panel.grid.minor = element_blank())+
theme(axis.title.x = element_text(size=30, hjust = .44),
axis.title.y = element_text(size=30))+
theme(axis.text.y = element_text(color = "black", size = 24),
axis.ticks.y = element_line(color = "black"))+
theme(axis.text.x = element_text(color = "black", size = 24),
axis.ticks.x = element_line(color = "black"))
Scit.plot
library(ggplot2)
library(grid)
#calculating mean and se of bee frequencies
beeScit <- subset(bdat, Flower=="Cit")
mean_bee_Scit <- mean(beeScit$Frequency)
mean_bee_Scit
std <- function(x) sd(x)/sqrt(length(x)) ##function for standard error
up_se_bee_Scit <- mean_bee_Scit + std(beeScit$Frequency)
up_se_bee_Scit
down_se_bee_Scit <- mean_bee_Scit - std(beeScit$Frequency)
down_se_bee_Scit
# S. citrullifolium - poll and feeding stamen vs bees freq
Scit.plot <- ggplot(NULL) +
aes(x = `frequency (Hz)` , y = accelleration) +
geom_line(data = scp1, size = 1) +
# geom_line(data = scp2, size = 1) +
# geom_line(data = scp3, size = 1) +
# geom_line(data = scp4, size = 1) +
# geom_line(data = scp5, size = 1) +
# geom_line(data = scp6, size = 1) +
# geom_line(data = scp7, size = 1) +
# geom_line(data = scp8, size = 1) +
# geom_line(data = scp9, size = 1) +
geom_line(data = scf9, size = 1, color = "darkgrey") +
geom_vline(xintercept = up_se_bee_Scit,
colour = "darkgrey", size = 1.1)+
geom_vline(xintercept = down_se_bee_Scit,
colour = "darkgrey", size = 1.1)+
geom_vline(xintercept = mean_bee_Scit,
colour = "red", size = 1.1)+
theme_bw()+
xlab("Frequency (Hz)")+
ylab(bquote('Acceleration ('*'m'~s^-2*')'))+
theme(panel.grid.major = element_blank(),
panel.grid.minor = element_blank())+
theme(axis.title.x = element_text(size=30, hjust = .44),
axis.title.y = element_text(size=30))+
theme(axis.text.y = element_text(color = "black", size = 24),
axis.ticks.y = element_line(color = "black"))+
theme(axis.text.x = element_text(color = "black", size = 24),
axis.ticks.x = element_line(color = "black"))
Scit.plot
library(ggplot2)
library(grid)
#calculating mean and se of bee frequencies
beeScit <- subset(bdat, Flower=="Cit")
mean_bee_Scit <- mean(beeScit$Frequency)
mean_bee_Scit
std <- function(x) sd(x)/sqrt(length(x)) ##function for standard error
up_se_bee_Scit <- mean_bee_Scit + std(beeScit$Frequency)
up_se_bee_Scit
down_se_bee_Scit <- mean_bee_Scit - std(beeScit$Frequency)
down_se_bee_Scit
# S. citrullifolium - poll and feeding stamen vs bees freq
Scit.plot <- ggplot(NULL) +
aes(x = `frequency (Hz)` , y = accelleration) +
# geom_line(data = scp1, size = 1) +
geom_line(data = scp2, size = 1) +
# geom_line(data = scp3, size = 1) +
# geom_line(data = scp4, size = 1) +
# geom_line(data = scp5, size = 1) +
# geom_line(data = scp6, size = 1) +
# geom_line(data = scp7, size = 1) +
# geom_line(data = scp8, size = 1) +
# geom_line(data = scp9, size = 1) +
geom_line(data = scf9, size = 1, color = "darkgrey") +
geom_vline(xintercept = up_se_bee_Scit,
colour = "darkgrey", size = 1.1)+
geom_vline(xintercept = down_se_bee_Scit,
colour = "darkgrey", size = 1.1)+
geom_vline(xintercept = mean_bee_Scit,
colour = "red", size = 1.1)+
theme_bw()+
xlab("Frequency (Hz)")+
ylab(bquote('Acceleration ('*'m'~s^-2*')'))+
theme(panel.grid.major = element_blank(),
panel.grid.minor = element_blank())+
