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?

Fireplaces, bedrooms, livingArea, and rooms have a positive correlation with home price.

Q2 What factors have strong positve correlation with home price?

The livingArea has a strong positive correlation with home price.

Q3 What factors have negative correlation with home price?

Age has a negative correlation with home price.

Q4 What factors have strong negative correlation with home price?

No factors 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?

LivingArea and rooms has the highest positive correlation coefficient. Bathrooms and age has the strongest negative correlation coefficient.

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. Exper and age.
  2. None, because they are both less than .4.
  3. None
  4. None
  5. Exper and age has the highest positive correlation coefficient. Exper and educ has the strongest negative correlation coefficient.
  6. exper and wage has the coefficient closest to zero. Create a scatterplot to find out weather they are related.

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.