rm(list=ls())
library(car)
attach(Bfox)
time <- as.numeric( rownames(Bfox))
Bfox.new <- cbind(Bfox, time)
names(Bfox.new)
# [1] "partic" "tfr"    "menwage" "womwage" "debt" "parttime" "time"

# 1.
# (a)
lm.out <- lm(partic ~ ., data=Bfox.new)
summary(lm.out)
# Call:
# lm(formula = partic ~ ., data = Bfox.new)
#
# Residuals:
# Min    1Q Median    3Q    Max
# -0.82202 -0.29852 0.01137 0.38882 1.01697
#
# Coefficients:
# Estimate Std. Error t value Pr(>|t|)
# (Intercept) 5.043e+01 1.913e+02 0.264 0.79443
# tfr       2.618e-04 4.093e-04 0.640 0.52874
# menwage -4.150e-02 1.478e-01 -0.281 0.78133
# womwage    5.724e-02 1.758e-01 0.325 0.74776
# debt       6.689e-02 1.558e-02 4.294 0.00027 ***
# parttime 6.865e-01 8.185e-02 8.387 1.89e-08 ***
# time    -1.806e-02 9.944e-02 -0.182 0.85745
# ---
# Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
#
# Residual standard error: 0.5333 on 23 degrees of freedom
# Multiple R-squared: 0.9936, Adjusted R-squared: 0.992
# F-statistic: 597.8 on 6 and 23 DF, p-value: < 2.2e-16

1. (in pounds) given below of 36 cans of regular Coke. Start the fi...