LL3

For my learning log I reviewed the women data.

attach(women)

For this step I learned how to relabel each axis and added the line of best fit which is located in the section of code after this one.

plot(height, weight, ylab = "Weight in pounds",
     xlab = "height in inches", 
     main = "Height vs. Weight in Women")
abline(-87.52,3.45)

mymod <- lm(weight ~ height)

mymod

## 
## Call:
## lm(formula = weight ~ height)
## 
## Coefficients:
## (Intercept)       height  
##      -87.52         3.45

In this next step, I learned how to calulate the residuals of my data set and plot them in a histogram to look for skewness.This data does not look too skewed.

myresids <- mymod$residuals
hist(myresids)

Next I learned how to make a qq plot and the data does not seem too far away from the line.

qqnorm(myresids)
qqline(myresids)

Next I checked to see the vertical spread. This seems appropriate.

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

Lastly, I printed out a data summary incase anymore data is necessary for the viewer of my data.

summary(mymod)

## 
## Call:
## lm(formula = weight ~ height)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -1.7333 -1.1333 -0.3833  0.7417  3.1167 
## 
## Coefficients:
##              Estimate Std. Error t value Pr(>|t|)    
## (Intercept) -87.51667    5.93694  -14.74 1.71e-09 ***
## height        3.45000    0.09114   37.85 1.09e-14 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.525 on 13 degrees of freedom
## Multiple R-squared:  0.991,  Adjusted R-squared:  0.9903 
## F-statistic:  1433 on 1 and 13 DF,  p-value: 1.091e-14