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 strong positve correlation with home price?

Living Area and Bathrooms

Q2 Continued from Q1: Does the strong correlation mean the variable causes home price to go up and down?

It causes price to go up

Q3 Continued from Q1: Do you think there is a confounding variable?

I do not believe there is a cofounding variable

Q4 What factors have strong negative correlation with home price?

None, age is the only factor with a negative correlation to price, but it is a weak correlation

Q5 What factors have little correlation with home price?

Lot size has a weak correlation with home price.

Q6 Simply based on the correlation coefficient, would you be sure that there is no relation at all? What would you do to check?

There may still be a correlation just not in a linear fashion

Q7 Plot correlation for CPS85 in the same way as above. Repeat Q1-Q6.

1. There are no variables with a strong positive correlation with wage, education does however have a weak correlation with wage. 2.Positive correlation would mean that wages go up with increased education. 3.I do not believe that there is a cofounding variable. 4.There are no variables with a negative correlation with wage. 5.Expertise has little to no correlation to wage, only having a correlation coefficient of 0.09 . 6. There may still be a correlation just not in a linear fashion

Q8 Hide the messages, the code and its results on the webpage.

Q9 Display the title and your name correctly at the top of the webpage.

Q10 Use the correct slug.