a.)
library(ISLR2)
#Numerical Summary
summary(Weekly)
## Year Lag1 Lag2 Lag3
## Min. :1990 Min. :-18.1950 Min. :-18.1950 Min. :-18.1950
## 1st Qu.:1995 1st Qu.: -1.1540 1st Qu.: -1.1540 1st Qu.: -1.1580
## Median :2000 Median : 0.2410 Median : 0.2410 Median : 0.2410
## Mean :2000 Mean : 0.1506 Mean : 0.1511 Mean : 0.1472
## 3rd Qu.:2005 3rd Qu.: 1.4050 3rd Qu.: 1.4090 3rd Qu.: 1.4090
## Max. :2010 Max. : 12.0260 Max. : 12.0260 Max. : 12.0260
## Lag4 Lag5 Volume Today
## Min. :-18.1950 Min. :-18.1950 Min. :0.08747 Min. :-18.1950
## 1st Qu.: -1.1580 1st Qu.: -1.1660 1st Qu.:0.33202 1st Qu.: -1.1540
## Median : 0.2380 Median : 0.2340 Median :1.00268 Median : 0.2410
## Mean : 0.1458 Mean : 0.1399 Mean :1.57462 Mean : 0.1499
## 3rd Qu.: 1.4090 3rd Qu.: 1.4050 3rd Qu.:2.05373 3rd Qu.: 1.4050
## Max. : 12.0260 Max. : 12.0260 Max. :9.32821 Max. : 12.0260
## Direction
## Down:484
## Up :605
##
##
##
##
#Graphical Summary
pairs(Weekly)
#Subset the numeric columns
numeric_cols <- c("Lag1", "Lag2", "Lag3", "Lag4", "Lag5", "Volume", "Today")
cor_matrix <- cor(Weekly[, numeric_cols])
cor_matrix
## Lag1 Lag2 Lag3 Lag4 Lag5
## Lag1 1.000000000 -0.07485305 0.05863568 -0.071273876 -0.008183096
## Lag2 -0.074853051 1.00000000 -0.07572091 0.058381535 -0.072499482
## Lag3 0.058635682 -0.07572091 1.00000000 -0.075395865 0.060657175
## Lag4 -0.071273876 0.05838153 -0.07539587 1.000000000 -0.075675027
## Lag5 -0.008183096 -0.07249948 0.06065717 -0.075675027 1.000000000
## Volume -0.064951313 -0.08551314 -0.06928771 -0.061074617 -0.058517414
## Today -0.075031842 0.05916672 -0.07124364 -0.007825873 0.011012698
## Volume Today
## Lag1 -0.06495131 -0.075031842
## Lag2 -0.08551314 0.059166717
## Lag3 -0.06928771 -0.071243639
## Lag4 -0.06107462 -0.007825873
## Lag5 -0.05851741 0.011012698
## Volume 1.00000000 -0.033077783
## Today -0.03307778 1.000000000