Group 3 tutorial week 3

{data(PlantGrowth)}
summary (PlantGrowth)
##      weight       group   
##  Min.   :3.590   ctrl:10  
##  1st Qu.:4.550   trt1:10  
##  Median :5.155   trt2:10  
##  Mean   :5.073            
##  3rd Qu.:5.530            
##  Max.   :6.310
head (PlantGrowth)
##   weight group
## 1   4.17  ctrl
## 2   5.58  ctrl
## 3   5.18  ctrl
## 4   6.11  ctrl
## 5   4.50  ctrl
## 6   4.61  ctrl
str(PlantGrowth)
## 'data.frame':    30 obs. of  2 variables:
##  $ weight: num  4.17 5.58 5.18 6.11 4.5 4.61 5.17 4.53 5.33 5.14 ...
##  $ group : Factor w/ 3 levels "ctrl","trt1",..: 1 1 1 1 1 1 1 1 1 1 ...
boxplot(PlantGrowth$weight ~ PlantGrowth$group,
        ylab = "Weight/g",
        xlab = "Treatment used")

library(ggplot2)
library(ggplot2)
library(dplyr)
## 
## Attaching package: 'dplyr'
## The following objects are masked from 'package:stats':
## 
##     filter, lag
## The following objects are masked from 'package:base':
## 
##     intersect, setdiff, setequal, union
# Using dplyr functions
Plantgrowth_summary <- 
  PlantGrowth %>% 
     group_by(group) %>%
     summarise(count = n(),
               mean = mean(weight, na.rm = TRUE),
               ssd = sd(weight, na.rm = TRUE)) %>%
     mutate(se = ssd / sqrt(count),
            lower_ci = mean - qt(1 - (0.05 / 2), count - 1) * se,
            upper_ci = mean + qt(1 - (0.05 / 2), count - 1) * se)

# Nice table output
knitr::kable(Plantgrowth_summary)
group count mean ssd se lower_ci upper_ci
ctrl 10 5.032 0.5830914 0.1843897 4.614882 5.449118
trt1 10 4.661 0.7936757 0.2509823 4.093239 5.228761
trt2 10 5.526 0.4425733 0.1399540 5.209402 5.842598 
Plantgrowth_summary %>% ggplot() +
                geom_point(aes(x = group, y = mean,
                               colour = group),
                           size = 3) +
                geom_errorbar(aes(x = group,
                                  ymin = lower_ci,
                                  ymax = upper_ci,
                                  colour = group),
                              width = 0.2, size = 1) +
                labs(x = "Treatment used", y = "Weight (g)",) +
                scale_colour_manual(values = c("darkorange",
                                             "purple",
                                             "cyan4")) +
                theme_minimal() +
                theme(legend.position = "none")
## Warning: Using `size` aesthetic for lines was deprecated in ggplot2 3.4.0.
## ℹ Please use `linewidth` instead.
## This warning is displayed once every 8 hours.
## Call `lifecycle::last_lifecycle_warnings()` to see where this warning was
## generated.

#Treatment 2 has the highest average growth