theme(axis.title.x = element_text(size=30, hjust = .44),
axis.title.y = element_text(size=30))+
theme(axis.text.y = element_text(color = "black", size = 24),
axis.ticks.y = element_line(color = "black"))+
theme(axis.text.x = element_text(color = "black", size = 24),
axis.ticks.x = element_line(color = "black"))
Scit.plot
library(ggplot2)
library(grid)
#calculating mean and se of bee frequencies
beeScit <- subset(bdat, Flower=="Cit")
mean_bee_Scit <- mean(beeScit$Frequency)
mean_bee_Scit
std <- function(x) sd(x)/sqrt(length(x)) ##function for standard error
up_se_bee_Scit <- mean_bee_Scit + std(beeScit$Frequency)
up_se_bee_Scit
down_se_bee_Scit <- mean_bee_Scit - std(beeScit$Frequency)
down_se_bee_Scit
# S. citrullifolium - poll and feeding stamen vs bees freq
Scit.plot <- ggplot(NULL) +
aes(x = `frequency (Hz)` , y = accelleration) +
# geom_line(data = scp1, size = 1) +
# geom_line(data = scp2, size = 1) +
geom_line(data = scp3, size = 1) +
# geom_line(data = scp4, size = 1) +
# geom_line(data = scp5, size = 1) +
# geom_line(data = scp6, size = 1) +
# geom_line(data = scp7, size = 1) +
# geom_line(data = scp8, size = 1) +
# geom_line(data = scp9, size = 1) +
geom_line(data = scf9, size = 1, color = "darkgrey") +
geom_vline(xintercept = up_se_bee_Scit,
colour = "darkgrey", size = 1.1)+
geom_vline(xintercept = down_se_bee_Scit,
colour = "darkgrey", size = 1.1)+
geom_vline(xintercept = mean_bee_Scit,
colour = "red", size = 1.1)+
theme_bw()+
xlab("Frequency (Hz)")+
ylab(bquote('Acceleration ('*'m'~s^-2*')'))+
theme(panel.grid.major = element_blank(),
panel.grid.minor = element_blank())+
theme(axis.title.x = element_text(size=30, hjust = .44),
axis.title.y = element_text(size=30))+
theme(axis.text.y = element_text(color = "black", size = 24),
axis.ticks.y = element_line(color = "black"))+
theme(axis.text.x = element_text(color = "black", size = 24),
axis.ticks.x = element_line(color = "black"))
Scit.plot
library(ggplot2)
library(grid)
#calculating mean and se of bee frequencies
beeScit <- subset(bdat, Flower=="Cit")
mean_bee_Scit <- mean(beeScit$Frequency)
mean_bee_Scit
std <- function(x) sd(x)/sqrt(length(x)) ##function for standard error
up_se_bee_Scit <- mean_bee_Scit + std(beeScit$Frequency)
up_se_bee_Scit
down_se_bee_Scit <- mean_bee_Scit - std(beeScit$Frequency)
down_se_bee_Scit
# S. citrullifolium - poll and feeding stamen vs bees freq
Scit.plot <- ggplot(NULL) +
aes(x = `frequency (Hz)` , y = accelleration) +
# geom_line(data = scp1, size = 1) +
# geom_line(data = scp2, size = 1) +
# geom_line(data = scp3, size = 1) +
geom_line(data = scp4, size = 1) +
# geom_line(data = scp5, size = 1) +
# geom_line(data = scp6, size = 1) +
# geom_line(data = scp7, size = 1) +
# geom_line(data = scp8, size = 1) +
# geom_line(data = scp9, size = 1) +
geom_line(data = scf9, size = 1, color = "darkgrey") +
geom_vline(xintercept = up_se_bee_Scit,
colour = "darkgrey", size = 1.1)+
geom_vline(xintercept = down_se_bee_Scit,
colour = "darkgrey", size = 1.1)+
geom_vline(xintercept = mean_bee_Scit,
colour = "red", size = 1.1)+
theme_bw()+
xlab("Frequency (Hz)")+
ylab(bquote('Acceleration ('*'m'~s^-2*')'))+
theme(panel.grid.major = element_blank(),
panel.grid.minor = element_blank())+
theme(axis.title.x = element_text(size=30, hjust = .44),
axis.title.y = element_text(size=30))+
