For my third learning log, I took a look at the dataset comparing women’s heights and weights.

Next, I plotted the data, comparing womens heights and weights. I chose to use their heights as a predictor for their weights.

plot(height, weight)

This shows that there is a trend, and a positive one at that.The trend looks like it may not be linear, but it seems very close from this perspective.

The next step I took was in making a regression line and plotting it ontop of the graph above.

myWmod <- lm(weight ~ height)
myWmod    #used to find y intercept and slope
## 
## Call:
## lm(formula = weight ~ height)
## 
## Coefficients:
## (Intercept)       height  
##      -87.52         3.45
plot(height, weight)
abline(myWmod)

This graph shows us more clearly that womens heights and weights dont have a perfectly liniar relationship. To help show this even clearer, here is a plot of the residuals against women’s height.

myWresids <- myWmod$residuals


plot(myWmod$residuals ~ height)
abline(0,0)

This clearly shows that there is a parabolic nature when comparing womens height and their weight