Q&A 17 What is the difference between categorical and numerical variables?
17.1 Explanation
In data analysis, variables are typically classified into two major types:
17.1.1 🔷 Categorical Variables
These represent groups, labels, or categories. They describe qualities, not quantities.
Nominal: Categories with no natural order
Example:"red","blue","green"Ordinal: Categories with a meaningful order
Example:"low","medium","high"
17.1.2 🔶 Numerical Variables
These represent measurable quantities and describe how much or how many.
Discrete: Countable, whole-number values
Example: Number of children, cars, booksContinuous: Measurable on a scale; can take any value within a range
Example: Height, weight, temperature
Correctly identifying variable types is critical. It informs the choice of: - Statistical methods (e.g., t-tests vs chi-squared tests) - Visualizations (e.g., histograms for continuous vs bar plots for categorical) - Feature encoding in machine learning (e.g., one-hot encoding for nominal variables)