Prep
library(pacman) #Load the pacman(package manager) package
p_load("dplyr", "tidyr", "ggplot2", "rio", "lubridate", "rmarkdown") #Load necessary Packages for this analysis
Body Mass & Wing Length Mean and SD bar graphs
Create the table given in R
Body.Mass.mean <- c(15.70, 17.00)
Wing.length.mean <- c(67.8, 69.3)
Body.Mass.sd <- c(1.36, 1.77)
Wing.length.sd <- c(2.28, 2.33)
survived <- c("no", "yes")
Mass.Wing.mean.sd.tbl <- data.frame(Body.Mass.mean, Wing.length.mean, Body.Mass.sd, Wing.length.sd, survived)
Plot the data
#Use qplot to create the bar plot, label axes, and title it
qplot(survived, Body.Mass.mean, data = Mass.Wing.mean.sd.tbl, geom = "col", main = "Mean of Body Mass of Surviving and Non-Surviving Finches", xlab = "Survivor Status", ylab = "Mean(grams)")
#Use ggsave to save the last plot as a png file
ggsave(filename = "Body Mass Mean Bar Plot.png", path = "/Users/danieltheng/Documents/Daniel Theng/BIOL 1B/BIOL 1BL/Finches")
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#Use qplot to create the bar plot, label axes, and title it
qplot(survived, Wing.length.mean, data = Mass.Wing.mean.sd.tbl, geom = "col", main = "Mean of Wing Length of Surviving and Non-Surviving Finches", xlab = "Survivor Status", ylab = "Mean(mm)")
#Use ggsave to save the last plot as a png
ggsave(filename = "Wing Length Mean Bar Plot.png", path = "/Users/danieltheng/Documents/Daniel Theng/BIOL 1B/BIOL 1BL/Finches")
## Saving 7 x 5 in image
Creating the other plots
Loading the Data
survivor <- import("/Users/danieltheng/Documents/Daniel Theng/BIOL 1B/BIOL 1BL/Finches/finch_survivor.xlsx")
nonsurvivor <- import("/Users/danieltheng/Documents/Daniel Theng/BIOL 1B/BIOL 1BL/Finches/finch_nonsurvivor.xlsx")
Combined the data into one dataframe
Survived <- rep("yes", times = 50)
survivor <- data.frame(survivor, Survived) #Add a column that says that these finches survived
Survived <- rep("no", times = 50)
nonsurvivor <- data.frame(nonsurvivor, Survived) #Add column that says that these finches died
finch.data <- rbind(survivor, nonsurvivor) #Combined the two separate dataframes
finch.data$Survived <- factor(finch.data$Survived)
Recreate Table 4 on the worksheet
Body.mass.mean <- c(mean(finch.data[finch.data$Survived == "yes", 6]), mean(finch.data[finch.data$Survived == "no", 6]))
Wing.length.mean <- c(mean(finch.data[finch.data$Survived == "yes", 7]), mean(finch.data[finch.data$Survived == "no", 7]))
Taursus.length.mean <- c(mean(finch.data[finch.data$Survived == "yes", 8]), mean(finch.data[finch.data$Survived == "no", 8]))
Beak.depth.mean <- c(mean(finch.data[finch.data$Survived == "yes", 10]), mean(finch.data[finch.data$Survived == "no", 10]))
Body.mass.var <- c(3.087, 1.842)
Wing.length.var <- c(5.448, 5.181)
Taursus.length.var <- c(.735, .701)
Beak.depth.var <- c(.709, .775)
table4 <- data.frame(Body.mass.mean, Wing.length.mean, Taursus.length.mean, Beak.depth.mean, Body.mass.var, Wing.length.var, Taursus.length.var, Beak.depth.var)
#Calculate the standard deviation
table4 <- mutate(table4, Body.mass.sd = sqrt(Body.mass.var))
table4 <- mutate(table4, Wing.length.sd = sqrt(Wing.length.var))
table4 <- mutate(table4, Taursus.length.sd = sqrt(Taursus.length.var))
table4 <- mutate(table4, Beak.depth.sd = sqrt(Beak.depth.var))
#Calculate the Standard Error
table4 <- mutate(table4, Body.mass.se = Body.mass.sd/sqrt(50))
