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 has a strong positive relationship with price.

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

Withouth knowing the context you cannot know the causation, so not necessarily.

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

The confounding variable is age with home price.

Q4 What factors have strong negative correlation with home price?

No strong negative correlations with home price

Q5 What factors have little correlation with home price?

Lot size has the weakest 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?

No. Put it on a scatter plot.

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.

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.

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

Q10 Use the correct slug.