Statistics Foundation · Lesson 1.3
Types of data.
Data type is one of the first decisions in statistical thinking. It determines how a variable should be summarised, visualised and interpreted. This lesson develops a careful understanding of categorical, numerical, ordinal, binary and time-to-event data.
80–90 minute lesson plan
Learn to recognise data before analysing it.
This lesson is designed to slow students down before analysis. Many statistical mistakes happen because the wrong summary or graph is chosen for the data type. By the end, you should be able to look at a variable and immediately ask: what type of data is this, what summary is suitable, and what interpretation is safe?
0–10 min
Why data type matters
Understand why the type of data controls the summary, graph, interpretation and later statistical method.
10–25 min
Categorical data
Learn nominal, ordinal and binary variables, and how they should be summarised.
25–40 min
Numerical data
Distinguish discrete and continuous numerical data, and understand appropriate summaries.
40–55 min
Measurement scales
Explore nominal, ordinal, interval and ratio scales, with careful examples.
55–70 min
Visual studio
Use an interactive data-type lab to compare bar charts, dot plots, histograms and missingness.
70–85 min
Practice, reflection and quiz
Classify variables, choose summaries, avoid common mistakes and complete the quiz.
Mastery checklist
By the end, you should be able to classify variables confidently.
Separate categorical and numerical variables.
Distinguish nominal, ordinal and binary variables.
Distinguish discrete and continuous numerical variables.
Recognise ID numbers and codes as labels, not measurements.
Choose suitable summaries and visual displays.
Explain why missingness and skewness affect interpretation.