Word-Suggestions: Device Demographic Results

source("./device-setup.R")

measured_runs <- read_device_runs(measured_only=TRUE)

1 Age

age_data <- measured_runs %>%
  filter(!is.na(age)) %>%
  distinct(participant, .keep_all = T) %>%
  select(participant, age, accuracy)

ggplot(
  age_data,
  aes(x = age, fill=accuracy)
) +
  geom_histogram(binwidth = 1)

age_data %>%
  summarize(
    mean_age = mean(age),
    sd_age = sd(age),
    max_age = max(age),
    min_age = min(age)
  )

age_data %>%
  group_by(accuracy) %>%
  summarize(
    mean_age = mean(age),
    sd_age = sd(age),
    max_age = max(age),
    min_age = min(age)
  )

2 Gender

table(measured_runs %>% distinct(participant, .keep_all = T) %>% pull(gender))

Female   Male 
    13     23 

measured_runs %>%
  distinct(participant, .keep_all = T) %>%
  group_by(accuracy, gender) %>%
  summarize(
    n = n(),
    .groups = "drop"
  )

3 Device Use (last 7 days)

ggplot(measured_runs, aes(x = device_use, fill=accuracy)) +
  geom_histogram(stat="count") +
  facet_grid(rows = vars(device)) +
  theme(axis.text.x = element_text(angle = 90, vjust = 0.5, hjust=1))

Warning in geom_histogram(stat = "count"): Ignoring unknown parameters: `binwidth`, `bins`, and `pad`

measured_runs %>%
  group_by(device) %>%
  summarize(
    .groups="drop",
    n_frequent = sum(device_use %in% c("2 to 4 hours", "4 to 8 hours", "more than 8 hours")),
    total = n(),
    ratio = n_frequent / total
  )

4 Typing (last 7 days)

ggplot(measured_runs, aes(x = typing_use, fill=accuracy)) +
  geom_histogram(stat="count") +
  facet_grid(rows = vars(device)) +
  theme(axis.text.x = element_text(angle = 90, vjust = 0.5, hjust=1))

Warning in geom_histogram(stat = "count"): Ignoring unknown parameters: `binwidth`, `bins`, and `pad`

measured_runs %>%
  group_by(device) %>%
  summarize(
    .groups="drop",
    n_frequent = sum(typing_use %in% c("4 to 8 hours", "more than 8 hours")),
    total = n(),
    ratio = n_frequent / total
  )

4.1 One handed typing on phone

typing_handedness_data <- measured_runs %>%
  filter(device == PHONE) %>%
  pivot_longer(
    cols = starts_with("typing_use"),
    names_to = "prop",
    values_to = "use"
  ) %>%
  mutate(
    handedness = case_when(
      prop == "typing_use" ~ "both hands",
      TRUE ~ "dominant"
    )
  )

typing_handedness_data %>%
  ggplot(aes(x = use, fill=accuracy)) +
    geom_histogram(stat="count") +
    facet_grid(rows = vars(handedness)) +
    theme(axis.text.x = element_text(angle = 90, vjust = 0.5, hjust=1))

Warning in geom_histogram(stat = "count"): Ignoring unknown parameters: `binwidth`, `bins`, and `pad`

typing_handedness_data %>%
  filter(handedness == "dominant") %>%
  summarize(
    .groups="drop",
    frequent = sum(use %in% c("1 to 2 hours", "2 to 4 hours", "4 to 8 hours", "more than 8 hours")),
    total = n(),
    ratio = frequent / total
  )

4.2 Swipe typing

ggplot(measured_runs, aes(x=suggestions_use_frequency, fill=accuracy)) +
  geom_histogram(stat="count") +
  facet_grid(rows = vars(device))

Warning in geom_histogram(stat = "count"): Ignoring unknown parameters: `binwidth`, `bins`, and `pad`

5 Suggestions Use (last 24h)

ggplot(measured_runs, aes(x=suggestions_use_frequency, fill=accuracy)) +
  geom_histogram(stat="count") +
  facet_grid(rows = vars(device)) +
  theme(axis.text.x = element_text(angle = 90, vjust = 0.5, hjust=1))

Warning in geom_histogram(stat = "count"): Ignoring unknown parameters: `binwidth`, `bins`, and `pad`

measured_runs %>%
  select(participant, device, suggestions_use_frequency) %>%
  arrange(participant, device) %>%
  group_by(device) %>%
  summarize(
    .groups="drop",
    use_frequently = sum(!suggestions_use_frequency %in% c("10 to 30", "30 to 100", "100 to 300")),
    total = n(),
    ratio = use_frequently / total
  )

6 Typing speed as a function of familiarity

data_fam <- measured_runs |>
  mutate(exp_typing_use = ifelse(
    is.na(typing_use_one_hand),
    as.character(typing_use),
    as.character(typing_use_one_hand)
  ) |>
    factor(levels = levels(measured_runs$typing_use)))

ggplot(data_fam, aes(x = exp_typing_use, y = avg_wpm, fill = device)) +
  geom_boxplot(show.legend = FALSE) +
  facet_wrap(vars(device)) +
  xlab("Typing usage in the experiment's condition") +
  theme(axis.text.x = element_text(
    angle = 90,
    vjust = 0.5,
    hjust = 1
  ))