Enter
the data from Table 4 into R.
Age <- c(25, 25, 28, 32, 32, 32, 38, 42, 48, 51, 51, 58, 62, 65)Fat <- c(19,28,19,16,24,20,31,20,26,24,32,21,21,30)Cholesterol <- c(180, 195, 186, 180, 210, 197, 239, 183, 204, 221, 243, 208, 228, 269)Table4 <- data.frame('Age'=Age, 'Fat'=Fat,'Cholesterol'=Cholesterol)head(Table4)## Age Fat Cholesterol## 1 25 19 180## 2 25 28 195## 3 28 19 186## 4 32 16 180## 5 32 24 210## 6 32 20 197To
find the correlation matrix, use the cor() command.
cor(Table4)## Age Fat Cholesterol## Age 1.0000000 0.3241428 0.7178106## Fat 0.3241428 1.0000000 0.7778371## Cholesterol 0.7178106 0.7778371 1.0000000The
linear correlation between total cholesterol and Age is 0.718. The linear
correlation between total cholesterol and saturated fat is 0.778. Because the
linear correlation between age and saturated fat (the 2 explanatory variables)
is only 0.324, we are not concerned with multicollinearity.
As
with base R, enter the data in Table 4 as shown above. Mosaic also uses the
cor() command to find the correlation matrix.