Data 621 Discussion 1 -1.3

The dataset prostate is from a study on 97 men with prostate cancer who were due to receive a radical prostatectomy. Make a numerical and graphical summary ofthe data as in the first question.

library(faraway)
## Warning: package 'faraway' was built under R version 3.3.3
data(prostate)
prostate[1:5,]
##       lcavol lweight age      lbph svi      lcp gleason pgg45     lpsa
## 1 -0.5798185  2.7695  50 -1.386294   0 -1.38629       6     0 -0.43078
## 2 -0.9942523  3.3196  58 -1.386294   0 -1.38629       6     0 -0.16252
## 3 -0.5108256  2.6912  74 -1.386294   0 -1.38629       7    20 -0.16252
## 4 -1.2039728  3.2828  58 -1.386294   0 -1.38629       6     0 -0.16252
## 5  0.7514161  3.4324  62 -1.386294   0 -1.38629       6     0  0.37156
attach(prostate)

prostate.lm <- lm(lpsa ~ lcavol+age+lweight+gleason) #how does it treat factor veriables?
summary(prostate.lm)
## 
## Call:
## lm(formula = lpsa ~ lcavol + age + lweight + gleason)
## 
## Residuals:
##      Min       1Q   Median       3Q      Max 
## -1.48679 -0.46467 -0.00243  0.38421  1.95227 
## 
## Coefficients:
##             Estimate Std. Error t value Pr(>|t|)    
## (Intercept) -0.85636    1.04299  -0.821 0.413732    
## lcavol       0.64443    0.07367   8.748 9.82e-14 ***
## age         -0.01320    0.01125  -1.173 0.243783    
## lweight      0.58736    0.16506   3.559 0.000592 ***
## gleason      0.17211    0.12103   1.422 0.158393    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 0.7476 on 92 degrees of freedom
## Multiple R-squared:  0.5981, Adjusted R-squared:  0.5806 
## F-statistic: 34.22 on 4 and 92 DF,  p-value: < 2.2e-16
plot(prostate.lm)