Read in the provided data set 'breeding_success' that contains stress-related mortality rates of two bird species given as a proportion (without underlying counts). Apply a beta regression model and...

39434/.RData
39434/.RData
39434/.Rhistory
coord_flip()
ggplot(adv_data, aes(x=adv_data$Age, fill=adv_data$Spending )) + geom_bar( ) +
scale_fill_brewer(palette = "Set1")+
coord_flip()
summary(adv_data)
grid.arrange(qplot(adv_data$Education),
nrow = NULL, ncol=NULL, newpage = TRUE)
ggplot(adv_data, aes(y=adv_data$Spending, x=adv_data$Income, fill=adv_data$Education)) +
geom_bar(stat="identity")+
coord_flip()
ggplot(adv_data, aes(y=adv_data$Age, x=adv_data$Income, fill=adv_data$Gender)) +
geom_bar(stat="identity")+
coord_flip()
ggplot(adv_data, aes(x=adv_data$Age, fill=adv_data$Spending )) + geom_bar( ) +
scale_fill_brewer(palette = "Set1")+
coord_flip()
summary(adv_data)
grid.arrange(qplot(adv_data$Education),
nrow = NULL, ncol=NULL, newpage = TRUE)
ggplot(adv_data, aes(y=adv_data$Spending, x=adv_data$Income, fill=adv_data$Education)) +
geom_bar(stat="identity")+
coord_flip()
ggplot(adv_data, aes(y=adv_data$Stereotype, x=adv_data$Income, fill=adv_data$Gender)) +
geom_bar(stat="identity")+
coord_flip()
ggplot(adv_data, aes(x=adv_data$Age, fill=adv_data$Spending )) + geom_bar( ) +
scale_fill_brewer(palette = "Set1")+
coord_flip()
summary(adv_data)
grid.arrange(qplot(adv_data$Education),
nrow = NULL, ncol=NULL, newpage = TRUE)
ggplot(adv_data, aes(y=adv_data$Spending, x=adv_data$Income, fill=adv_data$Education)) +
geom_bar(stat="identity")+
coord_flip()
ggplot(adv_data, aes(y=adv_data$Stereotype, x=adv_data$Transform, fill=adv_data$Reinforcing)) +
geom_bar(stat="identity")+
coord_flip()
ggplot(adv_data, aes(x=adv_data$Age, fill=adv_data$Spending )) + geom_bar( ) +
scale_fill_brewer(palette = "Set1")+
coord_flip()
summary(adv_data)
grid.arrange(qplot(adv_data$Education),
nrow = NULL, ncol=NULL, newpage = TRUE)
ggplot(adv_data, aes(y=adv_data$Spending, x=adv_data$Income, fill=adv_data$Education)) +
geom_bar(stat="identity")+
coord_flip()
ggplot(adv_data, aes(y=adv_data$Spending, x=adv_data$Transform, fill=adv_data$Reinforcing)) +
geom_bar(stat="identity")+
coord_flip()
ggplot(adv_data, aes(x=adv_data$Age, fill=adv_data$Spending )) + geom_bar( ) +
scale_fill_brewer(palette = "Set1")+
coord_flip()
View(sales_data)
View(sales_data)
summary(adv_data)
grid.arrange(qplot(adv_data$Education),
nrow = NULL, ncol=NULL, newpage = TRUE)
ggplot(adv_data, aes(y=adv_data$Spending, x=adv_data$Income, fill=adv_data$Education)) +
geom_bar(stat="identity")+
coord_flip()
ggplot(adv_data, aes(y=adv_data$Spending, x=adv_data$Transform, fill=adv_data$Reinforcing)) +
geom_bar(stat="identity")+
coord_flip()
summary(adv_data)
ggplot(adv_data, aes(y=adv_data$Spending, x=adv_data$Income, fill=adv_data$Education)) +
geom_bar(stat="identity")+
coord_flip()
ggplot(adv_data, aes(y=adv_data$Spending, x=adv_data$Transform, fill=adv_data$Reinforcing)) +
geom_bar(stat="identity")+
coord_flip()
summary(adv_data)
ggplot(adv_data, aes(y=adv_data$Spending, x=adv_data$Income, fill=adv_data$Education)) +