theme(axis.text.y = element_text(color = "black", size = 24),
axis.ticks.y = element_line(color = "black"))+
theme(axis.text.x = element_text(color = "black", size = 24),
axis.ticks.x = element_line(color = "black"))
Scit.plot
library(ggplot2)
library(grid)
#calculating mean and se of bee frequencies
beeScit <- subset(bdat, Flower=="Cit")
mean_bee_Scit <- mean(beeScit$Frequency)
mean_bee_Scit
std <- function(x) sd(x)/sqrt(length(x)) ##function for standard error
up_se_bee_Scit <- mean_bee_Scit + std(beeScit$Frequency)
up_se_bee_Scit
down_se_bee_Scit <- mean_bee_Scit - std(beeScit$Frequency)
down_se_bee_Scit
# S. citrullifolium - poll and feeding stamen vs bees freq
Scit.plot <- ggplot(NULL) +
aes(x = `frequency (Hz)` , y = accelleration) +
# geom_line(data = scp1, size = 1) +
# geom_line(data = scp2, size = 1) +
# geom_line(data = scp3, size = 1) +
# geom_line(data = scp4, size = 1) +
geom_line(data = scp5, size = 1) +
# geom_line(data = scp6, size = 1) +
# geom_line(data = scp7, size = 1) +
# geom_line(data = scp8, size = 1) +
# geom_line(data = scp9, size = 1) +
geom_line(data = scf9, size = 1, color = "darkgrey") +
geom_vline(xintercept = up_se_bee_Scit,
colour = "darkgrey", size = 1.1)+
geom_vline(xintercept = down_se_bee_Scit,
colour = "darkgrey", size = 1.1)+
geom_vline(xintercept = mean_bee_Scit,
colour = "red", size = 1.1)+
theme_bw()+
xlab("Frequency (Hz)")+
ylab(bquote('Acceleration ('*'m'~s^-2*')'))+
theme(panel.grid.major = element_blank(),
panel.grid.minor = element_blank())+
theme(axis.title.x = element_text(size=30, hjust = .44),
axis.title.y = element_text(size=30))+
theme(axis.text.y = element_text(color = "black", size = 24),
axis.ticks.y = element_line(color = "black"))+
theme(axis.text.x = element_text(color = "black", size = 24),
axis.ticks.x = element_line(color = "black"))
Scit.plot
library(ggplot2)
library(grid)
#calculating mean and se of bee frequencies
beeScit <- subset(bdat, Flower=="Cit")
mean_bee_Scit <- mean(beeScit$Frequency)
mean_bee_Scit
std <- function(x) sd(x)/sqrt(length(x)) ##function for standard error
up_se_bee_Scit <- mean_bee_Scit + std(beeScit$Frequency)
up_se_bee_Scit
down_se_bee_Scit <- mean_bee_Scit - std(beeScit$Frequency)
down_se_bee_Scit
# S. citrullifolium - poll and feeding stamen vs bees freq
Scit.plot <- ggplot(NULL) +
aes(x = `frequency (Hz)` , y = accelleration) +
# geom_line(data = scp1, size = 1) +
# geom_line(data = scp2, size = 1) +
# geom_line(data = scp3, size = 1) +
# geom_line(data = scp4, size = 1) +
geom_line(data = scp5, size = 1) +
geom_line(data = scp6, size = 1) +
# geom_line(data = scp7, size = 1) +
# geom_line(data = scp8, size = 1) +
# geom_line(data = scp9, size = 1) +
geom_line(data = scf9, size = 1, color = "darkgrey") +
geom_vline(xintercept = up_se_bee_Scit,
colour = "darkgrey", size = 1.1)+
geom_vline(xintercept = down_se_bee_Scit,
colour = "darkgrey", size = 1.1)+
geom_vline(xintercept = mean_bee_Scit,
colour = "red", size = 1.1)+
theme_bw()+
xlab("Frequency (Hz)")+
ylab(bquote('Acceleration ('*'m'~s^-2*')'))+
theme(panel.grid.major = element_blank(),
panel.grid.minor = element_blank())+
theme(axis.title.x = element_text(size=30, hjust = .44),
axis.title.y = element_text(size=30))+
theme(axis.text.y = element_text(color = "black", size = 24),
