library(rio)
p1=import("p1.xlsx")

## New names:
## • `` -> `...4`

p1=p1[-1,]
p1=na.omit(p1)

h1=formula(p1$safe~p1$mili)
r1=lm(h1,data=p1)
summary(r1)

## 
## Call:
## lm(formula = h1, data = p1)
## 
## Residuals:
##      Min       1Q   Median       3Q      Max 
## -1.30327 -0.42834  0.04095  0.39354  1.52883 
## 
## Coefficients:
##             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)   1.4761     0.2200   6.709 3.17e-10 ***
## p1$mili       0.5006     0.1149   4.357 2.34e-05 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 0.598 on 161 degrees of freedom
## Multiple R-squared:  0.1055, Adjusted R-squared:  0.09991 
## F-statistic: 18.98 on 1 and 161 DF,  p-value: 2.342e-05

h2=formula(p1$mili~p1$co)
r2=lm(h2,data=p1)
summary(r2)

## 
## Call:
## lm(formula = h2, data = p1)
## 
## Residuals:
##      Min       1Q   Median       3Q      Max 
## -0.67914 -0.21127 -0.07671  0.13529  1.84647 
## 
## Coefficients:
##             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)  1.36901    0.08372  16.351  < 2e-16 ***
## p1$co        0.27573    0.04319   6.385 1.75e-09 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 0.3664 on 161 degrees of freedom
## Multiple R-squared:  0.2021, Adjusted R-squared:  0.1971 
## F-statistic: 40.77 on 1 and 161 DF,  p-value: 1.755e-09

anova(r1,r2)

## Warning in anova.lmlist(object, ...): models with response '"p1$mili"' removed
## because response differs from model 1

## Analysis of Variance Table
## 
## Response: p1$safe
##            Df Sum Sq Mean Sq F value    Pr(>F)    
## p1$mili     1  6.787  6.7874  18.982 2.342e-05 ***
## Residuals 161 57.570  0.3576                      
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1