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.

##            price lotSize   age landValue livingArea pctCollege bedrooms
## price       1.00    0.16 -0.19      0.58       0.71       0.20     0.40
## lotSize     0.16    1.00 -0.02      0.06       0.16      -0.03     0.11
## age        -0.19   -0.02  1.00     -0.02      -0.17      -0.04     0.03
## landValue   0.58    0.06 -0.02      1.00       0.42       0.23     0.20
## livingArea  0.71    0.16 -0.17      0.42       1.00       0.21     0.66
## pctCollege  0.20   -0.03 -0.04      0.23       0.21       1.00     0.16
## bedrooms    0.40    0.11  0.03      0.20       0.66       0.16     1.00
## fireplaces  0.38    0.09 -0.17      0.21       0.47       0.25     0.28
## bathrooms   0.60    0.08 -0.36      0.30       0.72       0.18     0.46
## rooms       0.53    0.14 -0.08      0.30       0.73       0.16     0.67
##            fireplaces bathrooms rooms
## price            0.38      0.60  0.53
## lotSize          0.09      0.08  0.14
## age             -0.17     -0.36 -0.08
## landValue        0.21      0.30  0.30
## livingArea       0.47      0.72  0.73
## pctCollege       0.25      0.18  0.16
## bedrooms         0.28      0.46  0.67
## fireplaces       1.00      0.44  0.32
## bathrooms        0.44      1.00  0.52
## rooms            0.32      0.52  1.00

Q1 What factors have strong positve correlation with home price?

The factors are the living area and number of bathrooms. There is no corrilation with wage.

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

the correlation does not mean the varriables cuase the price. No there is not one.

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

The age would be the cofounding varriable if there is one. No there s no cofounding variable because nothing sounds strange.

Q4 What factors have strong negative correlation with home price?

There are no strong negitive correlation. there is no variable that has a negitive correlation with wage.

Q5 What factors have little correlation with home price?

The factors are age, lot size, and pct college have little corrilation to the price of the home. Experience has the smallest corrilationship with wage.

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 because there is still a possibility that there is a relationship and corrilation even if its weak. No there is no coeffiencent at all.

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.

##       wage  educ exper   age
## wage  1.00  0.38  0.09  0.18
## educ  0.38  1.00 -0.35 -0.15
## exper 0.09 -0.35  1.00  0.98
## age   0.18 -0.15  0.98  1.00

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.