axis.ticks.y = element_line(color = "black"))+
theme(axis.text.x = element_text(color = "black", size = 24),
axis.ticks.x = element_line(color = "black"))
Scit.plot
library(ggplot2)
library(grid)
#calculating mean and se of bee frequencies
beeScit <- subset(bdat, Flower=="Cit")
mean_bee_Scit <- mean(beeScit$Frequency)
mean_bee_Scit
std <- function(x) sd(x)/sqrt(length(x)) ##function for standard error
up_se_bee_Scit <- mean_bee_Scit + std(beeScit$Frequency)
up_se_bee_Scit
down_se_bee_Scit <- mean_bee_Scit - std(beeScit$Frequency)
down_se_bee_Scit
# S. citrullifolium - poll and feeding stamen vs bees freq
Scit.plot <- ggplot(NULL) +
aes(x = `frequency (Hz)` , y = accelleration) +
# geom_line(data = scp1, size = 1) +
# geom_line(data = scp2, size = 1) +
# geom_line(data = scp3, size = 1) +
# geom_line(data = scp4, size = 1) +
geom_line(data = scp5, size = 1) +
geom_line(data = scp6, size = 1) +
geom_line(data = scp7, size = 1) +
# geom_line(data = scp8, size = 1) +
# geom_line(data = scp9, size = 1) +
geom_line(data = scf9, size = 1, color = "darkgrey") +
geom_vline(xintercept = up_se_bee_Scit,
colour = "darkgrey", size = 1.1)+
geom_vline(xintercept = down_se_bee_Scit,
colour = "darkgrey", size = 1.1)+
geom_vline(xintercept = mean_bee_Scit,
colour = "red", size = 1.1)+
theme_bw()+
xlab("Frequency (Hz)")+
ylab(bquote('Acceleration ('*'m'~s^-2*')'))+
theme(panel.grid.major = element_blank(),
panel.grid.minor = element_blank())+
theme(axis.title.x = element_text(size=30, hjust = .44),
axis.title.y = element_text(size=30))+
theme(axis.text.y = element_text(color = "black", size = 24),
axis.ticks.y = element_line(color = "black"))+
theme(axis.text.x = element_text(color = "black", size = 24),
axis.ticks.x = element_line(color = "black"))
Scit.plot
library(ggplot2)
library(grid)
#calculating mean and se of bee frequencies
beeScit <- subset(bdat, Flower=="Cit")
mean_bee_Scit <- mean(beeScit$Frequency)
mean_bee_Scit
std <- function(x) sd(x)/sqrt(length(x)) ##function for standard error
up_se_bee_Scit <- mean_bee_Scit + std(beeScit$Frequency)
up_se_bee_Scit
down_se_bee_Scit <- mean_bee_Scit - std(beeScit$Frequency)
down_se_bee_Scit
# S. citrullifolium - poll and feeding stamen vs bees freq
Scit.plot <- ggplot(NULL) +
aes(x = `frequency (Hz)` , y = accelleration) +
# geom_line(data = scp1, size = 1) +
# geom_line(data = scp2, size = 1) +
# geom_line(data = scp3, size = 1) +
# geom_line(data = scp4, size = 1) +
# geom_line(data = scp5, size = 1) +
# geom_line(data = scp6, size = 1) +
geom_line(data = scp7, size = 1) +
geom_line(data = scp8, size = 1) +
# geom_line(data = scp9, size = 1) +
geom_line(data = scf9, size = 1, color = "darkgrey") +
geom_vline(xintercept = up_se_bee_Scit,
colour = "darkgrey", size = 1.1)+
geom_vline(xintercept = down_se_bee_Scit,
colour = "darkgrey", size = 1.1)+
geom_vline(xintercept = mean_bee_Scit,
colour = "red", size = 1.1)+
theme_bw()+
xlab("Frequency (Hz)")+
ylab(bquote('Acceleration ('*'m'~s^-2*')'))+
theme(panel.grid.major = element_blank(),
panel.grid.minor = element_blank())+
theme(axis.title.x = element_text(size=30, hjust = .44),
axis.title.y = element_text(size=30))+
theme(axis.text.y = element_text(color = "black", size = 24),
axis.ticks.y = element_line(color = "black"))+
