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 correlation to home price.

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

Yes, if two variables have a strong correlation, they directly affect each other. If Living Area goes down, it’s likely that home price also goes down. If Living Area goes up, it’s likely that home price will also go up.

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

bathrooms could be a confounding variable in this case. Bathroom sq. footage contributes to living area. The more living area in a home, the more bathrooms there will be most likely, which will cause the home price to increase.

Q4 What factors have strong negative correlation with home price?

The only factor that has a strong negative correlation to home price is age. This is because the age of buyer/seller does not matter in the sale of a home.

Q5 What factors have little correlation with home price?

Factors that have little correlation to home price include pctCollege and lot size. I will not include age as it has a strong negative correlation to 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?

Just looking at the correlation coefficient, you can be sure that there is a relationship between two factors. Of the correlation coefficient is exactly 0, you can be sure that there is no relation at all. Even if the coefficient is .01 or -.01, it still indicates that there is a very small correlation between two factors.

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

  1. The only factor that has a strong positive correlation to Wages is education.
  2. Yes, the strong correlation between wages and education means that difference in education causes a difference in wages.
  3. I do not think there is a confounding variable here, because both of the other factors have negative correlations to wages.
  4. There are no factors that have a negative correlation to wages.
  5. Factors that have little correlation with Wages include experience and age.

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

Done.

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

Q10 Use the correct slug.