Hands-on Exercise 4b

Author

Lennis

Published

May 5, 2023

Getting Started

Install and launching R packages

The code chunk below uses p_load() of pacman package to check if plotly, crosstalk, DT, ggdist, gganimate and tidyverse packages are installed in the computer. If they are, then they will be launched into R.

pacman::p_load(tidyverse, plotly, crosstalk, DT, ggdist, gganimate)

Importing the data

exam <- read_csv("data/Exam_data.csv", show_col_types = FALSE)

Visualizing Uncertainty of Point Estimates with ggplot2

The code chunk below performs the followings: a) group the observation by RACE, b) computes the count of observations, mean, standard deviation and standard error of Maths by RACE, and c) save the output as a tibble data table called my_sum.

my_sum <- exam %>%
  group_by(RACE) %>%
  summarise(
    n=n(),
    mean=mean(MATHS),
    sd=sd(MATHS)
    ) %>%
  mutate(se=sd/sqrt(n-1))

knitr::kable(head(my_sum), format = 'html')

RACE	n	mean	sd	se
Chinese	193	76.50777	15.69040	1.132357
Indian	12	60.66667	23.35237	7.041005
Malay	108	57.44444	21.13478	2.043177
Others	9	69.66667	10.72381	3.791438

Standard Error

Code

ggplot(my_sum) +
  geom_errorbar(
    aes(x=RACE, 
        ymin=mean-se, 
        ymax=mean+se), 
    width=0.2, 
    colour="black", 
    alpha=0.9, 
    size=0.5) +
  geom_point(aes
           (x=RACE, 
            y=mean), 
           stat="identity", 
           color="red",
           size = 1.5,
           alpha=1) +
  ggtitle("Standard error of mean 
          maths score by race")

Warning: Using `size` aesthetic for lines was deprecated in ggplot2 3.4.0.
ℹ Please use `linewidth` instead.

Confidence Interval of Mean

Code

ggplot(my_sum) +
  geom_errorbar(
    aes(x=reorder(RACE,-mean), 
        ymin=mean-qnorm(1-0.025)*sd/sqrt(n), 
        ymax=mean+qnorm(1-0.025)*sd/sqrt(n)), 
    width=0.2, 
    colour="black", 
    alpha=0.9, 
    size=0.5) +
  geom_point(aes
           (x=reorder(RACE,-mean), 
            y=mean), 
           stat="identity", 
           color="red",
           size = 1.5,
           alpha=1) +
  ggtitle("95% confidence interval of mean 
          maths score by race")

Confidence Interval of Mean with Interactive Error Bars

Code

my_sum$tooltip <- c(paste0(
  "Race: ", my_sum$RACE,         
  "\n N:  ", my_sum$n,
  "\n Avg. Scores:  ", my_sum$mean,
  "\n 99% CI: [",my_sum$mean-qnorm(1-0.005)*my_sum$sd/sqrt(my_sum$n), ",", my_sum$mean-qnorm(1-0.005)*my_sum$sd/sqrt(my_sum$n), "]"
  )) 

d <- highlight_key(my_sum) 
p <- ggplot(my_sum) +
  geom_errorbar(
    aes(x=reorder(RACE,-mean), 
        ymin=mean-qnorm(1-0.005)*sd/sqrt(n), 
        ymax=mean+qnorm(1-0.005)*sd/sqrt(n)), 
    width=0.2, 
    colour="black", 
    alpha=0.9, 
    size=0.5) +
  geom_point(aes
           (x=reorder(RACE,-mean), 
            y=mean,
            text=my_sum$tooltip), 
           stat="identity", 
           color="red",
           size = 1.5,
           alpha=1) +
  ggtitle("99% confidence interval of mean 
          maths score by race")

Warning in geom_point(aes(x = reorder(RACE, -mean), y = mean, text =
my_sum$tooltip), : Ignoring unknown aesthetics: text

Code

gg <- highlight(ggplotly(p, tooltip=c("text")),
                "plotly_selected")

Warning: Use of `my_sum$tooltip` is discouraged.
ℹ Use `tooltip` instead.

Code

crosstalk::bscols(gg,               
                  DT::datatable(d), 
                  widths = 5)

Visualizing Uncertainty of Point Estimates with ggdist

Code

exam %>%
  ggplot(aes(x = RACE, 
             y = MATHS)) +
  stat_pointinterval() +   #<<
  labs(
    title = "Visualising confidence intervals of mean math score",
    subtitle = "Mean Point + Multiple-interval plot")

Code

exam %>%
  ggplot(aes(x = RACE, y = MATHS)) +
  stat_pointinterval(.width = 0.95,
  .point = median,
  .interval = qi) +
  labs(
    title = "Visualising confidence intervals of mean math score",
    subtitle = "Mean Point + Multiple-interval plot")

Warning in layer_slabinterval(data = data, mapping = mapping, stat =
StatPointinterval, : Ignoring unknown parameters: `.point` and `.interval`

Code

exam %>%
  ggplot(aes(x = RACE, 
             y = MATHS)) +
  stat_pointinterval(
    show.legend = FALSE) +   
  labs(
    title = "Visualising confidence intervals of mean math score",
    subtitle = "Mean Point + Multiple-interval plot")

Code

exam %>%
  ggplot(aes(x = RACE, 
             y = MATHS)) +
  stat_gradientinterval(   
    fill = "skyblue",      
    show.legend = TRUE     
  ) +                        
  labs(
    title = "Visualising confidence intervals of mean math score",
    subtitle = "Gradient + interval plot")

Warning: `fill_type = "gradient"` is not supported by the current graphics device, which
is `"png"`.
ℹ Falling back to `fill_type = "segments"`.
ℹ If you believe your current graphics device does support `fill_type =
  "gradient"` but auto-detection failed, try setting `fill_type = "gradient"`
  explicitly. If this causes the gradient to display correctly, then this
  warning is likely a false positive caused by the graphics device failing to
  properly report its support for the `"LinearGradient"` pattern via
  `grDevices::dev.capabilities()`. Consider reporting a bug to the author of
  the graphics device.
ℹ See the documentation for `fill_type` in `ggdist::geom_slabinterval()` for
  more information.

Visualizing Uncertainty with Hypothetical Outcome Plots (HOPs)

library(ungeviz)

Code

ggplot(data = exam, 
       (aes(x = factor(RACE), y = MATHS))) +
  geom_point(position = position_jitter(
    height = 0.3, width = 0.05), 
    size = 0.4, color = "#0072B2", alpha = 1/2) +
  geom_hpline(data = sampler(25, group = RACE), height = 0.6, color = "#D55E00") +
  theme_bw() + 
  # `.draw` is a generated column indicating the sample draw
  transition_states(.draw, 1, 3)

Warning in geom_hpline(data = sampler(25, group = RACE), height = 0.6, color =
"#D55E00"): Ignoring unknown parameters: `height`

Warning: Using the `size` aesthetic in this geom was deprecated in ggplot2 3.4.0.
ℹ Please use `linewidth` in the `default_aes` field and elsewhere instead.

Code

ggplot(data = exam, 
       (aes(x = factor(RACE), 
            y = MATHS))) +
  geom_point(position = position_jitter(
    height = 0.3, 
    width = 0.05), 
    size = 0.4, 
    color = "#0072B2", 
    alpha = 1/2) +
  geom_hpline(data = sampler(25, 
                             group = RACE), 
              height = 0.6, 
              color = "#D55E00") +
  theme_bw() + 
  transition_states(.draw, 1, 3)

Warning in geom_hpline(data = sampler(25, group = RACE), height = 0.6, color =
"#D55E00"): Ignoring unknown parameters: `height`