table4 <- mutate(table4, Wing.length.se = Wing.length.sd/sqrt(50))
table4 <- mutate(table4, Taursus.length.se = Taursus.length.sd/sqrt(50))
table4 <- mutate(table4, Beak.depth.se = Beak.depth.sd/sqrt(50))
#Calculate the Upper limit of the confidence interval
table4 <- mutate(table4, Body.mass.confint.up = Body.mass.mean + Body.mass.se * 1.96)
table4 <- mutate(table4, Wing.length.confint.up = Wing.length.mean + Wing.length.se * 1.96)
table4 <- mutate(table4, Taursus.length.confint.up=Taursus.length.mean+Taursus.length.se*1.96)
table4 <- mutate(table4, Beak.depth.confint.up = Beak.depth.mean + Beak.depth.se * 1.96)
# Calculate the lower limit of the confidence interval
table4 <- mutate(table4, Body.mass.confint.low = Body.mass.mean - Body.mass.se * 1.96)
table4 <- mutate(table4, Wing.length.confint.low = Wing.length.mean - Wing.length.se * 1.96)
table4 <- mutate(table4, Taursus.length.confint.low=Taursus.length.mean-Taursus.length.se*1.96)
table4 <- mutate(table4, Beak.depth.confint.low = Beak.depth.mean - Beak.depth.se * 1.96)
table4 <- data.frame(table4, Survived = c("yes", "no"))
Creating the graphs using ggplot2
#Create Plot for Body Mass
bodymass <- ggplot(data = table4, aes(Survived, Body.mass.mean))
bodymass + geom_col() + geom_errorbar(aes(ymin = Body.mass.mean - Body.mass.se * 1.96, ymax = Body.mass.mean + Body.mass.se * 1.96)) + labs(x = "Survivor Status", y = "Mean(grams)", title = "Mean of Body Mass of Surviving and Non-Surviving Finches") + coord_cartesian(ylim = c(13, 18))
#Save plot
ggsave(filename = "BodyMassBar.png", device = "png", path = "/Users/danieltheng/Documents/Daniel Theng/BIOL 1B/BIOL 1BL/Finches")
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#Create Plot for Wing Length
winglength <- ggplot(data = table4, aes(Survived, Wing.length.mean))
winglength + geom_col() + geom_errorbar(aes(ymin = Wing.length.mean - Wing.length.se * 1.96, ymax = Wing.length.mean + Wing.length.se * 1.96)) + labs(x = "Survivor Status", y = "Mean(mm)", title = "Mean of Wing Length of Surviving and Non-Surviving Finches") + coord_cartesian(ylim = c(60, 70))
#Save plot
ggsave(filename = "WingLengthBar.png", path = "/Users/danieltheng/Documents/Daniel Theng/BIOL 1B/BIOL 1BL/Finches")
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#Create Plot for Taursus Length
taursuslength <- ggplot(data = table4, aes(Survived, Taursus.length.mean))
taursuslength + geom_col() + geom_errorbar(aes(ymin = Taursus.length.mean - Taursus.length.se * 1.96, ymax = Taursus.length.mean + Taursus.length.se * 1.96)) + labs(x = "Survivor Status", y = "Mean(mm)", title = "Mean of Tarsus Length of Surviving and Non-Surviving Finches") + coord_cartesian(ylim = c(15, 20))
#Save Plot
ggsave(filename = "TaursusLengthBar.png", path = "/Users/danieltheng/Documents/Daniel Theng/BIOL 1B/BIOL 1BL/Finches")
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#Create Plot for Beak Depth
beakdepth <- ggplot(data = table4, aes(Survived, Beak.depth.mean))
beakdepth + geom_col() + geom_errorbar(aes(ymin = Beak.depth.mean - Beak.depth.se * 1.96, ymax = Beak.depth.mean + Beak.depth.se * 1.96)) + labs(x = "Survivor Status", y = "Mean(mm)", title = "Mean of Beak Depth of Surviving and Non-Surviving Finches") + coord_cartesian(ylim = c(6, 10))
#Save Plot
ggsave(filename = "BeakDepthBar.png", path = "/Users/danieltheng/Documents/Daniel Theng/BIOL 1B/BIOL 1BL/Finches")
## Saving 7 x 5 in image