attach(trustData)

ag<-aggregate(trustData, by = list(type = face_category_and_gender2_ZAUFANIE), mean)

plot <- ggplot(data=ag, aes(x=type, y=response)) + list(geom_point(colour= 'red'))

plot

library(dplyr)
library(tidyr)
library(ggplot2)
ag %>%
    separate(type, into = c("val", "Type"), "(?=[A-Z])", remove = FALSE) %>%
    mutate(Type = factor(Type, levels =c("M", "K"), labels = c("Men", "Woman"))) %>%
    ggplot(., aes(x = val, y = response, col = Type)) +
                geom_point()

ag %>%
   separate(type, into = c("val", "Type"), "(?=[A-Z])", remove = FALSE) %>%
   mutate(Sex = case_when(.$Type == "M" ~ "Men", TRUE ~ "Woman")) %>%
   ggplot(., aes(x = val, y = response, col = Type)) +
                geom_point()

ag <- structure(list(type = c("12K", "12M", "15K", "15M", "1K", "1M",
"4K", "4M", "7K", "7M", "9K", "9M"), response = c(41.83, 42.45,
40.61, 40.69, 64.59, 57.88, 61.2, 54.71, 49.23, 48.24, 44.27,
45.09)), .Names = c("type", "response"), row.names = c(NA, -12L
), class = "data.frame")