Great Deal! Get Instant $10 FREE in Account on First Order + 10% Cashback on Every Order Order Now

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...

1 answer below »
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 check whether the precision parameter phi should be linked to 'stress' to allow variable dispersion (the default model assumes constant phi and thus constant variance). Figure out how to implement a model where the precision parameter phi is allowed to vary by linking it to a predictor. Test the significance of the stress x species interaction using a likelihood ratio test (drop1() and anova(m1, m2). Plot the model predictions of your final model superimposed on the raw data.
breedingsuccess1-op1ljzmx.csv
Answered Same Day Apr 24, 2021

Solution

Aakarsh answered on Apr 27 2021
142 Votes
39434/.RData
39434/.RData
39434/.Rhistory
coord_flip()
ggplot(adv_data, aes(x=adv_data$Age, fill=adv_data$Spending )) + geom_bar( ) +
scale_fill_
ewer(palette = "Set1")+
coord_flip()
summary(adv_data)
grid.a
ange(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$Spending )) + geom_bar( ) +
scale_fill_
ewer(palette = "Set1")+
coord_flip()
summary(adv_data)
grid.a
ange(qplot(adv_data$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_
ewer(palette = "Set1")+
coord_flip()
summary(adv_data)
grid.a
ange(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$Spending )) + geom_bar( ) +
scale_fill_
ewer(palette = "Set1")+
coord_flip()
summary(adv_data)
grid.a
ange(qplot(adv_data$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_
ewer(palette = "Set1")+
coord_flip()
View(sales_data)
View(sales_data)
summary(adv_data)
grid.a
ange(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(e
or = TRUE)
li
ary(readxl)
li
ary(grid)
li
ary(ggplot2)
li
ary(gridExtra)
li
ary(dplyr)
li
ary(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"))
co
plot(income_melt)
knitr::opts_chunk$set(e
or = TRUE)
li
ary(readxl)
li
ary(grid)
li
ary(ggplot2)
li
ary(gridExtra)
li
ary(dplyr)
li
ary(reshape2)
li
ary(co
plot)
income_melt<-melt(income_data, id.vars = c("Year"))
co
plot(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...
SOLUTION.PDF
SOLUTION.PDF

Answer To This Question Is Available To Download

Related Questions & Answers

More Questions »

Submit New Assignment

Copy and Paste Your Assignment Here
Attach File