What should we measure?
An empty table for the rounds played: add variables as columns, give them a data type, enter each game as a row, and save everything as a CSV or RDS file for R.
What you will learn
With this demo you decide yourself how the rounds of the game with three doors are recorded, and afterwards you can:
- explain that a row is an observation and a column is a variable
- decide for a question which variables have to be recorded, and give them names that R understands directly
- assign each variable a fitting data type: character, double, integer, logical or factor
- save a table as a CSV and as an RDS file and describe why only RDS keeps the data types
Goal: Design the table that records the rounds played of the game with three doors, and decide along the way which facts about a game are noted and in which form their values come.
How to use: The table starts with three empty columns and two empty rows. Each column is a variable, which you name at the top and, if you like, give a data type below. When you move the mouse over the table, a + appears on the right for another column and one below for another game. Every cell can be edited, and Enter jumps to the row below. A value that does not fit the chosen type gets a yellow outline but stays in place. Finally you save the table as CSV or as RDS, and below the buttons stands the R code that reads the file back. The table stays stored in this browser until you choose "Start over".
Each row is an observation, here one game played. Each column is a
variable, a fact we record for every game, such as the door with the car or
the decision between staying and switching. All values in a column share one
data type, and the label in the head of the column shows it the way R shows it
for a tibble: <chr> for text, <dbl> for decimal numbers, <int> for whole
numbers, <lgl> for TRUE and FALSE, and <fct> for categories with fixed
levels. Without a chosen type, the label shows in grey which type R would infer
from the values entered.
Details
- Level
- Beginner
- Modules
- Empirical Research
- Code
5257- Updated
- 2 November 2026
- Status
- published