Homework 3 Code

Problem 1a

View(marathon)
is.data.frame(data)

## [1] FALSE

lm(time ~ age, data = marathon)

## 
## Call:
## lm(formula = time ~ age, data = marathon)
## 
## Coefficients:
## (Intercept)          age  
##     127.987        2.636

summary(model)

## 
## Call:
## lm(formula = time ~ age, data = marathon)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -64.078 -23.078  -1.896  23.195  53.376 
## 
## Coefficients:
##             Estimate Std. Error t value Pr(>|t|)    
## (Intercept) 127.9873    19.3001   6.631 5.48e-08 ***
## age           2.6364     0.3677   7.170 9.50e-09 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 29.92 on 41 degrees of freedom
## Multiple R-squared:  0.5563, Adjusted R-squared:  0.5455 
## F-statistic: 51.41 on 1 and 41 DF,  p-value: 9.501e-09

anova(model)

## Analysis of Variance Table
## 
## Response: time
##           Df Sum Sq Mean Sq F value    Pr(>F)    
## age        1  46026   46026  51.406 9.501e-09 ***
## Residuals 41  36709     895                      
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

Problem 1l

mean(marathon$age)

## [1] 51

sd(marathon$age)

## [1] 12.55654