theme(axis.text.x = element_text(color = "black", size = 24),
axis.ticks.x = element_line(color = "black"))
Scit.plot
library(ggplot2)
library(grid)
#calculating mean and se of bee frequencies
beeScit <- subset(bdat, Flower=="Cit")
mean_bee_Scit <- mean(beeScit$Frequency)
mean_bee_Scit
std <- function(x) sd(x)/sqrt(length(x)) ##function for standard error
up_se_bee_Scit <- mean_bee_Scit + std(beeScit$Frequency)
up_se_bee_Scit
down_se_bee_Scit <- mean_bee_Scit - std(beeScit$Frequency)
down_se_bee_Scit
# S. citrullifolium - poll and feeding stamen vs bees freq
Scit.plot <- ggplot(NULL) +
aes(x = `frequency (Hz)` , y = accelleration) +
# geom_line(data = scp1, size = 1) +
# geom_line(data = scp2, size = 1) +
# geom_line(data = scp3, size = 1) +
# geom_line(data = scp4, size = 1) +
# geom_line(data = scp5, size = 1) +
# geom_line(data = scp6, size = 1) +
geom_line(data = scp7, size = 1) +
geom_line(data = scp8, size = 1) +
geom_line(data = scp9, size = 1) +
geom_line(data = scf9, size = 1, color = "darkgrey") +
geom_vline(xintercept = up_se_bee_Scit,
colour = "darkgrey", size = 1.1)+
geom_vline(xintercept = down_se_bee_Scit,
colour = "darkgrey", size = 1.1)+
geom_vline(xintercept = mean_bee_Scit,
colour = "red", size = 1.1)+
theme_bw()+
xlab("Frequency (Hz)")+
ylab(bquote('Acceleration ('*'m'~s^-2*')'))+
theme(panel.grid.major = element_blank(),
panel.grid.minor = element_blank())+
theme(axis.title.x = element_text(size=30, hjust = .44),
axis.title.y = element_text(size=30))+
theme(axis.text.y = element_text(color = "black", size = 24),
axis.ticks.y = element_line(color = "black"))+
theme(axis.text.x = element_text(color = "black", size = 24),
axis.ticks.x = element_line(color = "black"))
Scit.plot
library(ggplot2)
library(grid)
#calculating mean and se of bee frequencies
beeScit <- subset(bdat, Flower=="Cit")
mean_bee_Scit <- mean(beeScit$Frequency)
mean_bee_Scit
std <- function(x) sd(x)/sqrt(length(x)) ##function for standard error
up_se_bee_Scit <- mean_bee_Scit + std(beeScit$Frequency)
up_se_bee_Scit
down_se_bee_Scit <- mean_bee_Scit - std(beeScit$Frequency)
down_se_bee_Scit
# S. citrullifolium - poll and feeding stamen vs bees freq
Scit.plot <- ggplot(NULL) +
aes(x = `frequency (Hz)` , y = accelleration) +
geom_line(data = scp1, size = 1) +
geom_line(data = scp2, size = 1) +
# geom_line(data = scp3, size = 1) +
# geom_line(data = scp4, size = 1) +
# geom_line(data = scp5, size = 1) +
# geom_line(data = scp6, size = 1) +
# geom_line(data = scp7, size = 1) +
# geom_line(data = scp8, size = 1) +
# geom_line(data = scp9, size = 1) +
geom_line(data = scf9, size = 1, color = "darkgrey") +
geom_vline(xintercept = up_se_bee_Scit,
colour = "darkgrey", size = 1.1)+
geom_vline(xintercept = down_se_bee_Scit,
colour = "darkgrey", size = 1.1)+
geom_vline(xintercept = mean_bee_Scit,
colour = "red", size = 1.1)+
theme_bw()+
xlab("Frequency (Hz)")+
ylab(bquote('Acceleration ('*'m'~s^-2*')'))+
theme(panel.grid.major = element_blank(),
panel.grid.minor = element_blank())+
theme(axis.title.x = element_text(size=30, hjust = .44),
axis.title.y = element_text(size=30))+
theme(axis.text.y = element_text(color = "black", size = 24),
axis.ticks.y = element_line(color = "black"))+
theme(axis.text.x = element_text(color = "black", size = 24),