geom_bar(stat="identity")+
coord_flip()
ggplot(adv_data, aes(y=adv_data$Spending, x=adv_data$Education, fill=adv_data$Income)) +
geom_bar(stat="identity")+
coord_flip()
ggplot(adv_data, aes(y=adv_data$Spending, x=adv_data$Transform, fill=adv_data$Reinforcing)) +
geom_bar(stat="identity")+
coord_flip()
ggplot(adv_data, aes(y=aggregate(adv_data$Spending), x=adv_data$Education, fill=adv_data$Income)) +
geom_bar(stat="identity")+
coord_flip()
ggplot(adv_data, aes(y=adv_data$Spending, x=adv_data$Education, fill=adv_data$Income)) +
geom_bar(stat="identity")+
coord_flip()
ggplot(adv_data, aes(y=adv_data$Spending, x=adv_data$Transform, fill=adv_data$Reinforcing)) +
geom_bar(stat="identity")+
coord_flip()
View(adv_data)
View(adv_data)
ggplot(adv_data, aes(y=adv_data$Spending, x=adv_data$Education, fill=adv_data$Income)) +
geom_bar(stat="identity")+
coord_flip()
ggplot(adv_data, aes(y=adv_data["Ad Frequency"], x=adv_data$Spending, fill=adv_data$Reinforcing)) +
geom_bar(stat="identity")+
coord_flip()
ggplot(adv_data, aes(y=adv_data$Spending, x=adv_data$Education, fill=adv_data$Income)) +
geom_bar(stat="identity")+
coord_flip()
ggplot(adv_data, aes(y=adv_data$Ad Frequency, x=adv_data$Spending, fill=adv_data$Reinforcing)) +
ggplot(adv_data, aes(y=adv_data$Spending, x=adv_data$Education, fill=adv_data$Income)) +
geom_bar(stat="identity")+
coord_flip()
ggplot(adv_data, aes(y=adv_data$Ad$Frequency, x=adv_data$Spending, fill=adv_data$Reinforcing)) +
geom_bar(stat="identity")+
coord_flip()
ggplot(adv_data, aes(y=adv_data$Spending, x=adv_data$Education, fill=adv_data$Income)) +
geom_bar(stat="identity")+
coord_flip()
ggplot(adv_data, aes(y=adv_data$AdFrequency, x=adv_data$Spending, fill=adv_data$Reinforcing)) +
geom_bar(stat="identity")+
coord_flip()
ggplot(adv_data, aes(y=adv_data$Spending, x=adv_data$Education, fill=adv_data$Income)) +
geom_bar(stat="identity")+
coord_flip()
ggplot(adv_data, aes(y=adv_data$Stereotype, x=adv_data$Spending, fill=adv_data$Reinforcing)) +
geom_bar(stat="identity")+
coord_flip()
ggplot(adv_data, aes(y=adv_data$Spending, x=adv_data$Education, fill=adv_data$Income)) +
geom_bar(stat="identity")+
coord_flip()
ggplot(adv_data, aes(y=adv_data$Stereotype, x=adv_data$Spending) +
geom_bar(stat="identity")+
coord_flip()
ggplot(adv_data, aes(y=adv_data$Spending, x=adv_data$Education, fill=adv_data$Income)) +
geom_bar(stat="identity")+
coord_flip()
ggplot(adv_data, aes(y=adv_data$Stereotype, x=adv_data$Spending)) +
geom_bar(stat="identity")+
coord_flip()
knitr::opts_chunk$set(error = TRUE)
library(readxl)
library(grid)
library(ggplot2)
library(gridExtra)
library(dplyr)
library(reshape2)
View(income_data)
melt(income_data, id.vars = c("Year"),
measure.vars = c("avg_ppo2", "sum_amount"))
melt(income_data, id.vars = c("Year"))
income_melt<-melt(income_data, id.vars = c("Year"))
income_melt<-melt(income_data, id.vars = c("Year"))
corrplot(income_melt)
knitr::opts_chunk$set(error = TRUE)
library(readxl)
library(grid)
library(ggplot2)
library(gridExtra)
library(dplyr)
library(reshape2)
library(corrplot)
income_melt<-melt(income_data, id.vars = c("Year"))
