View the built-in dataset “Tooth Growth” in R Studio

View the built-in dataset “Tooth Growth” in R Studio. Is this in long format or wide format? Wide Long

The correct answer and explanation is:

The ToothGrowth dataset in R is in long format.

Explanation:
A dataset is considered to be in long format when each variable is represented by a single column, and each observation (or measurement) is recorded in multiple rows. In this format, there is usually a column indicating the treatment or condition, and another column indicating the outcome or dependent variable. The long format allows for repeated measures and makes it easier to work with in terms of analysis and modeling, particularly for statistical methods like regression.

The ToothGrowth dataset is structured as follows:

• It contains data on the tooth growth of guinea pigs under different treatment conditions.
• The variables in the dataset include len (the length of the teeth), supp (the supplement type, either Vitamin C or Orange juice), and dose (the dosage of the supplement).
• The data are presented in rows corresponding to different combinations of supplement type and dosage, with the length of the teeth being the measured outcome.

In this case, every row corresponds to a single observation with a specific combination of supp and dose, so the dataset is in long format.

Long Format

This format is typically advantageous for data analysis, especially when performing statistical tests like ANOVA or regression, where the categorical variables (like supplement type and dosage) are handled as factors. It is easier to manipulate long format data using functions from packages like tidyverse in R, as it allows for more flexibility when applying filtering, grouping, or summarizing operations.

Wide Format

On the other hand, in wide format, each level of the categorical variable would be spread out into separate columns (e.g., a column for each level of the supplement type and dosage), which can make the dataset less flexible for certain types of analyses, especially when the data have repeated measures or when a longitudinal approach is needed.