df.ppt <- read.csv('../../../data/exp2/PROCESSED_DATA/exp2.1_ppt.csv')
df.trial <- read.csv('../../../data/exp2/PROCESSED_DATA/exp2.1_trial.csv')

Demographics Stats

df.ppt %>%
  count(age_years) %>%
  knitr::kable()
age_years n
3 3
4 9
5 11 
df.ppt_gender <- df.ppt %>%
  count(gender) %>%
  knitr::kable()

df.ppt %>%
  summarise(min_age = min(age_years_cont), 
            max_age = max(age_years_cont), 
            mean_age = mean(age_years_cont), 
            sd_age = sd(age_years_cont))
##    min_age  max_age mean_age    sd_age
## 1 3.783562 5.871233 4.828946 0.5286573

Results

Cardinal extension operationalization

How do we operationalize cardinal extension success?

Correct Set Chosen

Descriptive Statistics

df.summary_magnitude_correct_set_chosen <- df.trial %>%
  summarise(mean = mean(correct_set_chosen), sd = sd(correct_set_chosen))
df.summary_magnitude_correct_set_chosen
##        mean        sd
## 1 0.4927536 0.5036102
df.summary_mising_set <- df.trial %>%
  summarise(mean = mean(remember_missing_item), sd = sd(remember_missing_item))
df.summary_mising_set
##   mean sd
## 1    1  0