with wage is experience, age, and education. 2. There are no factors that have a strong positive correlation with wage. 3. There are no Factors that have a negative correlation with wage. 4. There are no factors that have a strong negative correlation with wage. 5. The two variables that has the highest positive correlation is experience and age. The two variables that has the highest negative correlation is experience and education. 6. The two variables that has the correlation coefficient closest to zero is experience and age. The set of variables is very close to zero therefore there is little to no linear relationship. 
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.