axis.ticks.x = element_line(color = "black"))
Scit.plot
library(ggplot2)
library(grid)
#calculating mean and se of bee frequencies
beeScit <- subset(bdat, Flower=="Cit")
mean_bee_Scit <- mean(beeScit$Frequency)
mean_bee_Scit
std <- function(x) sd(x)/sqrt(length(x)) ##function for standard error
up_se_bee_Scit <- mean_bee_Scit + std(beeScit$Frequency)
up_se_bee_Scit
down_se_bee_Scit <- mean_bee_Scit - std(beeScit$Frequency)
down_se_bee_Scit
# S. citrullifolium - poll and feeding stamen vs bees freq
Scit.plot <- ggplot(NULL) +
aes(x = `frequency (Hz)` , y = accelleration) +
geom_line(data = scp1, size = 1) +
# geom_line(data = scp2, size = 1) +
# geom_line(data = scp3, size = 1) +
# geom_line(data = scp4, size = 1) +
# geom_line(data = scp5, size = 1) +
# geom_line(data = scp6, size = 1) +
# geom_line(data = scp7, size = 1) +
# geom_line(data = scp8, size = 1) +
# geom_line(data = scp9, size = 1) +
geom_line(data = scf9, size = 1, color = "darkgrey") +
geom_vline(xintercept = up_se_bee_Scit,
colour = "darkgrey", size = 1.1)+
geom_vline(xintercept = down_se_bee_Scit,
colour = "darkgrey", size = 1.1)+
geom_vline(xintercept = mean_bee_Scit,
colour = "red", size = 1.1)+
theme_bw()+
xlab("Frequency (Hz)")+
ylab(bquote('Acceleration ('*'m'~s^-2*')'))+
theme(panel.grid.major = element_blank(),
panel.grid.minor = element_blank())+
theme(axis.title.x = element_text(size=30, hjust = .44),
axis.title.y = element_text(size=30))+
theme(axis.text.y = element_text(color = "black", size = 24),
axis.ticks.y = element_line(color = "black"))+
theme(axis.text.x = element_text(color = "black", size = 24),
axis.ticks.x = element_line(color = "black"))
Scit.plot
library(ggplot2)
library(grid)
#calculating mean and se of bee frequencies
beeScit <- subset(bdat, Flower=="Cit")
mean_bee_Scit <- mean(beeScit$Frequency)
mean_bee_Scit
std <- function(x) sd(x)/sqrt(length(x)) ##function for standard error
up_se_bee_Scit <- mean_bee_Scit + std(beeScit$Frequency)
up_se_bee_Scit
down_se_bee_Scit <- mean_bee_Scit - std(beeScit$Frequency)
down_se_bee_Scit
# S. citrullifolium - poll and feeding stamen vs bees freq
Scit.plot <- ggplot(NULL) +
aes(x = `frequency (Hz)` , y = accelleration) +
# geom_line(data = scp1, size = 1) +
# geom_line(data = scp2, size = 1) +
# geom_line(data = scp3, size = 1) +
# geom_line(data = scp4, size = 1) +
# geom_line(data = scp5, size = 1) +
# geom_line(data = scp6, size = 1) +
# geom_line(data = scp7, size = 1) +
# geom_line(data = scp8, size = 1) +
geom_line(data = scp9, size = 1) +
geom_line(data = scf9, size = 1, color = "darkgrey") +
geom_vline(xintercept = up_se_bee_Scit,
colour = "darkgrey", size = 1.1)+
geom_vline(xintercept = down_se_bee_Scit,
colour = "darkgrey", size = 1.1)+
geom_vline(xintercept = mean_bee_Scit,
colour = "red", size = 1.1)+
theme_bw()+
xlab("Frequency (Hz)")+
ylab(bquote('Acceleration ('*'m'~s^-2*')'))+
theme(panel.grid.major = element_blank(),
panel.grid.minor = element_blank())+
theme(axis.title.x = element_text(size=30, hjust = .44),
axis.title.y = element_text(size=30))+
theme(axis.text.y = element_text(color = "black", size = 24),
axis.ticks.y = element_line(color = "black"))+
theme(axis.text.x = element_text(color = "black", size = 24),
axis.ticks.x = element_line(color = "black"))
Scit.plot
