Test

wc.at <- read.csv("C:\\Users\\Admin\\Downloads\\Data Sets\\Simple Linear Regression\\wc-at.csv")
attach(wc.at)
plot(Waist,AT) # Scatter plot

cor(AT,Waist)    # Correlation ANalysis r (Correlation Coefficient)

## [1] 0.8185578

summary(wc.at)

##      Waist             AT        
##  Min.   : 63.5   Min.   : 11.44  
##  1st Qu.: 80.0   1st Qu.: 50.88  
##  Median : 90.8   Median : 96.54  
##  Mean   : 91.9   Mean   :101.89  
##  3rd Qu.:104.0   3rd Qu.:137.00  
##  Max.   :121.0   Max.   :253.00

sd(Waist)

## [1] 13.55912

var(AT)

## [1] 3282.69

model1 <- lm(AT ~ Waist)
summary(model1)

## 
## Call:
## lm(formula = AT ~ Waist)
## 
## Residuals:
##      Min       1Q   Median       3Q      Max 
## -107.288  -19.143   -2.939   16.376   90.342 
## 
## Coefficients:
##              Estimate Std. Error t value Pr(>|t|)    
## (Intercept) -215.9815    21.7963  -9.909   <2e-16 ***
## Waist          3.4589     0.2347  14.740   <2e-16 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 33.06 on 107 degrees of freedom
## Multiple R-squared:   0.67,  Adjusted R-squared:  0.667 
## F-statistic: 217.3 on 1 and 107 DF,  p-value: < 2.2e-16