CSV of data: https://github.com/vhilab/psych-360/blob/master/psych-360.csv
Video Files: https://stanfordvr.com/psych-360-videos
Each row represents a sample, which in this case is a participant watching a video. Each participant watched five videos, so each participant has five rows associated with it.
location
: Locations of the study. Lab 1 and Lab2 are the rooms of our lab and Museum is our booth at The Tech Interactive in San Jose.pid
: The IDs of the participants. They are unique per location not across locations.video
: The video the participants watched.order
: The order of the video from the participant’s perspective.age
: The age of the participant. (19-/19-25/26-45/45+)gender
: The gender of the participant. (Female/Male/Other)race
: The race of the participant.experience
: Whether the participant had prior VR experience.arousal
: The arousal level the participant reported after watching the video.presence
: The presence level the participant reported after watching the video.sickness
: The simulator sickess level the participant reported after watching the video.preference
: The preference level the participant reported after watching the video.exploration
: The proportion of a full 360-degree horizontal sweep participant made watching the video
The first ten results are show below.
location | pid | video | order | age | gender | race | experience | arousal | presence | sickness | preference | exploration |
---|---|---|---|---|---|---|---|---|---|---|---|---|
Lab1 | 5 | Pond | 1 | 19-25 | Male | White, Caucasian, Non Hispanic | TRUE | 2 | 2.666667 | 1.0 | 2.5 | 0.8944242 |
Lab1 | 5 | Baboon1 | 2 | 19-25 | Male | White, Caucasian, Non Hispanic | TRUE | 5 | 3.666667 | 1.0 | 5.0 | 0.4832044 |
Lab1 | 5 | Concert1 | 3 | 19-25 | Male | White, Caucasian, Non Hispanic | TRUE | 3 | 2.000000 | 1.0 | 1.5 | 0.4845384 |
Lab1 | 5 | Rapunzel | 4 | 19-25 | Male | White, Caucasian, Non Hispanic | TRUE | 5 | 3.000000 | 1.0 | 1.0 | 0.4024281 |
Lab1 | 5 | Chickens | 5 | 19-25 | Male | White, Caucasian, Non Hispanic | TRUE | 3 | 3.000000 | 1.0 | 2.0 | 1.0000000 |
Lab1 | 6 | Waterfall3 | 1 | 19-25 | Female | Chinese | TRUE | 5 | 3.666667 | 1.0 | 3.5 | 0.9329999 |
Lab1 | 6 | Rocks | 2 | 19-25 | Female | Chinese | TRUE | 3 | 3.333333 | 1.0 | 3.0 | 0.8228508 |
Lab1 | 6 | Forest | 3 | 19-25 | Female | Chinese | TRUE | 5 | 4.000000 | 1.5 | 1.5 | 0.7769808 |
Lab1 | 6 | Bees | 4 | 19-25 | Female | Chinese | TRUE | 7 | 3.666667 | 1.0 | 4.5 | 0.5573311 |
Lab1 | 6 | March | 5 | 19-25 | Female | Chinese | TRUE | 7 | 4.000000 | 1.5 | 2.5 | 1.0000000 |
Each variable is shown descriptively and explored further below.
Note that the unique identifier for a participant is the pair of variables (location, pid).
# When grouping by PID only, how many PIDs have more than 5 rows associated with them?
psych_360 %>%
group_by(pid) %>%
count() %>%
filter(n != 5) %>%
nrow
## [1] 59
# Instead, it's better to group by PID and Location if you want participants to be uniquely grouped
psych_360 %>%
group_by(pid, location) %>%
count() %>%
filter(n != 5) %>%
nrow()
## [1] 0