# BI376 Lab 9/14
*Collaborators: Taylor and Youmian*

## 1)

I used ggplot to create boxplots of chick weight by day:


My code was a pretty standard ggplot command. I used the ```%in%``` operator to subset only days 0, 10, and 21.

p <- ggplot(subset(ChickWeight,
    Time %in% c(0,10,21)), aes(x=as.factor(Time),
    y=log10(as.numeric(weight)))) +
    geom_boxplot() +
    ggtitle("Chick Weight by Day") +
    xlab('Day') +
    ylab('log10 Weight')
p

**1a)**
I separated the diet groups by including a ```facet_wrap```.

p2 <- ggplot(subset(ChickWeight, Time %in% c(0,10,21)),
    aes(x=as.factor(Time), y=log10(as.numeric(weight)))) +
    geom_boxplot() + facet_wrap(.~Diet) +
    ggtitle("Chick Weight by Diet and Day") +
    xlab('Day') +
    ylab('log10 Weight')
p2


**1b)**

To better indicate individual values and distributions, I changed by plots to violins and added jittered points.

p3 <- ggplot(subset(ChickWeight, Time %in% c(0,10,21)), aes(x=as.factor(Time), y=log10(as.numeric(weight)))) +
  geom_violin(color = 'grey', size = 1, trim = FALSE, alpha = 0.75, draw_quantiles = 0.5) +
  facet_wrap(.~Diet) +
  geom_jitter(position = position_jitter(width = 0.2, height = 0),color = 'darkblue', size=.3, alpha=0.8)+
  ggtitle("Chick Weight by Diet and Day") +
  xlab('Day') +
  ylab('log10 Weight') +
  theme_bw()
p3


## 2)

I used ```runif``` and ```rnorm``` to generate my random values.

a <- runif(n=100, min = 0, max = 100)
b <- rnorm(n=100, mean = 50, sd = 10)

p4 <- ggplot(data.frame(a,b),aes(x=a, y=b)) +
    theme_bw() +
    geom_point(size = 2, alpha = 0.5) +
    stat_smooth(method=lm) +
    ggtitle("Random Plot")
p4


**2a, 2b)**

I used the ```lm``` command to find the slope and added text to the plot with an ```annotate``` call.

p5 <- p4 + annotate(geom = "text", x =30, y = 63,
                    label =  paste('slope:', round(lm(b ~a)[["coefficients"]][["a"]],5)), hjust = 0,
                    vjust = 1, size = 4)