Note: data need to be in the same folder as the analysis script. Otherwise, the path needs to be specified.
library(readr)
tdata <- read_delim("data.txt",
delim = "\t", escape_double = FALSE,
trim_ws = TRUE)
## Rows: 780 Columns: 12
## ── Column specification ────────────────────────────────────────────────────────
## Delimiter: "\t"
## chr (7): subj_code, desktop_conf, attent_conf, Cond_sum, explanation, gender...
## dbl (5): condition, instr_tests, Rating_CC, Rating_SE, age
##
## ℹ Use `spec()` to retrieve the full column specification for this data.
## ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.
Subject demographics:
# demographics
min(tdata$age) # minimum age
## [1] 18
max(tdata$age) # maximum age
## [1] 75
mean(tdata$age) # mean age
## [1] 37.94231
sd(tdata$age) # standard deviation of age
## [1] 12.73167
table(tdata$gender)
##
## 1: male 2: female 3: non-binary
## 388 378 11
## 4: prefer not to say
## 3
First prepare the data set:
Ratings in all conditions:
## Warning: `guides(<scale> = FALSE)` is deprecated. Please use `guides(<scale> =
## "none")` instead.
## Warning: `fun.y` is deprecated. Use `fun` instead.
## `fun.y` is deprecated. Use `fun` instead.
## `fun.y` is deprecated. Use `fun` instead.