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?

the larger the living area the larger the home price. As well as the more bathrooms the greater the price.

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

correlation does not always mean causation, without background info there is no way to know. however in this sceanario there does seem to be a correlation and causation effect.

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

I do not think that there are any confounding variable within this data set.

Q4 What factors have strong negative correlation with home price?

there are not any strong negative correlations within this data set. this is because there are no correlations stronger than -.60.

Q5 What factors have little correlation with home price?

fireplaces, pctCollege, lot size, and age, have little correlation with home price. this is because the correlation between the to is less than .40.

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

One can not be sure there is no correlationship even with a weak realtionship. there could be a non linear relationship. this can be checked with a scater 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.

  1. there is no strong positive correlation with wage. There is always a poitive correlation however non of it is a strong correlation.
  2. N/A
  3. because there is no strong relationship there is no need to find a confounding variable.
  4. there is no negative correlation between wage and anything else.
  5. All of the factors have weak linear correlation with wage. this is because non of the factors have a correlation greater than .4.
  6. one can not be sure that there is no correlation at all there could infact be a strong non linear correlation. this could be checked with a scatterplot.

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.