corrplot(income_melt)
View(income_melt)
View(income_melt)
income_melt<-melt(income_data, id.vars = c("Year"))
ggplot(data = income_melt, mapping = aes(x = Year,
y = variable,
fill = value)) +
geom_tile() +
xlab(label = "Sample")
income_melt<-melt(income_data, id.vars = c("Year"))
ggplot(data = income_melt, mapping = aes(x = Year,
y = variable,
fill = value)) +
geom_tile() +
xlab(label = "Sample")
View(income_data)
View(income_data)
View(income_data)
income_melt<-melt(income_data, id.vars = c("Year"))
ggplot(data = income_melt, mapping = aes(x = Year,
y = variable,
fill = mean(value))) +
geom_tile() +
xlab(label = "Sample")
income_melt<-melt(income_data, id.vars = c("Year"))
ggplot(data = income_melt, mapping = aes(x = Year,
y = variable,
fill = value)) +
geom_tile() +
xlab(label = "Sample")
income_melt<-melt(income_data, id.vars = c("Year"))
ggplot(data = income_melt, mapping = aes(x = Year,
y = variable,
fill = mean.value)) +
geom_tile() +
xlab(label = "Sample")
income_melt<-melt(income_data, id.vars = c("Year"))
ggplot(data = income_melt, mapping = aes(x = Year,
y = variable,
fill = ave.value)) +
geom_tile() +
xlab(label = "Sample")
income_melt<-melt(income_data, id.vars = c("Year"))
ggplot(data = income_melt, mapping = aes(x = Year,
y = variable,
fill = ave(value))) +
geom_tile() +
xlab(label = "Sample")
income_melt<-melt(income_data, id.vars = c("Year"))
ggplot(data = income_melt, mapping = aes(x = Year,
y = variable,
fill = sum(value))) +
geom_tile() +
xlab(label = "Sample")
income_melt<-melt(income_data, id.vars = c("Year"))
ggplot(data = income_melt, mapping = aes(x = Year,
y = variable,
fill = value)) +
geom_tile() +
xlab(label = "Sample")
income_melt<-melt(income_data, id.vars = c("Year"))
ggplot(data = income_melt, mapping = aes(x = Year,
y = variable,
fill = value)) +
geom_tile() +
xlab(label = "Income over time in different States in US")
summary(income_melt)
income_melt<-melt(income_data, id.vars = c("Year"))
ggplot(data = income_melt, mapping = aes(x = Year,
y = variable,
fill = value)) +
geom_tile() +
xlab(label = "Income over time in different States in US")
summary(income_melt)
ggplot(adv_data, aes(y=income_melt$variable, x=income_melt$value) +
geom_bar(stat="identity")+
coord_flip()
income_melt<-melt(income_data, id.vars = c("Year"))
ggplot(data = income_melt, mapping = aes(x = Year,
y = variable,
fill = value)) +
geom_tile() +
xlab(label = "Income over time in different States in US")
summary(income_melt)
ggplot(adv_data, aes(y=income_melt$variable, x=income_melt$value)) +
geom_bar(stat="identity")+
coord_flip()
income_melt<-melt(income_data, id.vars = c("Year"))
ggplot(data = income_melt, mapping = aes(x = Year,
y = variable,
fill = value)) +
geom_tile() +
xlab(label = "Income over time in different States in US")
summary(income_melt)
ggplot(income_melt, aes(y=income_melt$variable, x=income_melt$value)) +
geom_bar(stat="identity")+
coord_flip()
income_melt<-melt(income_data, id.vars = c("Year"))
ggplot(data = income_melt, mapping = aes(x = Year,
y = variable,
fill = value)) +
geom_tile() +
xlab(label = "Income over time in...