Hello. I am working with a dataset that I am using to develop some plots and run some stats. Here is my original dataset:
> pacman::p_load(pacman, party, rio, tidyverse)
> Cellphone_models < read.csv("~/Desktop/Cellphone models.csv")
> Cellphone_models < read.csv("~/Desktop/Cellphone models.csv")
> Cellphone_models
Cellphone.model Dimensions Price
1 Model A 10.3 400
2 Model A 10.5 350
3 Model A 10.2 300
4 Model A 10.1 400
5 Model A 10.0 500
6 Model B 10.0 450
7 Model B 10.1 300
8 Model B 10.2 200
9 Model B 9.9 45
10 Model C 10.0 475
11 Model C 10.2 560
12 Model D 9.8 400
13 Model D 9.9 350
14 Model D 10.2 300
15 Model D 10.0 400
16 Model D 10.0 500
17 Model D 10.1 450
18 Model E 9.9 200
19 Model E 9.9 45
20 Model E 9.0 475
> Cellphone_models %>% group_by(Cellphone.model) %>% summarise_if(is.numeric, mean)
# A tibble: 5 x 3
Cellphone.model Dimensions Price
<fct> <dbl> <dbl>
1 Model A 10.2 390
2 Model B 10.0 249.
3 Model C 10.1 518.
4 Model D 10 400
5 Model E 9.6 240
I then developed a boxplot showing the relationship between cell phone models and their dimensions (cm) using the following code:
boxplot(Dimensions~Cellphone.model)
Here is where I need some help:

How can I display the mean values of each of the 5 individual box plots (i.e. cell phone model types on the xaxis) within the graph?

Is there a ttest code that will allow me to compare the significance of difference in mean values between the two cell phone model types (e.g. Model B and D (using Model D as a reference mean value).
Thanks!